diff options
Diffstat (limited to 'docs/dev/reference')
137 files changed, 7407 insertions, 1049 deletions
diff --git a/docs/dev/reference/AIC.mmkin.html b/docs/dev/reference/AIC.mmkin.html index b332257e..8c791755 100644 --- a/docs/dev/reference/AIC.mmkin.html +++ b/docs/dev/reference/AIC.mmkin.html @@ -73,7 +73,7 @@ same dataset." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ same dataset." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -187,8 +187,7 @@ dataframe if there are several fits in the column).</p> <span class='va'>f</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"FOCUS A"</span> <span class='op'>=</span> <span class='va'>FOCUS_2006_A</span>, <span class='st'>"FOCUS C"</span> <span class='op'>=</span> <span class='va'>FOCUS_2006_C</span><span class='op'>)</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> -#> <span class='warning'>false convergence (8)</span></div><div class='input'> <span class='co'># We get a warning because the FOMC model does not converge for the</span> + <span class='co'># We get a warning because the FOMC model does not converge for the</span> <span class='co'># FOCUS A dataset, as it is well described by SFO</span> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># We get a single number for a single fit</span> @@ -199,15 +198,15 @@ dataframe if there are several fits in the column).</p> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> df AIC #> SFO 3 55.28197 -#> FOMC 4 57.28211 +#> FOMC 4 57.28222 #> DFOP 5 59.28197</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span>, k <span class='op'>=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='co'># If we do not penalize additional parameters, we get nearly the same</span> </div><div class='output co'>#> df AIC #> SFO 3 49.28197 -#> FOMC 4 49.28211 +#> FOMC 4 49.28222 #> DFOP 5 49.28197</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>BIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># Comparing the BIC gives a very similar picture</span> </div><div class='output co'>#> df BIC #> SFO 3 55.52030 -#> FOMC 4 57.59987 +#> FOMC 4 57.59999 #> DFOP 5 59.67918</div><div class='input'> <span class='co'># For FOCUS C, the more complex models fit better</span> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS C"</span><span class='op'>]</span><span class='op'>)</span> diff --git a/docs/dev/reference/CAKE_export.html b/docs/dev/reference/CAKE_export.html index d3f45bf0..e187772f 100644 --- a/docs/dev/reference/CAKE_export.html +++ b/docs/dev/reference/CAKE_export.html @@ -73,7 +73,7 @@ specified as well." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ specified as well." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/D24_2014.html b/docs/dev/reference/D24_2014.html index 2498c58e..9ecb6330 100644 --- a/docs/dev/reference/D24_2014.html +++ b/docs/dev/reference/D24_2014.html @@ -77,7 +77,7 @@ constrained by data protection regulations." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> diff --git a/docs/dev/reference/DFOP.solution.html b/docs/dev/reference/DFOP.solution.html index 22b28732..3ee660f2 100644 --- a/docs/dev/reference/DFOP.solution.html +++ b/docs/dev/reference/DFOP.solution.html @@ -73,7 +73,7 @@ two exponential decline functions." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ two exponential decline functions." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/Extract.mmkin.html b/docs/dev/reference/Extract.mmkin.html index 0c02355f..8381337a 100644 --- a/docs/dev/reference/Extract.mmkin.html +++ b/docs/dev/reference/Extract.mmkin.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -220,7 +220,7 @@ either a list of mkinfit objects or a single mkinfit object.</p></td> <span class='op'>)</span> </div><div class='output co'>#> $par #> parent_0 log_alpha log_beta sigma -#> 99.666193 2.549849 5.050586 1.890202 +#> 99.666192 2.549850 5.050586 1.890202 #> #> $objective #> [1] 28.58291 diff --git a/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html b/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html index 16d12378..a188430d 100644 --- a/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html +++ b/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html @@ -76,7 +76,7 @@ in this fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ in this fit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html index 6b8a6119..0bee1c16 100644 --- a/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html +++ b/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html @@ -76,7 +76,7 @@ in this fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ in this fit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html index 076a66c6..460fdf0d 100644 --- a/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html +++ b/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html @@ -76,7 +76,7 @@ in this fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ in this fit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html index 08f1d416..c1a5fdff 100644 --- a/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html +++ b/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html @@ -76,7 +76,7 @@ in this fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ in this fit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/FOCUS_2006_datasets.html b/docs/dev/reference/FOCUS_2006_datasets.html index df4651f8..fb3a8f17 100644 --- a/docs/dev/reference/FOCUS_2006_datasets.html +++ b/docs/dev/reference/FOCUS_2006_datasets.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/FOMC.solution.html b/docs/dev/reference/FOMC.solution.html index ed5c4d21..1a5124e0 100644 --- a/docs/dev/reference/FOMC.solution.html +++ b/docs/dev/reference/FOMC.solution.html @@ -73,7 +73,7 @@ a decreasing rate constant." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ a decreasing rate constant." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/HS.solution.html b/docs/dev/reference/HS.solution.html index 8cf5c7f9..1b79e8b6 100644 --- a/docs/dev/reference/HS.solution.html +++ b/docs/dev/reference/HS.solution.html @@ -73,7 +73,7 @@ between them." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ between them." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/IORE.solution.html b/docs/dev/reference/IORE.solution.html index 29d615dc..bc17319e 100644 --- a/docs/dev/reference/IORE.solution.html +++ b/docs/dev/reference/IORE.solution.html @@ -73,7 +73,7 @@ a concentration dependent rate constant." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ a concentration dependent rate constant." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/NAFTA_SOP_2015-1.png b/docs/dev/reference/NAFTA_SOP_2015-1.png Binary files differindex 4d823d77..4f0d7833 100644 --- a/docs/dev/reference/NAFTA_SOP_2015-1.png +++ b/docs/dev/reference/NAFTA_SOP_2015-1.png diff --git a/docs/dev/reference/NAFTA_SOP_2015.html b/docs/dev/reference/NAFTA_SOP_2015.html index 4243faba..fb65fec8 100644 --- a/docs/dev/reference/NAFTA_SOP_2015.html +++ b/docs/dev/reference/NAFTA_SOP_2015.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/NAFTA_SOP_Attachment-1.png b/docs/dev/reference/NAFTA_SOP_Attachment-1.png Binary files differindex 6eb10cde..9417685e 100644 --- a/docs/dev/reference/NAFTA_SOP_Attachment-1.png +++ b/docs/dev/reference/NAFTA_SOP_Attachment-1.png diff --git a/docs/dev/reference/NAFTA_SOP_Attachment.html b/docs/dev/reference/NAFTA_SOP_Attachment.html index de984984..311a7c61 100644 --- a/docs/dev/reference/NAFTA_SOP_Attachment.html +++ b/docs/dev/reference/NAFTA_SOP_Attachment.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -193,7 +193,7 @@ #> Estimate Pr(>t) Lower Upper #> parent_0 9.99e+01 1.41e-26 98.8116 101.0810 #> k1 2.67e-02 5.05e-06 0.0243 0.0295 -#> k2 2.42e-12 5.00e-01 0.0000 Inf +#> k2 2.26e-12 5.00e-01 0.0000 Inf #> g 6.47e-01 3.67e-06 0.6248 0.6677 #> sigma 1.27e+00 8.91e-06 0.8395 1.6929 #> @@ -202,7 +202,7 @@ #> DT50 DT90 DT50_rep #> SFO 67.7 2.25e+02 6.77e+01 #> IORE 58.2 1.07e+03 3.22e+02 -#> DFOP 55.5 5.22e+11 2.86e+11 +#> DFOP 55.5 5.59e+11 3.07e+11 #> #> Representative half-life: #> [1] 321.51</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>nafta_att_p5a</span><span class='op'>)</span> diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png Binary files differindex bca41e2c..17a35806 100644 --- a/docs/dev/reference/Rplot001.png +++ b/docs/dev/reference/Rplot001.png diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png Binary files differindex 9b97a634..32c64fcd 100644 --- a/docs/dev/reference/Rplot002.png +++ b/docs/dev/reference/Rplot002.png diff --git a/docs/dev/reference/Rplot003.png b/docs/dev/reference/Rplot003.png Binary files differindex ff6bc722..5726488c 100644 --- a/docs/dev/reference/Rplot003.png +++ b/docs/dev/reference/Rplot003.png diff --git a/docs/dev/reference/Rplot004.png b/docs/dev/reference/Rplot004.png Binary files differindex 98dd019e..c279f831 100644 --- a/docs/dev/reference/Rplot004.png +++ b/docs/dev/reference/Rplot004.png diff --git a/docs/dev/reference/Rplot005.png b/docs/dev/reference/Rplot005.png Binary files differindex 5e675828..92c7cc2d 100644 --- a/docs/dev/reference/Rplot005.png +++ b/docs/dev/reference/Rplot005.png diff --git a/docs/dev/reference/Rplot006.png b/docs/dev/reference/Rplot006.png Binary files differindex da52f580..4c728f4e 100644 --- a/docs/dev/reference/Rplot006.png +++ b/docs/dev/reference/Rplot006.png diff --git a/docs/dev/reference/Rplot007.png b/docs/dev/reference/Rplot007.png Binary files differindex fce3b6ee..10b7455a 100644 --- a/docs/dev/reference/Rplot007.png +++ b/docs/dev/reference/Rplot007.png diff --git a/docs/dev/reference/SFO.solution.html b/docs/dev/reference/SFO.solution.html index b3e7ef9a..43c434c6 100644 --- a/docs/dev/reference/SFO.solution.html +++ b/docs/dev/reference/SFO.solution.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/SFORB.solution.html b/docs/dev/reference/SFORB.solution.html index 9310212f..807fbe5c 100644 --- a/docs/dev/reference/SFORB.solution.html +++ b/docs/dev/reference/SFORB.solution.html @@ -76,7 +76,7 @@ and no substance in the bound fraction." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ and no substance in the bound fraction." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/add_err-1.png b/docs/dev/reference/add_err-1.png Binary files differindex d2ce797f..9ba106db 100644 --- a/docs/dev/reference/add_err-1.png +++ b/docs/dev/reference/add_err-1.png diff --git a/docs/dev/reference/add_err-2.png b/docs/dev/reference/add_err-2.png Binary files differindex ac220c9e..3088c40e 100644 --- a/docs/dev/reference/add_err-2.png +++ b/docs/dev/reference/add_err-2.png diff --git a/docs/dev/reference/add_err-3.png b/docs/dev/reference/add_err-3.png Binary files differindex 40465b71..493a761a 100644 --- a/docs/dev/reference/add_err-3.png +++ b/docs/dev/reference/add_err-3.png diff --git a/docs/dev/reference/add_err.html b/docs/dev/reference/add_err.html index 6ea30515..b94cef29 100644 --- a/docs/dev/reference/add_err.html +++ b/docs/dev/reference/add_err.html @@ -74,7 +74,7 @@ may depend on the predicted value and is specified as a standard deviation." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ may depend on the predicted value and is specified as a standard deviation." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/aw.html b/docs/dev/reference/aw.html index ef808dd8..3b06f2a6 100644 --- a/docs/dev/reference/aw.html +++ b/docs/dev/reference/aw.html @@ -74,7 +74,7 @@ by Burnham and Anderson (2004)." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ by Burnham and Anderson (2004)." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/confint.mkinfit.html b/docs/dev/reference/confint.mkinfit.html index 515a7c9e..2237a539 100644 --- a/docs/dev/reference/confint.mkinfit.html +++ b/docs/dev/reference/confint.mkinfit.html @@ -79,7 +79,7 @@ method of Venzon and Moolgavkar (1988)." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -128,7 +128,7 @@ method of Venzon and Moolgavkar (1988)." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -273,68 +273,69 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/identical.html'>identical</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span><span class='op'>(</span><span class='st'>"NOT_CRAN"</span><span class='op'>)</span>, <span class='st'>"true"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span> <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fu'>parallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>1</span> <span class='op'>}</span> <span class='kw'>else</span> <span class='op'>{</span> - <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fl'>1</span> + <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fl'>1</span> <span class='op'>}</span> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span><span class='op'>(</span><span class='st'>"TRAVIS"</span><span class='op'>)</span> <span class='op'>!=</span> <span class='st'>""</span><span class='op'>)</span> <span class='va'>n_cores</span> <span class='op'>=</span> <span class='fl'>1</span> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>[</span><span class='st'>"sysname"</span><span class='op'>]</span> <span class='op'>==</span> <span class='st'>"Windows"</span><span class='op'>)</span> <span class='va'>n_cores</span> <span class='op'>=</span> <span class='fl'>1</span> -<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, + use_of_ff <span class='op'>=</span> <span class='st'>"min"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>SFO_SFO.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>f_d_1</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span><span class='va'>ci_profile</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"profile"</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span> </div><div class='output co'>#> user system elapsed -#> 3.900 0.929 3.548 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span> +#> 4.295 1.008 3.959 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span> <span class='co'># If we additionally exclude parent_0 (the confidence of which is often of</span> -<span class='co'># minor interest), we get a nice performance improvement from about 50</span> -<span class='co'># seconds to about 12 seconds if we use at least four cores</span> +<span class='co'># minor interest), we get a nice performance improvement if we use at least 4 cores</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span><span class='va'>ci_profile_no_parent_0</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"profile"</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"k_parent_sink"</span>, <span class='st'>"k_parent_m1"</span>, <span class='st'>"k_m1_sink"</span>, <span class='st'>"sigma"</span><span class='op'>)</span>, cores <span class='op'>=</span> <span class='va'>n_cores</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> <span class='warning'>Warning: scheduled cores 3, 2, 1 encountered errors in user code, all values of the jobs will be affected</span></div><div class='output co'>#> <span class='error'>Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.009 0.034 0.257</span></div><div class='input'><span class='va'>ci_profile</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.456003640 1.027703e+02 -#> k_parent 0.090911032 1.071578e-01 -#> k_m1 0.003892606 6.702775e-03 -#> f_parent_to_m1 0.471328495 5.611550e-01 -#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='va'>ci_quadratic_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> user system elapsed +#> 1.451 0.126 0.923 </div><div class='input'><span class='va'>ci_profile</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.456003640 1.027703e+02 +#> k_parent_sink 0.040762501 5.549764e-02 +#> k_parent_m1 0.046786482 5.500879e-02 +#> k_m1_sink 0.003892605 6.702778e-03 +#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='va'>ci_quadratic_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> <span class='va'>ci_quadratic_transformed</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.403833585 102.79311650 -#> k_parent 0.090823771 0.10725430 -#> k_m1 0.004012219 0.00689755 -#> f_parent_to_m1 0.469118824 0.55959615 -#> sigma 2.396089689 3.85491806</div><div class='input'><span class='va'>ci_quadratic_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403841640 1.027931e+02 +#> k_parent_sink 0.041033378 5.596269e-02 +#> k_parent_m1 0.046777902 5.511931e-02 +#> k_m1_sink 0.004012217 6.897547e-03 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='va'>ci_quadratic_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> <span class='va'>ci_quadratic_untransformed</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.403833589 1.027931e+02 -#> k_parent 0.090491913 1.069035e-01 -#> k_m1 0.003835485 6.685823e-03 -#> f_parent_to_m1 0.469113477 5.598387e-01 -#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='co'># Against the expectation based on Bates and Watts (1988), the confidence</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403841645 102.79312449 +#> k_parent_sink 0.040485331 0.05535491 +#> k_parent_m1 0.046611582 0.05494364 +#> k_m1_sink 0.003835483 0.00668582 +#> sigma 2.396089689 3.85491806</div><div class='input'><span class='co'># Against the expectation based on Bates and Watts (1988), the confidence</span> <span class='co'># intervals based on the internal parameter transformation are less</span> <span class='co'># congruent with the likelihood based intervals. Note the superiority of the</span> <span class='co'># interval based on the untransformed fit for k_m1_sink</span> <span class='va'>rel_diffs_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span><span class='op'>(</span><span class='op'>(</span><span class='va'>ci_quadratic_transformed</span> <span class='op'>-</span> <span class='va'>ci_profile</span><span class='op'>)</span><span class='op'>/</span><span class='va'>ci_profile</span><span class='op'>)</span> <span class='va'>rel_diffs_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span><span class='op'>(</span><span class='op'>(</span><span class='va'>ci_quadratic_untransformed</span> <span class='op'>-</span> <span class='va'>ci_profile</span><span class='op'>)</span><span class='op'>/</span><span class='va'>ci_profile</span><span class='op'>)</span> <span class='va'>rel_diffs_transformed</span> <span class='op'><</span> <span class='va'>rel_diffs_untransformed</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 FALSE FALSE -#> k_parent TRUE TRUE -#> k_m1 FALSE FALSE -#> f_parent_to_m1 TRUE FALSE -#> sigma TRUE FALSE</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_transformed</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 0.000541 0.000222 -#> k_parent 0.000960 0.000900 -#> k_m1 0.030700 0.029100 -#> f_parent_to_m1 0.004690 0.002780 -#> sigma 0.055000 0.032700</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_untransformed</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 0.000541 0.000222 -#> k_parent 0.004610 0.002370 -#> k_m1 0.014700 0.002530 -#> f_parent_to_m1 0.004700 0.002350 -#> sigma 0.055000 0.032700</div><div class='input'> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 FALSE FALSE +#> k_parent_sink TRUE FALSE +#> k_parent_m1 TRUE FALSE +#> k_m1_sink FALSE FALSE +#> sigma FALSE FALSE</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_transformed</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent_sink 0.006650 0.008380 +#> k_parent_m1 0.000183 0.002010 +#> k_m1_sink 0.030700 0.029100 +#> sigma 0.055000 0.032700</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_untransformed</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent_sink 0.006800 0.002570 +#> k_parent_m1 0.003740 0.001180 +#> k_m1_sink 0.014700 0.002530 +#> sigma 0.055000 0.032700</div><div class='input'> <span class='co'># Investigate a case with formation fractions</span> <span class='va'>f_d_2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> @@ -348,14 +349,14 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, #> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='va'>ci_quadratic_transformed_ff</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_2</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> <span class='va'>ci_quadratic_transformed_ff</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.403833585 102.79311650 +#> parent_0 96.403833578 102.79311649 #> k_parent 0.090823771 0.10725430 #> k_m1 0.004012219 0.00689755 #> f_parent_to_m1 0.469118824 0.55959615 #> sigma 2.396089689 3.85491806</div><div class='input'><span class='va'>ci_quadratic_untransformed_ff</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_2</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> <span class='va'>ci_quadratic_untransformed_ff</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.403833589 1.027931e+02 +#> parent_0 96.403833583 1.027931e+02 #> k_parent 0.090491913 1.069035e-01 #> k_m1 0.003835485 6.685823e-03 #> f_parent_to_m1 0.469113477 5.598387e-01 @@ -373,15 +374,15 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, #> f_parent_to_m1 TRUE FALSE #> sigma TRUE FALSE</div><div class='input'><span class='va'>rel_diffs_transformed_ff</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 0.0005408689 0.0002217234 +#> parent_0 0.0005408690 0.0002217233 #> k_parent 0.0009598532 0.0009001864 -#> k_m1 0.0307283044 0.0290588365 -#> f_parent_to_m1 0.0046881768 0.0027780063 +#> k_m1 0.0307283041 0.0290588361 +#> f_parent_to_m1 0.0046881769 0.0027780063 #> sigma 0.0550252516 0.0327066836</div><div class='input'><span class='va'>rel_diffs_untransformed_ff</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 0.0005408689 0.0002217233 -#> k_parent 0.0046102155 0.0023732281 -#> k_m1 0.0146740688 0.0025291817 +#> parent_0 0.0005408689 0.0002217232 +#> k_parent 0.0046102156 0.0023732281 +#> k_m1 0.0146740690 0.0025291820 #> f_parent_to_m1 0.0046995211 0.0023457712 #> sigma 0.0550252516 0.0327066836</div><div class='input'> <span class='co'># The profiling for the following fit does not finish in a reasonable time,</span> @@ -395,18 +396,18 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, error_model_algorithm <span class='op'>=</span> <span class='st'>"direct"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_tc_2</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 94.596126334 106.19944007 -#> k_M1 0.037605408 0.04490759 -#> k_M2 0.008568739 0.01087675 -#> f_parent_to_M1 0.021463787 0.62023881 -#> f_parent_to_M2 0.015166531 0.37975349 -#> k1 0.273897467 0.33388084 -#> k2 0.018614555 0.02250379 -#> g 0.671943606 0.73583278 -#> sigma_low 0.251283766 0.83992113 -#> rsd_high 0.040411014 0.07662005</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_tc_2</span>, <span class='st'>"parent_0"</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> +#> parent_0 94.596039609 106.19954892 +#> k_M1 0.037605368 0.04490762 +#> k_M2 0.008568731 0.01087676 +#> f_parent_to_M1 0.021462489 0.62023882 +#> f_parent_to_M2 0.015165617 0.37975348 +#> k1 0.273897348 0.33388101 +#> k2 0.018614554 0.02250378 +#> g 0.671943411 0.73583305 +#> sigma_low 0.251283495 0.83992077 +#> rsd_high 0.040411024 0.07662008</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_tc_2</span>, <span class='st'>"parent_0"</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> </div><div class='output co'>#> 2.5% 97.5% -#> parent_0 94.59613 106.1994</div><div class='input'><span class='co'># }</span> +#> parent_0 94.59604 106.1995</div><div class='input'><span class='co'># }</span> </div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> diff --git a/docs/dev/reference/create_deg_func.html b/docs/dev/reference/create_deg_func.html index 4945d157..65a682bb 100644 --- a/docs/dev/reference/create_deg_func.html +++ b/docs/dev/reference/create_deg_func.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -181,8 +181,8 @@ deSolve <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, replications <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Loading required package: rbenchmark</span></div><div class='output co'>#> test replications elapsed relative user.self sys.self user.child -#> 1 analytical 2 0.396 1.000 0.395 0 0 -#> 2 deSolve 2 0.694 1.753 0.693 0 0 +#> 1 analytical 2 0.396 1.00 0.396 0 0 +#> 2 deSolve 2 0.709 1.79 0.707 0 0 #> sys.child #> 1 0 #> 2 0</div><div class='input'> <span class='va'>DFOP_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> @@ -193,8 +193,8 @@ deSolve <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>DFOP_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, replications <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span> </div><div class='output co'>#> test replications elapsed relative user.self sys.self user.child -#> 1 analytical 2 0.838 1.000 0.838 0.001 0 -#> 2 deSolve 2 1.573 1.877 1.572 0.000 0 +#> 1 analytical 2 0.844 1.000 0.844 0 0 +#> 2 deSolve 2 1.624 1.924 1.624 0 0 #> sys.child #> 1 0 #> 2 0</div><div class='input'><span class='co'># }</span> diff --git a/docs/dev/reference/dimethenamid_2018-1.png b/docs/dev/reference/dimethenamid_2018-1.png Binary files differnew file mode 100644 index 00000000..52b8a2be --- /dev/null +++ b/docs/dev/reference/dimethenamid_2018-1.png diff --git a/docs/dev/reference/dimethenamid_2018-2.png b/docs/dev/reference/dimethenamid_2018-2.png Binary files differnew file mode 100644 index 00000000..a81b2aaf --- /dev/null +++ b/docs/dev/reference/dimethenamid_2018-2.png diff --git a/docs/dev/reference/dimethenamid_2018.html b/docs/dev/reference/dimethenamid_2018.html index 21dea623..160dcaa3 100644 --- a/docs/dev/reference/dimethenamid_2018.html +++ b/docs/dev/reference/dimethenamid_2018.html @@ -77,7 +77,7 @@ constrained by data protection regulations." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -168,7 +168,7 @@ constrained by data protection regulations.</p> <p>Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria (2018) Renewal Assessment Report Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour Rev. 2 - November 2017 -<a href='http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-5211'>http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-5211</a></p> +<a href='https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716'>https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716</a></p> <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> <p>The R code used to create this data object is installed with this package @@ -203,7 +203,476 @@ specific pieces of information in the comments.</p> #> Elliot 2 0.75 33.37 23 #> Flaach 0.40 NA 20 #> BBA 2.2 0.40 NA 20 -#> BBA 2.3 0.40 NA 20</div></pre> +#> BBA 2.3 0.40 NA 20</div><div class='input'><span class='va'>dmta_ds</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>:</span><span class='fl'>8</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'>{</span> + <span class='va'>ds_i</span> <span class='op'><-</span> <span class='va'>dimethenamid_2018</span><span class='op'>$</span><span class='va'>ds</span><span class='op'>[[</span><span class='va'>i</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>data</span> + <span class='va'>ds_i</span><span class='op'>[</span><span class='va'>ds_i</span><span class='op'>$</span><span class='va'>name</span> <span class='op'>==</span> <span class='st'>"DMTAP"</span>, <span class='st'>"name"</span><span class='op'>]</span> <span class='op'><-</span> <span class='st'>"DMTA"</span> + <span class='va'>ds_i</span><span class='op'>$</span><span class='va'>time</span> <span class='op'><-</span> <span class='va'>ds_i</span><span class='op'>$</span><span class='va'>time</span> <span class='op'>*</span> <span class='va'>dimethenamid_2018</span><span class='op'>$</span><span class='va'>f_time_norm</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span> + <span class='va'>ds_i</span> +<span class='op'>}</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>dmta_ds</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='va'>dimethenamid_2018</span><span class='op'>$</span><span class='va'>ds</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='va'>ds</span><span class='op'>$</span><span class='va'>title</span><span class='op'>)</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Borstel"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/cbind.html'>rbind</a></span><span class='op'>(</span><span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Borstel 1"</span><span class='op'>]</span><span class='op'>]</span>, <span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Borstel 2"</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Borstel 1"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='cn'>NULL</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Borstel 2"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='cn'>NULL</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Elliot"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/cbind.html'>rbind</a></span><span class='op'>(</span><span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Elliot 1"</span><span class='op'>]</span><span class='op'>]</span>, <span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Elliot 2"</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Elliot 1"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='cn'>NULL</span> +<span class='va'>dmta_ds</span><span class='op'>[[</span><span class='st'>"Elliot 2"</span><span class='op'>]</span><span class='op'>]</span> <span class='op'><-</span> <span class='cn'>NULL</span> +<span class='co'># \dontrun{</span> +<span class='va'>dfop_sfo3_plus</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> + DMTA <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"M23"</span>, <span class='st'>"M27"</span>, <span class='st'>"M31"</span><span class='op'>)</span><span class='op'>)</span>, + M23 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, + M27 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, + M31 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"M27"</span>, sink <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>, + quiet <span class='op'>=</span> <span class='cn'>TRUE</span> +<span class='op'>)</span> +<span class='va'>f_dmta_mkin_tc</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span> + <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"DFOP-SFO3+"</span> <span class='op'>=</span> <span class='va'>dfop_sfo3_plus</span><span class='op'>)</span>, + <span class='va'>dmta_ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> +<span class='fu'><a href='nlmixr.mmkin.html'>nlmixr_model</a></span><span class='op'>(</span><span class='va'>f_dmta_mkin_tc</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)</span></div><div class='output co'>#> function () +#> { +#> ini({ +#> DMTA_0 = 98.7697627680706 +#> eta.DMTA_0 ~ 2.35171765917765 +#> log_k_M23 = -3.92162409637283 +#> eta.log_k_M23 ~ 0.549278519419884 +#> log_k_M27 = -4.33774620773911 +#> eta.log_k_M27 ~ 0.864474956685295 +#> log_k_M31 = -4.24767627688461 +#> eta.log_k_M31 ~ 0.750297149164171 +#> log_k1 = -2.2341008812259 +#> eta.log_k1 ~ 0.902976221565793 +#> log_k2 = -3.7762779983269 +#> eta.log_k2 ~ 1.57684519529298 +#> g_qlogis = 0.450175725479389 +#> eta.g_qlogis ~ 3.0851335687675 +#> f_DMTA_tffm0_1_qlogis = -2.09240906629456 +#> eta.f_DMTA_tffm0_1_qlogis ~ 0.3 +#> f_DMTA_tffm0_2_qlogis = -2.18057573598794 +#> eta.f_DMTA_tffm0_2_qlogis ~ 0.3 +#> f_DMTA_tffm0_3_qlogis = -2.14267187609763 +#> eta.f_DMTA_tffm0_3_qlogis ~ 0.3 +#> sigma_low_DMTA = 0.697933852349996 +#> rsd_high_DMTA = 0.0257724286053519 +#> sigma_low_M23 = 0.697933852349996 +#> rsd_high_M23 = 0.0257724286053519 +#> sigma_low_M27 = 0.697933852349996 +#> rsd_high_M27 = 0.0257724286053519 +#> sigma_low_M31 = 0.697933852349996 +#> rsd_high_M31 = 0.0257724286053519 +#> }) +#> model({ +#> DMTA_0_model = DMTA_0 + eta.DMTA_0 +#> DMTA(0) = DMTA_0_model +#> k_M23 = exp(log_k_M23 + eta.log_k_M23) +#> k_M27 = exp(log_k_M27 + eta.log_k_M27) +#> k_M31 = exp(log_k_M31 + eta.log_k_M31) +#> k1 = exp(log_k1 + eta.log_k1) +#> k2 = exp(log_k2 + eta.log_k2) +#> g = expit(g_qlogis + eta.g_qlogis) +#> f_DMTA_tffm0_1 = expit(f_DMTA_tffm0_1_qlogis + eta.f_DMTA_tffm0_1_qlogis) +#> f_DMTA_tffm0_2 = expit(f_DMTA_tffm0_2_qlogis + eta.f_DMTA_tffm0_2_qlogis) +#> f_DMTA_tffm0_3 = expit(f_DMTA_tffm0_3_qlogis + eta.f_DMTA_tffm0_3_qlogis) +#> f_DMTA_to_M23 = f_DMTA_tffm0_1 +#> f_DMTA_to_M27 = f_DMTA_tffm0_2 * (1 - f_DMTA_tffm0_1) +#> f_DMTA_to_M31 = f_DMTA_tffm0_3 * (1 - f_DMTA_tffm0_2) * +#> (1 - f_DMTA_tffm0_1) +#> d/dt(DMTA) = -((k1 * g * exp(-k1 * time) + k2 * (1 - +#> g) * exp(-k2 * time))/(g * exp(-k1 * time) + (1 - +#> g) * exp(-k2 * time))) * DMTA +#> d/dt(M23) = +f_DMTA_to_M23 * ((k1 * g * exp(-k1 * time) + +#> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + +#> (1 - g) * exp(-k2 * time))) * DMTA - k_M23 * M23 +#> d/dt(M27) = +f_DMTA_to_M27 * ((k1 * g * exp(-k1 * time) + +#> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + +#> (1 - g) * exp(-k2 * time))) * DMTA - k_M27 * M27 + +#> k_M31 * M31 +#> d/dt(M31) = +f_DMTA_to_M31 * ((k1 * g * exp(-k1 * time) + +#> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + +#> (1 - g) * exp(-k2 * time))) * DMTA - k_M31 * M31 +#> DMTA ~ add(sigma_low_DMTA) + prop(rsd_high_DMTA) +#> M23 ~ add(sigma_low_M23) + prop(rsd_high_M23) +#> M27 ~ add(sigma_low_M27) + prop(rsd_high_M27) +#> M31 ~ add(sigma_low_M31) + prop(rsd_high_M31) +#> }) +#> } +#> <environment: 0x555559c00ce8></div><div class='input'><span class='co'># The focei fit takes about four minutes on my system</span> +<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span> + <span class='va'>f_dmta_nlmixr_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_dmta_mkin_tc</span>, est <span class='op'>=</span> <span class='st'>"focei"</span>, + control <span class='op'>=</span> <span class='fu'>nlmixr</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/foceiControl.html'>foceiControl</a></span><span class='op'>(</span>print <span class='op'>=</span> <span class='fl'>500</span><span class='op'>)</span><span class='op'>)</span> +<span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:02 +#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:04 +#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:01 +#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:08 +#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:07 +#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:07 +#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:00 +#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> [====|====|====|====|====|====|====|====|====|====] 0:00:00 +#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> [1] "CMT"</div><div class='output co'>#> <span class='message'>RxODE 1.1.0 using 8 threads (see ?getRxThreads)</span> +#> <span class='message'> no cache: create with `rxCreateCache()`</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | DMTA_0 | log_k_M23 | log_k_M27 | log_k_M31 | +#> |.....................| log_k1 | log_k2 | g_qlogis |f_DMTA_tffm0_1_qlogis | +#> |.....................|f_DMTA_tffm0_2_qlogis |f_DMTA_tffm0_3_qlogis | sigma_low | rsd_high | +#> |.....................| o1 | o2 | o3 | o4 | +#> |.....................| o5 | o6 | o7 | o8 | +#> <span style='text-decoration: underline;'>|.....................| o9 | o10 |...........|...........|</span> +#> calculating covariance matrix +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: S matrix non-positive definite</span></div><div class='output co'>#> <span class='warning'>Warning: using R matrix to calculate covariance</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate and covariance; see $scaleInfo</span></div><div class='output co'>#> user system elapsed +#> 227.879 9.742 237.728 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>f_dmta_nlmixr_focei</span><span class='op'>)</span> +</div><div class='output co'>#> nlmixr version used for fitting: 2.0.4 +#> mkin version used for pre-fitting: 1.1.0 +#> R version used for fitting: 4.1.0 +#> Date of fit: Tue Jul 27 16:02:33 2021 +#> Date of summary: Tue Jul 27 16:02:34 2021 +#> +#> Equations: +#> d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * +#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) +#> * DMTA +#> d_M23/dt = + f_DMTA_to_M23 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M23 * M23 +#> d_M27/dt = + f_DMTA_to_M27 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M27 * M27 + k_M31 * M31 +#> d_M31/dt = + f_DMTA_to_M31 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M31 * M31 +#> +#> Data: +#> 568 observations of 4 variable(s) grouped in 6 datasets +#> +#> Degradation model predictions using RxODE +#> +#> Fitted in 237.547 s +#> +#> Variance model: Two-component variance function +#> +#> Mean of starting values for individual parameters: +#> DMTA_0 log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1 f_DMTA_ilr_2 +#> 98.7698 -3.9216 -4.3377 -4.2477 0.1380 0.1393 +#> f_DMTA_ilr_3 log_k1 log_k2 g_qlogis +#> -1.7571 -2.2341 -3.7763 0.4502 +#> +#> Mean of starting values for error model parameters: +#> sigma_low rsd_high +#> 0.69793 0.02577 +#> +#> Fixed degradation parameter values: +#> None +#> +#> Results: +#> +#> Likelihood calculated by focei +#> AIC BIC logLik +#> 1936 2031 -945.9 +#> +#> Optimised parameters: +#> est. lower upper +#> DMTA_0 98.7698 98.7356 98.8039 +#> log_k_M23 -3.9216 -3.9235 -3.9197 +#> log_k_M27 -4.3377 -4.3398 -4.3357 +#> log_k_M31 -4.2477 -4.2497 -4.2457 +#> log_k1 -2.2341 -2.2353 -2.2329 +#> log_k2 -3.7763 -3.7781 -3.7744 +#> g_qlogis 0.4502 0.4496 0.4507 +#> f_DMTA_tffm0_1_qlogis -2.0924 -2.0936 -2.0912 +#> f_DMTA_tffm0_2_qlogis -2.1806 -2.1818 -2.1794 +#> f_DMTA_tffm0_3_qlogis -2.1427 -2.1439 -2.1415 +#> +#> Correlation: +#> DMTA_0 l__M23 l__M27 l__M31 log_k1 log_k2 g_qlgs +#> log_k_M23 0 +#> log_k_M27 0 0 +#> log_k_M31 0 0 0 +#> log_k1 0 0 0 0 +#> log_k2 0 0 0 0 0 +#> g_qlogis 0 0 0 0 0 0 +#> f_DMTA_tffm0_1_qlogis 0 0 0 0 0 0 0 +#> f_DMTA_tffm0_2_qlogis 0 0 0 0 0 0 0 +#> f_DMTA_tffm0_3_qlogis 0 0 0 0 0 0 0 +#> f_DMTA_0_1 f_DMTA_0_2 +#> log_k_M23 +#> log_k_M27 +#> log_k_M31 +#> log_k1 +#> log_k2 +#> g_qlogis +#> f_DMTA_tffm0_1_qlogis +#> f_DMTA_tffm0_2_qlogis 0 +#> f_DMTA_tffm0_3_qlogis 0 0 +#> +#> Random effects (omega): +#> eta.DMTA_0 eta.log_k_M23 eta.log_k_M27 eta.log_k_M31 +#> eta.DMTA_0 2.352 0.0000 0.0000 0.0000 +#> eta.log_k_M23 0.000 0.5493 0.0000 0.0000 +#> eta.log_k_M27 0.000 0.0000 0.8645 0.0000 +#> eta.log_k_M31 0.000 0.0000 0.0000 0.7503 +#> eta.log_k1 0.000 0.0000 0.0000 0.0000 +#> eta.log_k2 0.000 0.0000 0.0000 0.0000 +#> eta.g_qlogis 0.000 0.0000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_1_qlogis 0.000 0.0000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_2_qlogis 0.000 0.0000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_3_qlogis 0.000 0.0000 0.0000 0.0000 +#> eta.log_k1 eta.log_k2 eta.g_qlogis +#> eta.DMTA_0 0.000 0.000 0.000 +#> eta.log_k_M23 0.000 0.000 0.000 +#> eta.log_k_M27 0.000 0.000 0.000 +#> eta.log_k_M31 0.000 0.000 0.000 +#> eta.log_k1 0.903 0.000 0.000 +#> eta.log_k2 0.000 1.577 0.000 +#> eta.g_qlogis 0.000 0.000 3.085 +#> eta.f_DMTA_tffm0_1_qlogis 0.000 0.000 0.000 +#> eta.f_DMTA_tffm0_2_qlogis 0.000 0.000 0.000 +#> eta.f_DMTA_tffm0_3_qlogis 0.000 0.000 0.000 +#> eta.f_DMTA_tffm0_1_qlogis eta.f_DMTA_tffm0_2_qlogis +#> eta.DMTA_0 0.0 0.0 +#> eta.log_k_M23 0.0 0.0 +#> eta.log_k_M27 0.0 0.0 +#> eta.log_k_M31 0.0 0.0 +#> eta.log_k1 0.0 0.0 +#> eta.log_k2 0.0 0.0 +#> eta.g_qlogis 0.0 0.0 +#> eta.f_DMTA_tffm0_1_qlogis 0.3 0.0 +#> eta.f_DMTA_tffm0_2_qlogis 0.0 0.3 +#> eta.f_DMTA_tffm0_3_qlogis 0.0 0.0 +#> eta.f_DMTA_tffm0_3_qlogis +#> eta.DMTA_0 0.0 +#> eta.log_k_M23 0.0 +#> eta.log_k_M27 0.0 +#> eta.log_k_M31 0.0 +#> eta.log_k1 0.0 +#> eta.log_k2 0.0 +#> eta.g_qlogis 0.0 +#> eta.f_DMTA_tffm0_1_qlogis 0.0 +#> eta.f_DMTA_tffm0_2_qlogis 0.0 +#> eta.f_DMTA_tffm0_3_qlogis 0.3 +#> +#> Variance model: +#> sigma_low rsd_high +#> 0.69793 0.02577 +#> +#> Backtransformed parameters: +#> est. lower upper +#> DMTA_0 98.76976 98.73563 98.80390 +#> k_M23 0.01981 0.01977 0.01985 +#> k_M27 0.01307 0.01304 0.01309 +#> k_M31 0.01430 0.01427 0.01433 +#> f_DMTA_to_M23 0.10984 NA NA +#> f_DMTA_to_M27 0.09036 NA NA +#> f_DMTA_to_M31 0.08399 NA NA +#> k1 0.10709 0.10696 0.10722 +#> k2 0.02291 0.02287 0.02295 +#> g 0.61068 0.61055 0.61081 +#> +#> Resulting formation fractions: +#> ff +#> DMTA_M23 0.10984 +#> DMTA_M27 0.09036 +#> DMTA_M31 0.08399 +#> DMTA_sink 0.71581 +#> +#> Estimated disappearance times: +#> DT50 DT90 DT50back DT50_k1 DT50_k2 +#> DMTA 10.66 59.78 18 6.473 30.26 +#> M23 34.99 116.24 NA NA NA +#> M27 53.05 176.23 NA NA NA +#> M31 48.48 161.05 NA NA NA</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_dmta_nlmixr_focei</span><span class='op'>)</span> +</div><div class='img'><img src='dimethenamid_2018-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># Using saemix takes about 18 minutes</span> +<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span> + <span class='va'>f_dmta_saemix</span> <span class='op'><-</span> <span class='fu'><a href='saem.html'>saem</a></span><span class='op'>(</span><span class='va'>f_dmta_mkin_tc</span>, test_log_parms <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='op'>)</span> +</div><div class='output co'>#> Running main SAEM algorithm +#> [1] "Tue Jul 27 16:02:34 2021" +#> .... +#> Minimisation finished +#> [1] "Tue Jul 27 16:21:39 2021"</div><div class='output co'>#> user system elapsed +#> 1213.394 0.087 1213.578 </div><div class='input'> +<span class='co'># nlmixr with est = "saem" is pretty fast with default iteration numbers, most</span> +<span class='co'># of the time (about 2.5 minutes) is spent for calculating the log likelihood at the end</span> +<span class='co'># The likelihood calculated for the nlmixr fit is much lower than that found by saemix</span> +<span class='co'># Also, the trace plot and the plot of the individual predictions is not</span> +<span class='co'># convincing for the parent. It seems we are fitting an overparameterised</span> +<span class='co'># model, so the result we get strongly depends on starting parameters and control settings.</span> +<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span> + <span class='va'>f_dmta_nlmixr_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_dmta_mkin_tc</span>, est <span class='op'>=</span> <span class='st'>"saem"</span>, + control <span class='op'>=</span> <span class='fu'>nlmixr</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/saemControl.html'>saemControl</a></span><span class='op'>(</span>print <span class='op'>=</span> <span class='fl'>500</span>, logLik <span class='op'>=</span> <span class='cn'>TRUE</span>, nmc <span class='op'>=</span> <span class='fl'>9</span><span class='op'>)</span><span class='op'>)</span> +<span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> 1: 98.3427 -3.5148 -3.3187 -3.7728 -2.1163 -2.8457 0.9482 -2.8064 -2.7412 -2.8745 2.7912 0.6805 0.8213 0.8055 0.8578 1.4980 2.9309 0.2850 0.2854 0.2850 4.0990 0.3821 3.5349 0.6537 5.4143 0.0002 4.5093 0.1905 +#> 500: 97.8277 -4.3506 -4.0318 -4.1520 -3.0553 -3.5843 1.1326 -2.0873 -2.0421 -2.0751 0.2960 1.2515 0.2531 0.3807 0.7928 0.8863 6.5211 0.1433 0.1082 0.3353 0.8960 0.0470 0.7501 0.0475 0.9527 0.0281 0.7321 0.0594</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> [1] "CMT"</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> user system elapsed +#> 818.782 3.808 154.926 </div><div class='input'><span class='fu'>traceplot</span><span class='op'>(</span><span class='va'>f_dmta_nlmixr_saem</span><span class='op'>$</span><span class='va'>nm</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in traceplot(f_dmta_nlmixr_saem$nm): could not find function "traceplot"</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>f_dmta_nlmixr_saem</span><span class='op'>)</span> +</div><div class='output co'>#> nlmixr version used for fitting: 2.0.4 +#> mkin version used for pre-fitting: 1.1.0 +#> R version used for fitting: 4.1.0 +#> Date of fit: Tue Jul 27 16:25:23 2021 +#> Date of summary: Tue Jul 27 16:25:23 2021 +#> +#> Equations: +#> d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * +#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) +#> * DMTA +#> d_M23/dt = + f_DMTA_to_M23 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M23 * M23 +#> d_M27/dt = + f_DMTA_to_M27 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M27 * M27 + k_M31 * M31 +#> d_M31/dt = + f_DMTA_to_M31 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) +#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * +#> exp(-k2 * time))) * DMTA - k_M31 * M31 +#> +#> Data: +#> 568 observations of 4 variable(s) grouped in 6 datasets +#> +#> Degradation model predictions using RxODE +#> +#> Fitted in 154.632 s +#> +#> Variance model: Two-component variance function +#> +#> Mean of starting values for individual parameters: +#> DMTA_0 log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1 f_DMTA_ilr_2 +#> 98.7698 -3.9216 -4.3377 -4.2477 0.1380 0.1393 +#> f_DMTA_ilr_3 log_k1 log_k2 g_qlogis +#> -1.7571 -2.2341 -3.7763 0.4502 +#> +#> Mean of starting values for error model parameters: +#> sigma_low_DMTA rsd_high_DMTA sigma_low_M23 rsd_high_M23 sigma_low_M27 +#> 0.69793 0.02577 0.69793 0.02577 0.69793 +#> rsd_high_M27 sigma_low_M31 rsd_high_M31 +#> 0.02577 0.69793 0.02577 +#> +#> Fixed degradation parameter values: +#> None +#> +#> Results: +#> +#> Likelihood calculated by focei +#> AIC BIC logLik +#> 2036 2157 -989.8 +#> +#> Optimised parameters: +#> est. lower upper +#> DMTA_0 97.828 96.121 99.535 +#> log_k_M23 -4.351 -5.300 -3.401 +#> log_k_M27 -4.032 -4.470 -3.594 +#> log_k_M31 -4.152 -4.689 -3.615 +#> log_k1 -3.055 -3.785 -2.325 +#> log_k2 -3.584 -4.517 -2.651 +#> g_qlogis 1.133 -2.165 4.430 +#> f_DMTA_tffm0_1_qlogis -2.087 -2.407 -1.768 +#> f_DMTA_tffm0_2_qlogis -2.042 -2.336 -1.748 +#> f_DMTA_tffm0_3_qlogis -2.075 -2.557 -1.593 +#> +#> Correlation: +#> DMTA_0 l__M23 l__M27 l__M31 log_k1 log_k2 g_qlgs +#> log_k_M23 -0.031 +#> log_k_M27 -0.050 0.004 +#> log_k_M31 -0.032 0.003 0.078 +#> log_k1 0.014 -0.002 -0.002 -0.001 +#> log_k2 0.059 0.006 -0.001 0.002 -0.037 +#> g_qlogis -0.077 0.005 0.009 0.004 0.035 -0.201 +#> f_DMTA_tffm0_1_qlogis -0.104 0.066 0.009 0.006 0.000 -0.011 0.014 +#> f_DMTA_tffm0_2_qlogis -0.120 0.013 0.081 -0.033 -0.002 -0.013 0.017 +#> f_DMTA_tffm0_3_qlogis -0.086 0.010 0.060 0.078 -0.002 -0.005 0.010 +#> f_DMTA_0_1 f_DMTA_0_2 +#> log_k_M23 +#> log_k_M27 +#> log_k_M31 +#> log_k1 +#> log_k2 +#> g_qlogis +#> f_DMTA_tffm0_1_qlogis +#> f_DMTA_tffm0_2_qlogis 0.026 +#> f_DMTA_tffm0_3_qlogis 0.019 0.002 +#> +#> Random effects (omega): +#> eta.DMTA_0 eta.log_k_M23 eta.log_k_M27 eta.log_k_M31 +#> eta.DMTA_0 0.296 0.000 0.0000 0.0000 +#> eta.log_k_M23 0.000 1.252 0.0000 0.0000 +#> eta.log_k_M27 0.000 0.000 0.2531 0.0000 +#> eta.log_k_M31 0.000 0.000 0.0000 0.3807 +#> eta.log_k1 0.000 0.000 0.0000 0.0000 +#> eta.log_k2 0.000 0.000 0.0000 0.0000 +#> eta.g_qlogis 0.000 0.000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_1_qlogis 0.000 0.000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_2_qlogis 0.000 0.000 0.0000 0.0000 +#> eta.f_DMTA_tffm0_3_qlogis 0.000 0.000 0.0000 0.0000 +#> eta.log_k1 eta.log_k2 eta.g_qlogis +#> eta.DMTA_0 0.0000 0.0000 0.000 +#> eta.log_k_M23 0.0000 0.0000 0.000 +#> eta.log_k_M27 0.0000 0.0000 0.000 +#> eta.log_k_M31 0.0000 0.0000 0.000 +#> eta.log_k1 0.7928 0.0000 0.000 +#> eta.log_k2 0.0000 0.8863 0.000 +#> eta.g_qlogis 0.0000 0.0000 6.521 +#> eta.f_DMTA_tffm0_1_qlogis 0.0000 0.0000 0.000 +#> eta.f_DMTA_tffm0_2_qlogis 0.0000 0.0000 0.000 +#> eta.f_DMTA_tffm0_3_qlogis 0.0000 0.0000 0.000 +#> eta.f_DMTA_tffm0_1_qlogis eta.f_DMTA_tffm0_2_qlogis +#> eta.DMTA_0 0.0000 0.0000 +#> eta.log_k_M23 0.0000 0.0000 +#> eta.log_k_M27 0.0000 0.0000 +#> eta.log_k_M31 0.0000 0.0000 +#> eta.log_k1 0.0000 0.0000 +#> eta.log_k2 0.0000 0.0000 +#> eta.g_qlogis 0.0000 0.0000 +#> eta.f_DMTA_tffm0_1_qlogis 0.1433 0.0000 +#> eta.f_DMTA_tffm0_2_qlogis 0.0000 0.1082 +#> eta.f_DMTA_tffm0_3_qlogis 0.0000 0.0000 +#> eta.f_DMTA_tffm0_3_qlogis +#> eta.DMTA_0 0.0000 +#> eta.log_k_M23 0.0000 +#> eta.log_k_M27 0.0000 +#> eta.log_k_M31 0.0000 +#> eta.log_k1 0.0000 +#> eta.log_k2 0.0000 +#> eta.g_qlogis 0.0000 +#> eta.f_DMTA_tffm0_1_qlogis 0.0000 +#> eta.f_DMTA_tffm0_2_qlogis 0.0000 +#> eta.f_DMTA_tffm0_3_qlogis 0.3353 +#> +#> Variance model: +#> sigma_low_DMTA rsd_high_DMTA sigma_low_M23 rsd_high_M23 sigma_low_M27 +#> 0.89603 0.04704 0.75015 0.04753 0.95265 +#> rsd_high_M27 sigma_low_M31 rsd_high_M31 +#> 0.02810 0.73212 0.05942 +#> +#> Backtransformed parameters: +#> est. lower upper +#> DMTA_0 97.82774 96.120503 99.53498 +#> k_M23 0.01290 0.004991 0.03334 +#> k_M27 0.01774 0.011451 0.02749 +#> k_M31 0.01573 0.009195 0.02692 +#> f_DMTA_to_M23 0.11033 NA NA +#> f_DMTA_to_M27 0.10218 NA NA +#> f_DMTA_to_M31 0.08784 NA NA +#> k1 0.04711 0.022707 0.09773 +#> k2 0.02775 0.010918 0.07056 +#> g 0.75632 0.102960 0.98823 +#> +#> Resulting formation fractions: +#> ff +#> DMTA_M23 0.11033 +#> DMTA_M27 0.10218 +#> DMTA_M31 0.08784 +#> DMTA_sink 0.69965 +#> +#> Estimated disappearance times: +#> DT50 DT90 DT50back DT50_k1 DT50_k2 +#> DMTA 16.59 57.44 17.29 14.71 24.97 +#> M23 53.74 178.51 NA NA NA +#> M27 39.07 129.78 NA NA NA +#> M31 44.06 146.36 NA NA NA</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_dmta_nlmixr_saem</span><span class='op'>)</span> +</div><div class='img'><img src='dimethenamid_2018-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span> +</div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> <nav id="toc" data-toggle="toc" class="sticky-top"> diff --git a/docs/dev/reference/endpoints.html b/docs/dev/reference/endpoints.html index db702c2e..aa5bd773 100644 --- a/docs/dev/reference/endpoints.html +++ b/docs/dev/reference/endpoints.html @@ -78,7 +78,7 @@ advantage that the SFORB model can also be used for metabolites." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -127,7 +127,7 @@ advantage that the SFORB model can also be used for metabolites." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -165,8 +165,8 @@ advantage that the SFORB model can also be used for metabolites.</p> <colgroup><col class="name" /><col class="desc" /></colgroup> <tr> <th>fit</th> - <td><p>An object of class <a href='mkinfit.html'>mkinfit</a>, <a href='nlme.mmkin.html'>nlme.mmkin</a> or -<a href='saem.html'>saem.mmkin</a>. Or another object that has list components + <td><p>An object of class <a href='mkinfit.html'>mkinfit</a>, <a href='nlme.mmkin.html'>nlme.mmkin</a>, <a href='saem.html'>saem.mmkin</a> or +<a href='nlmixr.mmkin.html'>nlmixr.mmkin</a>. Or another object that has list components mkinmod containing an <a href='mkinmod.html'>mkinmod</a> degradation model, and two numeric vectors, bparms.optim and bparms.fixed, that contain parameter values for that model.</p></td> diff --git a/docs/dev/reference/experimental_data_for_UBA-1.png b/docs/dev/reference/experimental_data_for_UBA-1.png Binary files differindex 24cb54c5..33946ded 100644 --- a/docs/dev/reference/experimental_data_for_UBA-1.png +++ b/docs/dev/reference/experimental_data_for_UBA-1.png diff --git a/docs/dev/reference/experimental_data_for_UBA.html b/docs/dev/reference/experimental_data_for_UBA.html index 78e57fb0..9904370f 100644 --- a/docs/dev/reference/experimental_data_for_UBA.html +++ b/docs/dev/reference/experimental_data_for_UBA.html @@ -100,7 +100,7 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -149,7 +149,7 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/f_time_norm_focus.html b/docs/dev/reference/f_time_norm_focus.html index 3421043d..852e00a0 100644 --- a/docs/dev/reference/f_time_norm_focus.html +++ b/docs/dev/reference/f_time_norm_focus.html @@ -73,7 +73,7 @@ in Appendix 8 to the FOCUS kinetics guidance (FOCUS 2014, p. 369)." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> diff --git a/docs/dev/reference/focus_soil_moisture.html b/docs/dev/reference/focus_soil_moisture.html index c46fd69a..0e6fea28 100644 --- a/docs/dev/reference/focus_soil_moisture.html +++ b/docs/dev/reference/focus_soil_moisture.html @@ -73,7 +73,7 @@ corresponds to pF2, MWHC to pF 1 and 1/3 bar to pF 2.5." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ corresponds to pF2, MWHC to pF 1 and 1/3 bar to pF 2.5." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/get_deg_func.html b/docs/dev/reference/get_deg_func.html index a266bf5f..fb661085 100644 --- a/docs/dev/reference/get_deg_func.html +++ b/docs/dev/reference/get_deg_func.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/ilr.html b/docs/dev/reference/ilr.html index 98e51211..452647d6 100644 --- a/docs/dev/reference/ilr.html +++ b/docs/dev/reference/ilr.html @@ -73,7 +73,7 @@ transformations." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ transformations." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html index e038ef5c..d5ec387a 100644 --- a/docs/dev/reference/index.html +++ b/docs/dev/reference/index.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -175,7 +175,7 @@ </tr><tr> <td> - <p><code><a href="mmkin.html">mmkin()</a></code> </p> + <p><code><a href="mmkin.html">mmkin()</a></code> <code><a href="mmkin.html">print(<i><mmkin></i>)</a></code> </p> </td> <td><p>Fit one or more kinetic models with one or more state variables to one or more datasets</p></td> @@ -297,12 +297,6 @@ of an mmkin object</p></td> <p><code><a href="AIC.mmkin.html">AIC(<i><mmkin></i>)</a></code> <code><a href="AIC.mmkin.html">BIC(<i><mmkin></i>)</a></code> </p> </td> <td><p>Calculate the AIC for a column of an mmkin object</p></td> - </tr><tr> - - <td> - <p><code><a href="print.mmkin.html">print(<i><mmkin></i>)</a></code> </p> - </td> - <td><p>Print method for mmkin objects</p></td> </tr> </tbody><tbody> <tr> @@ -331,6 +325,12 @@ of an mmkin object</p></td> </tr><tr> <td> + <p><code><a href="nlmixr.mmkin.html">nlmixr(<i><mmkin></i>)</a></code> <code><a href="nlmixr.mmkin.html">print(<i><nlmixr.mmkin></i>)</a></code> <code><a href="nlmixr.mmkin.html">nlmixr_model()</a></code> <code><a href="nlmixr.mmkin.html">nlmixr_data()</a></code> </p> + </td> + <td><p>Fit nonlinear mixed models using nlmixr</p></td> + </tr><tr> + + <td> <p><code><a href="plot.mixed.mmkin.html">plot(<i><mixed.mmkin></i>)</a></code> </p> </td> <td><p>Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object</p></td> @@ -343,13 +343,19 @@ of an mmkin object</p></td> </tr><tr> <td> + <p><code><a href="summary.nlmixr.mmkin.html">summary(<i><nlmixr.mmkin></i>)</a></code> <code><a href="summary.nlmixr.mmkin.html">print(<i><summary.nlmixr.mmkin></i>)</a></code> </p> + </td> + <td><p>Summary method for class "nlmixr.mmkin"</p></td> + </tr><tr> + + <td> <p><code><a href="summary.saem.mmkin.html">summary(<i><saem.mmkin></i>)</a></code> <code><a href="summary.saem.mmkin.html">print(<i><summary.saem.mmkin></i>)</a></code> </p> </td> <td><p>Summary method for class "saem.mmkin"</p></td> </tr><tr> <td> - <p><code><a href="nlme.html">nlme_function()</a></code> <code><a href="nlme.html">mean_degparms()</a></code> <code><a href="nlme.html">nlme_data()</a></code> </p> + <p><code><a href="nlme.html">nlme_function()</a></code> <code><a href="nlme.html">nlme_data()</a></code> </p> </td> <td><p>Helper functions to create nlme models from mmkin row objects</p></td> </tr><tr> @@ -576,6 +582,12 @@ kinetic models fitted with mkinfit</p></td> </tr><tr> <td> + <p><code><a href="tffm0.html">tffm0()</a></code> <code><a href="tffm0.html">invtffm0()</a></code> </p> + </td> + <td><p>Transform formation fractions as in the first published mkin version</p></td> + </tr><tr> + + <td> <p><code><a href="logLik.mkinfit.html">logLik(<i><mkinfit></i>)</a></code> </p> </td> <td><p>Calculated the log-likelihood of a fitted mkinfit object</p></td> @@ -612,6 +624,12 @@ kinetic models fitted with mkinfit</p></td> </tr><tr> <td> + <p><code><a href="mean_degparms.html">mean_degparms()</a></code> </p> + </td> + <td><p>Calculate mean degradation parameters for an mmkin row object</p></td> + </tr><tr> + + <td> <p><code><a href="create_deg_func.html">create_deg_func()</a></code> </p> </td> <td><p>Create degradation functions for known analytical solutions</p></td> diff --git a/docs/dev/reference/loftest-1.png b/docs/dev/reference/loftest-1.png Binary files differindex 6b918fec..d6006ecc 100644 --- a/docs/dev/reference/loftest-1.png +++ b/docs/dev/reference/loftest-1.png diff --git a/docs/dev/reference/loftest-2.png b/docs/dev/reference/loftest-2.png Binary files differindex 60874bd3..4d0dc551 100644 --- a/docs/dev/reference/loftest-2.png +++ b/docs/dev/reference/loftest-2.png diff --git a/docs/dev/reference/loftest-3.png b/docs/dev/reference/loftest-3.png Binary files differindex 4837e7f2..6afd084b 100644 --- a/docs/dev/reference/loftest-3.png +++ b/docs/dev/reference/loftest-3.png diff --git a/docs/dev/reference/loftest-4.png b/docs/dev/reference/loftest-4.png Binary files differindex 9c18ac30..f94eede1 100644 --- a/docs/dev/reference/loftest-4.png +++ b/docs/dev/reference/loftest-4.png diff --git a/docs/dev/reference/loftest-5.png b/docs/dev/reference/loftest-5.png Binary files differindex 11f2bda7..43460a65 100644 --- a/docs/dev/reference/loftest-5.png +++ b/docs/dev/reference/loftest-5.png diff --git a/docs/dev/reference/loftest.html b/docs/dev/reference/loftest.html index abbbd3b9..9dbd547d 100644 --- a/docs/dev/reference/loftest.html +++ b/docs/dev/reference/loftest.html @@ -75,7 +75,7 @@ lrtest.default from the lmtest package." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -124,7 +124,7 @@ lrtest.default from the lmtest package." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/logLik.mkinfit.html b/docs/dev/reference/logLik.mkinfit.html index 66539dbd..3e9452c6 100644 --- a/docs/dev/reference/logLik.mkinfit.html +++ b/docs/dev/reference/logLik.mkinfit.html @@ -76,7 +76,7 @@ the error model." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ the error model." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -196,11 +196,11 @@ and the fitted error model parameters.</p> parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span> <span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='va'>d_t</span> <span class='op'><-</span> <span class='va'>FOCUS_2006_D</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='va'>d_t</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='va'>f_nw</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='co'># no weighting (weights are unity)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='va'>f_tc</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nw</span>, <span class='va'>f_obs</span>, <span class='va'>f_tc</span><span class='op'>)</span> + <span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> + <span class='va'>f_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> + <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nw</span>, <span class='va'>f_obs</span>, <span class='va'>f_tc</span><span class='op'>)</span> </div><div class='output co'>#> df AIC #> f_nw 5 204.4486 #> f_obs 6 205.8727 diff --git a/docs/dev/reference/logistic.solution-2.png b/docs/dev/reference/logistic.solution-2.png Binary files differindex 764996df..73e6436d 100644 --- a/docs/dev/reference/logistic.solution-2.png +++ b/docs/dev/reference/logistic.solution-2.png diff --git a/docs/dev/reference/logistic.solution.html b/docs/dev/reference/logistic.solution.html index 950e8a8e..ab68c99e 100644 --- a/docs/dev/reference/logistic.solution.html +++ b/docs/dev/reference/logistic.solution.html @@ -73,7 +73,7 @@ an increasing rate constant, supposedly caused by microbial growth" /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ an increasing rate constant, supposedly caused by microbial growth" /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -240,10 +240,10 @@ Version 1.1, 18 December 2014 <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>m</span><span class='op'>)</span> </div><div class='img'><img src='logistic.solution-2.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>m</span><span class='op'>)</span><span class='op'>$</span><span class='va'>bpar</span> </div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower -#> parent_0 1.057896e+02 1.9023449703 55.610119 3.768361e-16 1.016451e+02 -#> kmax 6.398190e-02 0.0143201031 4.467978 3.841829e-04 3.929235e-02 +#> parent_0 1.057896e+02 1.9023449590 55.610120 3.768360e-16 1.016451e+02 +#> kmax 6.398190e-02 0.0143201029 4.467978 3.841828e-04 3.929235e-02 #> k0 1.612775e-04 0.0005866813 0.274898 3.940351e-01 5.846688e-08 -#> r 2.263946e-01 0.1718110715 1.317695 1.061044e-01 4.335843e-02 +#> r 2.263946e-01 0.1718110662 1.317695 1.061043e-01 4.335843e-02 #> sigma 5.332935e+00 0.9145907310 5.830952 4.036926e-05 3.340213e+00 #> Upper #> parent_0 109.9341588 diff --git a/docs/dev/reference/lrtest.mkinfit.html b/docs/dev/reference/lrtest.mkinfit.html index b76ebc87..f2d8472e 100644 --- a/docs/dev/reference/lrtest.mkinfit.html +++ b/docs/dev/reference/lrtest.mkinfit.html @@ -76,7 +76,7 @@ and can be expressed by fixing the parameters of the other." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ and can be expressed by fixing the parameters of the other." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/max_twa_parent.html b/docs/dev/reference/max_twa_parent.html index 25f745e9..a358568a 100644 --- a/docs/dev/reference/max_twa_parent.html +++ b/docs/dev/reference/max_twa_parent.html @@ -78,7 +78,7 @@ soil section of the FOCUS guidance." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -127,7 +127,7 @@ soil section of the FOCUS guidance." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mccall81_245T-1.png b/docs/dev/reference/mccall81_245T-1.png Binary files differindex 5daa5f18..91fe060e 100644 --- a/docs/dev/reference/mccall81_245T-1.png +++ b/docs/dev/reference/mccall81_245T-1.png diff --git a/docs/dev/reference/mccall81_245T.html b/docs/dev/reference/mccall81_245T.html index 7179533d..f79137be 100644 --- a/docs/dev/reference/mccall81_245T.html +++ b/docs/dev/reference/mccall81_245T.html @@ -74,7 +74,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -181,30 +181,30 @@ <span class='va'>fit.1</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>mccall81_245T</span>, <span class='va'>soil</span> <span class='op'>==</span> <span class='st'>"Commerce"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.1</span><span class='op'>)</span><span class='op'>$</span><span class='va'>bpar</span> </div><div class='output co'>#> Estimate se_notrans t value Pr(>t) -#> T245_0 1.038550e+02 2.1847074888 47.537272 4.472189e-18 +#> T245_0 1.038550e+02 2.1847074945 47.537272 4.472189e-18 #> k_T245 4.337042e-02 0.0018983965 22.845818 2.276911e-13 -#> k_phenol 4.050581e-01 0.2986993400 1.356073 9.756988e-02 -#> k_anisole 6.678742e-03 0.0008021439 8.326114 2.623176e-07 -#> f_T245_to_phenol 6.227599e-01 0.3985340295 1.562627 6.949412e-02 -#> f_phenol_to_anisole 1.000000e+00 0.6718439378 1.488441 7.867787e-02 -#> sigma 2.514628e+00 0.4907558750 5.123989 6.233156e-05 +#> k_phenol 4.050581e-01 0.2986993563 1.356073 9.756989e-02 +#> k_anisole 6.678742e-03 0.0008021439 8.326114 2.623177e-07 +#> f_T245_to_phenol 6.227599e-01 0.3985340558 1.562627 6.949413e-02 +#> f_phenol_to_anisole 1.000000e+00 0.6718439825 1.488441 7.867789e-02 +#> sigma 2.514628e+00 0.4907558883 5.123989 6.233157e-05 #> Lower Upper -#> T245_0 99.246061370 1.084640e+02 +#> T245_0 99.246061385 1.084640e+02 #> k_T245 0.039631621 4.746194e-02 -#> k_phenol 0.218013878 7.525762e-01 +#> k_phenol 0.218013879 7.525762e-01 #> k_anisole 0.005370739 8.305299e-03 -#> f_T245_to_phenol 0.547559083 6.924813e-01 +#> f_T245_to_phenol 0.547559081 6.924813e-01 #> f_phenol_to_anisole 0.000000000 1.000000e+00 #> sigma 1.706607296 3.322649e+00</div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fit.1</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> T245_phenol T245_sink phenol_anisole phenol_sink -#> 6.227599e-01 3.772401e-01 1.000000e+00 6.894640e-11 +#> 6.227599e-01 3.772401e-01 1.000000e+00 3.773626e-10 #> #> $distimes #> DT50 DT90 #> T245 15.982025 53.09114 #> phenol 1.711229 5.68458 -#> anisole 103.784092 344.76329 +#> anisole 103.784093 344.76329 #> </div><div class='input'> <span class='co'># formation fraction from phenol to anisol is practically 1. As we cannot</span> <span class='co'># fix formation fractions when using the ilr transformation, we can turn of</span> <span class='co'># the sink in the model generation</span> @@ -215,28 +215,28 @@ quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span><span class='op'>$</span><span class='va'>bpar</span> </div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower -#> T245_0 1.038550e+02 2.1623653027 48.028439 4.993108e-19 99.271020526 -#> k_T245 4.337042e-02 0.0018343666 23.643268 3.573555e-14 0.039650977 -#> k_phenol 4.050582e-01 0.1177237248 3.440752 1.679252e-03 0.218746585 -#> k_anisole 6.678741e-03 0.0006829745 9.778903 1.872894e-08 0.005377083 -#> f_T245_to_phenol 6.227599e-01 0.0342197865 18.198825 2.039410e-12 0.547975628 +#> T245_0 1.038550e+02 2.1623653066 48.028439 4.993108e-19 99.271020284 +#> k_T245 4.337042e-02 0.0018343666 23.643268 3.573556e-14 0.039650976 +#> k_phenol 4.050582e-01 0.1177237473 3.440752 1.679254e-03 0.218746587 +#> k_anisole 6.678742e-03 0.0006829745 9.778903 1.872894e-08 0.005377083 +#> f_T245_to_phenol 6.227599e-01 0.0342197875 18.198824 2.039411e-12 0.547975637 #> sigma 2.514628e+00 0.3790944250 6.633250 2.875782e-06 1.710983655 #> Upper -#> T245_0 108.43904097 +#> T245_0 108.43904074 #> k_T245 0.04743877 -#> k_phenol 0.75005577 +#> k_phenol 0.75005585 #> k_anisole 0.00829550 -#> f_T245_to_phenol 0.69212306 +#> f_T245_to_phenol 0.69212308 #> sigma 3.31827222</div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fit.1</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> T245_phenol T245_sink phenol_anisole phenol_sink -#> 6.227599e-01 3.772401e-01 1.000000e+00 6.894640e-11 +#> 6.227599e-01 3.772401e-01 1.000000e+00 3.773626e-10 #> #> $distimes #> DT50 DT90 #> T245 15.982025 53.09114 #> phenol 1.711229 5.68458 -#> anisole 103.784092 344.76329 +#> anisole 103.784093 344.76329 #> </div><div class='input'> <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span> </div><div class='img'><img src='mccall81_245T-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='co'># }</span> </div></pre> diff --git a/docs/dev/reference/mean_degparms.html b/docs/dev/reference/mean_degparms.html new file mode 100644 index 00000000..5981c625 --- /dev/null +++ b/docs/dev/reference/mean_degparms.html @@ -0,0 +1,210 @@ +<!-- Generated by pkgdown: do not edit by hand --> +<!DOCTYPE html> +<html lang="en"> + <head> + <meta charset="utf-8"> +<meta 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class='op'>(</span><span class='va'>object</span>, random <span class='op'>=</span> <span class='cn'>FALSE</span>, test_log_parms <span class='op'>=</span> <span class='cn'>FALSE</span>, conf.level <span class='op'>=</span> <span class='fl'>0.6</span><span class='op'>)</span></pre> + + <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>object</th> + <td><p>An mmkin row object containing several fits of the same model to different datasets</p></td> + </tr> + <tr> + <th>random</th> + <td><p>Should a list with fixed and random effects be returned?</p></td> + </tr> + <tr> + <th>test_log_parms</th> + <td><p>If TRUE, log parameters are only considered in +the mean calculations if their untransformed counterparts (most likely +rate constants) pass the t-test for significant difference from zero.</p></td> + </tr> + <tr> + <th>conf.level</th> + <td><p>Possibility to adjust the required confidence level +for parameter that are tested if requested by 'test_log_parms'.</p></td> + </tr> + </table> + + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>If random is FALSE (default), a named vector containing mean values +of the fitted degradation model parameters. If random is TRUE, a list with +fixed and random effects, in the format required by the start argument of +nlme for the case of a single grouping variable ds.</p> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"> + <h2 data-toc-skip>Contents</h2> + </nav> + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + diff --git a/docs/dev/reference/mixed-1.png b/docs/dev/reference/mixed-1.png Binary files differindex 3400c4aa..422ab6a0 100644 --- a/docs/dev/reference/mixed-1.png +++ b/docs/dev/reference/mixed-1.png diff --git a/docs/dev/reference/mixed.html b/docs/dev/reference/mixed.html index 18a67af8..338480ee 100644 --- a/docs/dev/reference/mixed.html +++ b/docs/dev/reference/mixed.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.5</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -180,6 +180,10 @@ </tr> </table> + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>An object of class 'mixed.mmkin' which has the observed data in a +single dataframe which is convenient for plotting</p> <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'><span class='va'>sampling_times</span> <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span><span class='op'>)</span> @@ -235,18 +239,16 @@ #> Status of individual fits: #> #> dataset -#> model 1 2 3 4 5 6 7 8 -#> DFOP-SFO OK OK OK OK OK C OK OK +#> model 1 2 3 4 5 6 7 8 +#> DFOP-SFO OK OK OK OK OK OK OK OK #> #> OK: No warnings -#> C: Optimisation did not converge: -#> iteration limit reached without convergence (10) #> #> Mean fitted parameters: #> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 -#> 100.606304 -8.759216 -0.002001 -3.350539 -3.989549 +#> 100.674757 -8.761916 -0.004347 -3.348812 -3.986853 #> g_qlogis -#> -0.090353 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_mixed</span><span class='op'>)</span> +#> -0.087392 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_mixed</span><span class='op'>)</span> </div><div class='img'><img src='mixed-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span> </div></pre> </div> diff --git a/docs/dev/reference/mkin_long_to_wide.html b/docs/dev/reference/mkin_long_to_wide.html index 28a37800..6246fbe2 100644 --- a/docs/dev/reference/mkin_long_to_wide.html +++ b/docs/dev/reference/mkin_long_to_wide.html @@ -74,7 +74,7 @@ variable and several dependent variables as columns." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ variable and several dependent variables as columns." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkin_wide_to_long.html b/docs/dev/reference/mkin_wide_to_long.html index f085d162..f2bf00c1 100644 --- a/docs/dev/reference/mkin_wide_to_long.html +++ b/docs/dev/reference/mkin_wide_to_long.html @@ -74,7 +74,7 @@ mkinfit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ mkinfit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkinds.html b/docs/dev/reference/mkinds.html index 907f8ad3..0d1de46d 100644 --- a/docs/dev/reference/mkinds.html +++ b/docs/dev/reference/mkinds.html @@ -75,7 +75,7 @@ provided by this package come as mkinds objects nevertheless." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -124,7 +124,7 @@ provided by this package come as mkinds objects nevertheless." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkindsg.html b/docs/dev/reference/mkindsg.html index 3e4dfb39..67c6e5df 100644 --- a/docs/dev/reference/mkindsg.html +++ b/docs/dev/reference/mkindsg.html @@ -75,7 +75,7 @@ dataset if no data are supplied." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -124,7 +124,7 @@ dataset if no data are supplied." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -239,12 +239,12 @@ or covariates like soil pH).</p></dd> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span><span class='op'>)</span> </div><div class='output co'>#> <mkindsg> holding 5 mkinds objects #> Title $title: Experimental X -#> Occurrene of observed compounds $observed_n: +#> Occurrence of observed compounds $observed_n: #> parent A1 #> 5 5 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> <mkindsg> holding 5 mkinds objects #> Title $title: Experimental X -#> Occurrene of observed compounds $observed_n: +#> Occurrence of observed compounds $observed_n: #> parent A1 #> 5 5 #> @@ -290,7 +290,7 @@ or covariates like soil pH).</p></dd> #> Observation unit: \%AR </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> <mkindsg> holding 5 mkinds objects #> Title $title: Experimental X -#> Occurrene of observed compounds $observed_n: +#> Occurrence of observed compounds $observed_n: #> parent A1 #> 5 5 #> diff --git a/docs/dev/reference/mkinerrmin.html b/docs/dev/reference/mkinerrmin.html index 1cff040d..94c575cb 100644 --- a/docs/dev/reference/mkinerrmin.html +++ b/docs/dev/reference/mkinerrmin.html @@ -73,7 +73,7 @@ the chi-squared test as defined in the FOCUS kinetics report from 2006." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ the chi-squared test as defined in the FOCUS kinetics report from 2006." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkinerrplot.html b/docs/dev/reference/mkinerrplot.html index 2324b968..7f1fd048 100644 --- a/docs/dev/reference/mkinerrplot.html +++ b/docs/dev/reference/mkinerrplot.html @@ -76,7 +76,7 @@ using the argument show_errplot = TRUE." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ using the argument show_errplot = TRUE." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkinfit-1.png b/docs/dev/reference/mkinfit-1.png Binary files differindex eed9064f..de2a90a9 100644 --- a/docs/dev/reference/mkinfit-1.png +++ b/docs/dev/reference/mkinfit-1.png diff --git a/docs/dev/reference/mkinfit.html b/docs/dev/reference/mkinfit.html index 6ae7b343..5910038f 100644 --- a/docs/dev/reference/mkinfit.html +++ b/docs/dev/reference/mkinfit.html @@ -80,7 +80,7 @@ likelihood function." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -431,17 +431,17 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 <span class='co'># Use shorthand notation for parent only degradation</span> <span class='va'>fit</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>FOCUS_2006_C</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='output co'>#> mkin version used for fitting: 0.9.50.4 +</div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Jan 11 12:41:45 2021 -#> Date of summary: Mon Jan 11 12:41:45 2021 +#> Date of fit: Mon Feb 15 17:09:39 2021 +#> Date of summary: Mon Feb 15 17:09:39 2021 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 222 model solutions performed in 0.046 s +#> Fitted using 222 model solutions performed in 0.045 s #> #> Error model: Constant variance #> @@ -476,10 +476,10 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 #> #> Parameter correlation: #> parent_0 log_alpha log_beta sigma -#> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.758e-08 -#> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.007e-07 -#> log_beta -3.142e-01 9.564e-01 1.000e+00 8.568e-08 -#> sigma 4.758e-08 1.007e-07 8.568e-08 1.000e+00 +#> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.772e-08 +#> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.005e-07 +#> log_beta -3.142e-01 9.564e-01 1.000e+00 8.541e-08 +#> sigma 4.772e-08 1.005e-07 8.541e-08 1.000e+00 #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. @@ -548,7 +548,7 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='fu'><a href='parms.html'>parms</a></span><span class='op'>(</span><span class='va'>fit.tc</span><span class='op'>)</span> </div><div class='output co'>#> parent_0 k_parent k_m1 f_parent_to_m1 sigma_low -#> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049884e-03 +#> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049883e-03 #> rsd_high #> 7.928118e-02 </div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fit.tc</span><span class='op'>)</span> </div><div class='output co'>#> $ff @@ -574,10 +574,10 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 analytical <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, solution_type <span class='op'>=</span> <span class='st'>"analytical"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>}</span> -</div><div class='output co'>#> <span class='message'>Loading required package: rbenchmark</span></div><div class='output co'>#> test relative elapsed -#> 3 analytical 1.000 0.526 -#> 1 deSolve_compiled 1.903 1.001 -#> 2 eigen 2.308 1.214</div><div class='input'><span class='co'># }</span> +</div><div class='output co'>#> test relative elapsed +#> 3 analytical 1.000 0.563 +#> 1 deSolve_compiled 1.702 0.958 +#> 2 eigen 2.597 1.462</div><div class='input'><span class='co'># }</span> <span class='co'># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span> <span class='co'># \dontrun{</span> @@ -587,22 +587,21 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fit.FOMC_SFO</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='co'># Again, we get a warning and try a more sophisticated error model</span> <span class='va'>fit.FOMC_SFO.tc</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> -#> <span class='warning'>iteration limit reached without convergence (10)</span></div><div class='input'><span class='co'># This model has a higher likelihood, but not significantly so</span> +<span class='co'># This model has a higher likelihood, but not significantly so</span> <span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>fit.tc</span>, <span class='va'>fit.FOMC_SFO.tc</span><span class='op'>)</span> </div><div class='output co'>#> Likelihood ratio test #> #> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0 #> Model 2: SFO_SFO with error model tc and fixed parameter(s) m1_0 #> #Df LogLik Df Chisq Pr(>Chisq) -#> 1 7 -64.870 -#> 2 6 -64.983 -1 0.2259 0.6346</div><div class='input'><span class='co'># Also, the missing standard error for log_beta and the t-tests for alpha</span> +#> 1 7 -64.829 +#> 2 6 -64.983 -1 0.3075 0.5792</div><div class='input'><span class='co'># Also, the missing standard error for log_beta and the t-tests for alpha</span> <span class='co'># and beta indicate overparameterisation</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.FOMC_SFO.tc</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: diag(.) had 0 or NA entries; non-finite result is doubtful</span></div><div class='output co'>#> mkin version used for fitting: 0.9.50.4 +</div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: diag(.) had 0 or NA entries; non-finite result is doubtful</span></div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Jan 11 12:41:56 2021 -#> Date of summary: Mon Jan 11 12:41:56 2021 +#> Date of fit: Mon Feb 15 17:09:50 2021 +#> Date of summary: Mon Feb 15 17:09:50 2021 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent @@ -611,12 +610,12 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 #> #> Model predictions using solution type deSolve #> -#> Fitted using 4273 model solutions performed in 3.456 s +#> Fitted using 3729 model solutions performed in 2.815 s #> #> Error model: Two-component variance function #> #> Error model algorithm: d_3 -#> Three-step fitting yielded a higher likelihood than direct fitting +#> Direct fitting and three-step fitting yield approximately the same likelihood #> #> Starting values for parameters to be optimised: #> value type @@ -642,72 +641,67 @@ doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6 #> value type #> m1_0 0 state #> -#> -#> Warning(s): -#> Optimisation did not converge: -#> iteration limit reached without convergence (10) -#> #> Results: #> -#> AIC BIC logLik -#> 143.7396 155.2027 -64.86982 +#> AIC BIC logLik +#> 143.658 155.1211 -64.82902 #> #> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 1.016e+02 1.90600 97.7400 105.5000 -#> log_k_m1 -5.285e+00 0.09286 -5.4740 -5.0950 -#> f_parent_qlogis 6.482e-04 0.06164 -0.1251 0.1264 -#> log_alpha 5.467e+00 NaN NaN NaN -#> log_beta 7.750e+00 NaN NaN NaN -#> sigma_low 0.000e+00 NaN NaN NaN -#> rsd_high 7.989e-02 NaN NaN NaN +#> Estimate Std. Error Lower Upper +#> parent_0 101.600000 2.6400000 96.240000 107.000000 +#> log_k_m1 -5.284000 0.0929100 -5.474000 -5.095000 +#> f_parent_qlogis 0.001426 0.0767000 -0.155000 0.157800 +#> log_alpha 5.522000 0.0077320 5.506000 5.538000 +#> log_beta 7.806000 NaN NaN NaN +#> sigma_low 0.002488 0.0002431 0.001992 0.002984 +#> rsd_high 0.079210 0.0093280 0.060180 0.098230 #> #> Parameter correlation: -#> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta -#> parent_0 1.0000000 -0.0002167 -0.6060 NaN NaN -#> log_k_m1 -0.0002167 1.0000000 0.5474 NaN NaN -#> f_parent_qlogis -0.6060320 0.5474423 1.0000 NaN NaN -#> log_alpha NaN NaN NaN 1 NaN -#> log_beta NaN NaN NaN NaN 1 -#> sigma_low NaN NaN NaN NaN NaN -#> rsd_high NaN NaN NaN NaN NaN -#> sigma_low rsd_high -#> parent_0 NaN NaN -#> log_k_m1 NaN NaN -#> f_parent_qlogis NaN NaN -#> log_alpha NaN NaN -#> log_beta NaN NaN -#> sigma_low 1 NaN -#> rsd_high NaN 1 +#> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta +#> parent_0 1.000000 -0.095226 -0.76678 0.70544 NaN +#> log_k_m1 -0.095226 1.000000 0.51432 -0.14387 NaN +#> f_parent_qlogis -0.766780 0.514321 1.00000 -0.61396 NaN +#> log_alpha 0.705444 -0.143872 -0.61396 1.00000 NaN +#> log_beta NaN NaN NaN NaN 1 +#> sigma_low 0.016073 0.001586 0.01548 5.87007 NaN +#> rsd_high 0.006626 -0.011700 -0.05357 0.04849 NaN +#> sigma_low rsd_high +#> parent_0 0.016073 0.006626 +#> log_k_m1 0.001586 -0.011700 +#> f_parent_qlogis 0.015476 -0.053566 +#> log_alpha 5.870075 0.048487 +#> log_beta NaN NaN +#> sigma_low 1.000000 -0.652558 +#> rsd_high -0.652558 1.000000 #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. #> t-test (unrealistically) based on the assumption of normal distribution #> for estimators of untransformed parameters. #> Estimate t value Pr(>t) Lower Upper -#> parent_0 1.016e+02 32.5400 7.812e-26 97.740000 1.055e+02 -#> k_m1 5.069e-03 10.0400 1.448e-11 0.004194 6.126e-03 -#> f_parent_to_m1 5.002e-01 20.7300 5.001e-20 0.468800 5.315e-01 -#> alpha 2.367e+02 0.6205 2.697e-01 NA NA -#> beta 2.322e+03 0.6114 2.727e-01 NA NA -#> sigma_low 0.000e+00 NaN NaN NaN NaN -#> rsd_high 7.989e-02 8.6630 4.393e-10 NaN NaN +#> parent_0 1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02 +#> k_m1 5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03 +#> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01 +#> alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02 +#> beta 2.455e+03 0.5549 2.915e-01 NA NA +#> sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03 +#> rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02 #> #> FOCUS Chi2 error levels in percent: #> err.min n.optim df -#> All data 6.782 5 14 -#> parent 7.142 3 6 -#> m1 4.639 2 8 +#> All data 6.781 5 14 +#> parent 7.141 3 6 +#> m1 4.640 2 8 #> #> Resulting formation fractions: #> ff -#> parent_m1 0.5002 -#> parent_sink 0.4998 +#> parent_m1 0.5004 +#> parent_sink 0.4996 #> #> Estimated disappearance times: -#> DT50 DT90 DT50back -#> parent 6.81 22.7 6.833 -#> m1 136.74 454.2 NA</div><div class='input'> +#> DT50 DT90 DT50back +#> parent 6.812 22.7 6.834 +#> m1 136.661 454.0 NA</div><div class='input'> <span class='co'># We can easily use starting parameters from the parent only fit (only for illustration)</span> <span class='va'>fit.FOMC</span> <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> <span class='va'>fit.FOMC_SFO</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, diff --git a/docs/dev/reference/mkinmod.html b/docs/dev/reference/mkinmod.html index 9a7dac6f..e57e7062 100644 --- a/docs/dev/reference/mkinmod.html +++ b/docs/dev/reference/mkinmod.html @@ -44,9 +44,7 @@ variable, specifying the corresponding submodel as well as outgoing pathways (see examples). Print mkinmod objects in a way that the user finds his way to get to its -components. -This is a convenience function to set up the lists used as arguments for -mkinmod." /> +components." /> <meta name="robots" content="noindex"> @@ -78,7 +76,7 @@ mkinmod." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -127,7 +125,7 @@ mkinmod." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -155,8 +153,6 @@ variable, specifying the corresponding submodel as well as outgoing pathways (see examples).</p> <p>Print mkinmod objects in a way that the user finds his way to get to its components.</p> -<p>This is a convenience function to set up the lists used as arguments for -<code>mkinmod</code>.</p> </div> <pre class="usage"><span class='fu'>mkinmod</span><span class='op'>(</span> @@ -348,7 +344,7 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media</p> parent <span class='op'>=</span> <span class='fu'>mkinsub</span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span>, full_name <span class='op'>=</span> <span class='st'>"Test compound"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'>mkinsub</span><span class='op'>(</span><span class='st'>"SFO"</span>, full_name <span class='op'>=</span> <span class='st'>"Metabolite M1"</span><span class='op'>)</span>, name <span class='op'>=</span> <span class='st'>"SFO_SFO"</span>, dll_dir <span class='op'>=</span> <span class='va'>DLL_dir</span>, unload <span class='op'>=</span> <span class='cn'>TRUE</span>, overwrite <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Copied DLL from /tmp/Rtmpy4eiQb/file554e573761a7.so to /home/jranke/.local/share/mkin/SFO_SFO.so</span></div><div class='input'><span class='co'># Now we can save the model and restore it in a new session</span> +</div><div class='output co'>#> <span class='message'>Copied DLL from /tmp/RtmpPWWdbW/fileccff46a6d9773.so to /home/jranke/.local/share/mkin/SFO_SFO.so</span></div><div class='input'><span class='co'># Now we can save the model and restore it in a new session</span> <span class='fu'><a href='https://rdrr.io/r/base/readRDS.html'>saveRDS</a></span><span class='op'>(</span><span class='va'>SFO_SFO.2</span>, file <span class='op'>=</span> <span class='st'>"~/SFO_SFO.rds"</span><span class='op'>)</span> <span class='co'># Terminate the R session here if you would like to check, and then do</span> <span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://pkgdown.jrwb.de/mkin/'>mkin</a></span><span class='op'>)</span> @@ -397,7 +393,7 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media</p> #> }) #> return(predicted) #> } -#> <environment: 0x55555cac8d00></div><div class='input'> +#> <environment: 0x5555645abab8></div><div class='input'> <span class='co'># If we have several parallel metabolites</span> <span class='co'># (compare tests/testthat/test_synthetic_data_for_UBA_2014.R)</span> <span class='va'>m_synth_DFOP_par</span> <span class='op'><-</span> <span class='fu'>mkinmod</span><span class='op'>(</span> diff --git a/docs/dev/reference/mkinparplot-1.png b/docs/dev/reference/mkinparplot-1.png Binary files differindex dcf3e4b5..c9ed49eb 100644 --- a/docs/dev/reference/mkinparplot-1.png +++ b/docs/dev/reference/mkinparplot-1.png diff --git a/docs/dev/reference/mkinparplot.html b/docs/dev/reference/mkinparplot.html index 0a989ef9..bac6e71c 100644 --- a/docs/dev/reference/mkinparplot.html +++ b/docs/dev/reference/mkinparplot.html @@ -73,7 +73,7 @@ mkinfit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ mkinfit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -176,7 +176,8 @@ effect, namely to produce a plot.</p> phenol <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"anisole"</span><span class='op'>)</span><span class='op'>)</span>, anisole <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>model</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>mccall81_245T</span>, <span class='va'>soil</span> <span class='op'>==</span> <span class='st'>"Commerce"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='fu'>mkinparplot</span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> +#> <span class='warning'>false convergence (8)</span></div><div class='input'><span class='fu'>mkinparplot</span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> </div><div class='img'><img src='mkinparplot-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span> </div></pre> </div> diff --git a/docs/dev/reference/mkinplot.html b/docs/dev/reference/mkinplot.html index 417c8c73..120bddb3 100644 --- a/docs/dev/reference/mkinplot.html +++ b/docs/dev/reference/mkinplot.html @@ -73,7 +73,7 @@ plot.mkinfit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ plot.mkinfit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/mkinpredict.html b/docs/dev/reference/mkinpredict.html index 3221fc23..1ebaecb5 100644 --- a/docs/dev/reference/mkinpredict.html +++ b/docs/dev/reference/mkinpredict.html @@ -74,7 +74,7 @@ kinetic parameters and initial values for the state variables." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ kinetic parameters and initial values for the state variables." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -408,10 +408,10 @@ as these always return mapped output.</p></td> solution_type <span class='op'>=</span> <span class='st'>"analytical"</span>, use_compiled <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span><span class='op'>[</span><span class='fl'>201</span>,<span class='op'>]</span><span class='op'>)</span> <span class='op'>}</span> </div><div class='output co'>#> test relative elapsed +#> 2 deSolve_compiled 1.0 0.005 #> 4 analytical 1.0 0.005 -#> 2 deSolve_compiled 1.2 0.006 -#> 1 eigen 4.0 0.020 -#> 3 deSolve 44.2 0.221</div><div class='input'> +#> 1 eigen 4.4 0.022 +#> 3 deSolve 46.8 0.234</div><div class='input'> <span class='co'># \dontrun{</span> <span class='co'># Predict from a fitted model</span> <span class='va'>f</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_C</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> diff --git a/docs/dev/reference/mkinresplot.html b/docs/dev/reference/mkinresplot.html index 4b2f6bea..30377f2c 100644 --- a/docs/dev/reference/mkinresplot.html +++ b/docs/dev/reference/mkinresplot.html @@ -75,7 +75,7 @@ argument show_residuals = TRUE." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -124,7 +124,7 @@ argument show_residuals = TRUE." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -242,7 +242,7 @@ lines of the mkinfit object, and <code><a href='plot.mkinfit.html'>plot_res</a>< combining the plot of the fit and the residual plot.</p></div> <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> - <p>Johannes Ranke</p> + <p>Johannes Ranke and Katrin Lindenberger</p> <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'> diff --git a/docs/dev/reference/mmkin-1.png b/docs/dev/reference/mmkin-1.png Binary files differindex 7b7da90a..701a6d6a 100644 --- a/docs/dev/reference/mmkin-1.png +++ b/docs/dev/reference/mmkin-1.png diff --git a/docs/dev/reference/mmkin-2.png b/docs/dev/reference/mmkin-2.png Binary files differindex ce2b2af4..5277b389 100644 --- a/docs/dev/reference/mmkin-2.png +++ b/docs/dev/reference/mmkin-2.png diff --git a/docs/dev/reference/mmkin-3.png b/docs/dev/reference/mmkin-3.png Binary files differindex bb96f1b2..2659cd61 100644 --- a/docs/dev/reference/mmkin-3.png +++ b/docs/dev/reference/mmkin-3.png diff --git a/docs/dev/reference/mmkin-4.png b/docs/dev/reference/mmkin-4.png Binary files differindex 351b21aa..ae16ee79 100644 --- a/docs/dev/reference/mmkin-4.png +++ b/docs/dev/reference/mmkin-4.png diff --git a/docs/dev/reference/mmkin-5.png b/docs/dev/reference/mmkin-5.png Binary files differindex c1c05eea..2b9dc831 100644 --- a/docs/dev/reference/mmkin-5.png +++ b/docs/dev/reference/mmkin-5.png diff --git a/docs/dev/reference/mmkin.html b/docs/dev/reference/mmkin.html index 651eb9a6..c385bbf6 100644 --- a/docs/dev/reference/mmkin.html +++ b/docs/dev/reference/mmkin.html @@ -75,7 +75,7 @@ datasets specified in its first two arguments." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.5</span> </span> </div> @@ -124,7 +124,7 @@ datasets specified in its first two arguments." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -155,10 +155,13 @@ datasets specified in its first two arguments.</p> <pre class="usage"><span class='fu'>mmkin</span><span class='op'>(</span> models <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>datasets</span>, - cores <span class='op'>=</span> <span class='fu'>parallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span><span class='op'>(</span><span class='op'>)</span>, + cores <span class='op'>=</span> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>[</span><span class='st'>"sysname"</span><span class='op'>]</span> <span class='op'>==</span> <span class='st'>"Windows"</span><span class='op'>)</span> <span class='fl'>1</span> <span class='kw'>else</span> <span class='fu'>parallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span><span class='op'>(</span><span class='op'>)</span>, cluster <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>...</span> -<span class='op'>)</span></pre> +<span class='op'>)</span> + +<span class='co'># S3 method for mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span></pre> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> <table class="ref-arguments"> @@ -180,7 +183,8 @@ data for <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> is only used when the <code>cluster</code> argument is <code>NULL</code>. On Windows machines, cores > 1 is not supported, you need to use the <code>cluster</code> argument to use multiple logical processors. Per default, all cores -detected by <code><a href='https://rdrr.io/r/parallel/detectCores.html'>parallel::detectCores()</a></code> are used.</p></td> +detected by <code><a href='https://rdrr.io/r/parallel/detectCores.html'>parallel::detectCores()</a></code> are used, except on Windows where +the default is 1.</p></td> </tr> <tr> <th>cluster</th> @@ -189,7 +193,11 @@ for parallel execution.</p></td> </tr> <tr> <th>...</th> - <td><p>Further arguments that will be passed to <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> + <td><p>Not used.</p></td> + </tr> + <tr> + <th>x</th> + <td><p>An mmkin object.</p></td> </tr> </table> @@ -227,19 +235,19 @@ plotting.</p></div> <span class='va'>time_default</span> </div><div class='output co'>#> user system elapsed -#> 4.968 0.427 1.342 </div><div class='input'><span class='va'>time_1</span> +#> 4.771 0.576 1.803 </div><div class='input'><span class='va'>time_1</span> </div><div class='output co'>#> user system elapsed -#> 5.365 0.000 5.368 </div><div class='input'> +#> 5.779 0.000 5.781 </div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fits.0</span><span class='op'>[[</span><span class='st'>"SFO_lin"</span>, <span class='fl'>2</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> parent_M1 parent_sink M1_M2 M1_sink -#> 0.7340478 0.2659522 0.7505687 0.2494313 +#> 0.7340481 0.2659519 0.7505683 0.2494317 #> #> $distimes #> DT50 DT90 #> parent 0.877769 2.915885 -#> M1 2.325746 7.725960 -#> M2 33.720083 112.015691 +#> M1 2.325744 7.725956 +#> M2 33.720100 112.015749 #> </div><div class='input'> <span class='co'># plot.mkinfit handles rows or columns of mmkin result objects</span> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>fits.0</span><span class='op'>[</span><span class='fl'>1</span>, <span class='op'>]</span><span class='op'>)</span> @@ -266,12 +274,10 @@ plotting.</p></div> #> dataset #> model A B C D #> SFO OK OK OK OK -#> FOMC C OK OK OK +#> FOMC OK OK OK OK #> DFOP OK OK OK OK #> -#> OK: No warnings -#> C: Optimisation did not converge: -#> false convergence (8)</div><div class='input'><span class='co'># We get false convergence for the FOMC fit to FOCUS_2006_A because this</span> +#> OK: No warnings</div><div class='input'><span class='co'># We get false convergence for the FOMC fit to FOCUS_2006_A because this</span> <span class='co'># dataset is really SFO, and the FOMC fit is overparameterised</span> <span class='fu'>stopCluster</span><span class='op'>(</span><span class='va'>cl</span><span class='op'>)</span> <span class='co'># }</span> diff --git a/docs/dev/reference/nafta-1.png b/docs/dev/reference/nafta-1.png Binary files differindex 4d823d77..4f0d7833 100644 --- a/docs/dev/reference/nafta-1.png +++ b/docs/dev/reference/nafta-1.png diff --git a/docs/dev/reference/nafta.html b/docs/dev/reference/nafta.html index bbc8797d..6fb797a5 100644 --- a/docs/dev/reference/nafta.html +++ b/docs/dev/reference/nafta.html @@ -76,7 +76,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/nlme-1.png b/docs/dev/reference/nlme-1.png Binary files differindex 193722c7..f739089a 100644 --- a/docs/dev/reference/nlme-1.png +++ b/docs/dev/reference/nlme-1.png diff --git a/docs/dev/reference/nlme-2.png b/docs/dev/reference/nlme-2.png Binary files differindex c0fb6dcf..d3b29bb0 100644 --- a/docs/dev/reference/nlme-2.png +++ b/docs/dev/reference/nlme-2.png diff --git a/docs/dev/reference/nlme.html b/docs/dev/reference/nlme.html index b3e88428..184585df 100644 --- a/docs/dev/reference/nlme.html +++ b/docs/dev/reference/nlme.html @@ -75,7 +75,7 @@ datasets. They are used internally by the nlme.mmkin() method." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -124,7 +124,7 @@ datasets. They are used internally by the nlme.mmkin() method." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -155,8 +155,6 @@ datasets. They are used internally by the <code><a href='nlme.mmkin.html'>nlme.m <pre class="usage"><span class='fu'>nlme_function</span><span class='op'>(</span><span class='va'>object</span><span class='op'>)</span> -<span class='fu'>mean_degparms</span><span class='op'>(</span><span class='va'>object</span>, random <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> - <span class='fu'>nlme_data</span><span class='op'>(</span><span class='va'>object</span><span class='op'>)</span></pre> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> @@ -166,19 +164,11 @@ datasets. They are used internally by the <code><a href='nlme.mmkin.html'>nlme.m <th>object</th> <td><p>An mmkin row object containing several fits of the same model to different datasets</p></td> </tr> - <tr> - <th>random</th> - <td><p>Should a list with fixed and random effects be returned?</p></td> - </tr> </table> <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> <p>A function that can be used with nlme</p> -<p>If random is FALSE (default), a named vector containing mean values -of the fitted degradation model parameters. If random is TRUE, a list with -fixed and random effects, in the format required by the start argument of -nlme for the case of a single grouping variable ds.</p> <p>A <code><a href='https://rdrr.io/pkg/nlme/man/groupedData.html'>groupedData</a></code> object</p> <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2> @@ -206,12 +196,12 @@ nlme for the case of a single grouping variable ds.</p> <span class='va'>ds</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>d1 <span class='op'>=</span> <span class='va'>d1</span>, d2 <span class='op'>=</span> <span class='va'>d2</span>, d3 <span class='op'>=</span> <span class='va'>d3</span><span class='op'>)</span> <span class='va'>f</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>ds</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='va'>mean_dp</span> <span class='op'><-</span> <span class='fu'>mean_degparms</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> +<span class='va'>mean_dp</span> <span class='op'><-</span> <span class='fu'><a href='mean_degparms.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> <span class='va'>grouped_data</span> <span class='op'><-</span> <span class='fu'>nlme_data</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> <span class='va'>nlme_f</span> <span class='op'><-</span> <span class='fu'>nlme_function</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> <span class='co'># These assignments are necessary for these objects to be</span> <span class='co'># visible to nlme and augPred when evaluation is done by</span> -<span class='co'># pkgdown to generated the html docs.</span> +<span class='co'># pkgdown to generate the html docs.</span> <span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span><span class='op'>(</span><span class='st'>"nlme_f"</span>, <span class='va'>nlme_f</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span><span class='op'>(</span><span class='st'>"grouped_data"</span>, <span class='va'>grouped_data</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span> @@ -224,37 +214,37 @@ nlme for the case of a single grouping variable ds.</p> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>m_nlme</span><span class='op'>)</span> </div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood #> Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) -#> Data: grouped_data +#> Data: grouped_data #> AIC BIC logLik -#> 252.7798 262.1358 -121.3899 +#> 278.1355 287.7946 -134.0677 #> #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1) #> Level: ds #> Structure: Diagonal -#> parent_0 log_k_parent_sink Residual -#> StdDev: 0.0006768135 0.6800777 2.489397 +#> parent_0 log_k_parent_sink Residual +#> StdDev: 3.406042 0.6437579 2.620833 #> -#> Fixed effects: parent_0 + log_k_parent_sink ~ 1 -#> Value Std.Error DF t-value p-value -#> parent_0 101.74884 0.6456014 44 157.60321 0 -#> log_k_parent_sink -3.05575 0.4015811 44 -7.60929 0 +#> Fixed effects: parent_0 + log_k_parent_sink ~ 1 +#> Value Std.Error DF t-value p-value +#> parent_0 101.50173 2.123709 47 47.79457 0 +#> log_k_parent_sink -3.07597 0.379775 47 -8.09945 0 #> Correlation: #> prnt_0 -#> log_k_parent_sink 0.026 +#> log_k_parent_sink 0.01 #> #> Standardized Within-Group Residuals: -#> Min Q1 Med Q3 Max -#> -2.1317488 -0.6878121 0.0828385 0.8592270 2.9529864 +#> Min Q1 Med Q3 Max +#> -2.06889303 -0.50100169 -0.06268253 0.62557544 2.19922001 #> -#> Number of Observations: 48 +#> Number of Observations: 51 #> Number of Groups: 3 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/pkg/nlme/man/augPred.html'>augPred</a></span><span class='op'>(</span><span class='va'>m_nlme</span>, level <span class='op'>=</span> <span class='fl'>0</span><span class='op'>:</span><span class='fl'>1</span><span class='op'>)</span>, layout <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fl'>1</span><span class='op'>)</span><span class='op'>)</span> </div><div class='img'><img src='nlme-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># augPred does not work on fits with more than one state</span> <span class='co'># variable</span> <span class='co'>#</span> <span class='co'># The procedure is greatly simplified by the nlme.mmkin function</span> <span class='va'>f_nlme</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Iteration 1, LME step: nlminb() did not converge (code = 1). Do increase 'msMaxIter'!</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme</span><span class='op'>)</span> </div><div class='img'><img src='nlme-2.png' alt='' width='700' height='433' /></div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> diff --git a/docs/dev/reference/nlme.mmkin-1.png b/docs/dev/reference/nlme.mmkin-1.png Binary files differindex 25bebeca..95adfafb 100644 --- a/docs/dev/reference/nlme.mmkin-1.png +++ b/docs/dev/reference/nlme.mmkin-1.png diff --git a/docs/dev/reference/nlme.mmkin-2.png b/docs/dev/reference/nlme.mmkin-2.png Binary files differindex c314c149..53b6fc76 100644 --- a/docs/dev/reference/nlme.mmkin-2.png +++ b/docs/dev/reference/nlme.mmkin-2.png diff --git a/docs/dev/reference/nlme.mmkin-3.png b/docs/dev/reference/nlme.mmkin-3.png Binary files differindex a40b7cad..8df1e73b 100644 --- a/docs/dev/reference/nlme.mmkin-3.png +++ b/docs/dev/reference/nlme.mmkin-3.png diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html index a4d7070a..866091ca 100644 --- a/docs/dev/reference/nlme.mmkin.html +++ b/docs/dev/reference/nlme.mmkin.html @@ -74,7 +74,7 @@ have been obtained by fitting the same model to a list of datasets." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -123,7 +123,7 @@ have been obtained by fitting the same model to a list of datasets." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -155,11 +155,11 @@ have been obtained by fitting the same model to a list of datasets.</p> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span> <span class='va'>model</span>, data <span class='op'>=</span> <span class='st'>"auto"</span>, - fixed <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>as.list</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='fu'><a href='nlme_function.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>el</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/eval.html'>eval</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/parse.html'>parse</a></span><span class='op'>(</span>text <span class='op'>=</span> + fixed <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>as.list</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='fu'><a href='mean_degparms.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>el</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/eval.html'>eval</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/parse.html'>parse</a></span><span class='op'>(</span>text <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='va'>el</span>, <span class='fl'>1</span>, sep <span class='op'>=</span> <span class='st'>"~"</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>, - random <span class='op'>=</span> <span class='fu'>pdDiag</span><span class='op'>(</span><span class='va'>fixed</span><span class='op'>)</span>, + random <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/pdDiag.html'>pdDiag</a></span><span class='op'>(</span><span class='va'>fixed</span><span class='op'>)</span>, <span class='va'>groups</span>, - start <span class='op'>=</span> <span class='fu'><a href='nlme_function.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span>, random <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, + start <span class='op'>=</span> <span class='fu'><a href='mean_degparms.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span>, random <span class='op'>=</span> <span class='cn'>TRUE</span>, test_log_parms <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, correlation <span class='op'>=</span> <span class='cn'>NULL</span>, weights <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>subset</span>, @@ -194,10 +194,9 @@ mmkin model are used as fixed parameters</p></td> </tr> <tr> <th>random</th> - <td><p>If not specified, correlated random effects are set up -for all optimised degradation model parameters using the log-Cholesky -parameterization <a href='https://rdrr.io/pkg/nlme/man/pdLogChol.html'>nlme::pdLogChol</a> that is also the default of -the generic <a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a> method.</p></td> + <td><p>If not specified, no correlations between random effects are +set up for the optimised degradation model parameters. This is +achieved by using the <a href='https://rdrr.io/pkg/nlme/man/pdDiag.html'>nlme::pdDiag</a> method.</p></td> </tr> <tr> <th>groups</th> @@ -262,6 +261,12 @@ parameters taken from the mmkin object are used</p></td> <p>Upon success, a fitted 'nlme.mmkin' object, which is an nlme object with additional elements. It also inherits from 'mixed.mmkin'.</p> + <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> + + <p>Note that the convergence of the nlme algorithms depends on the quality +of the data. In degradation kinetics, we often only have few datasets +(e.g. data for few soils) and complicated degradation models, which may +make it impossible to obtain convergence with nlme.</p> <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2> <p>As the object inherits from <a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme::nlme</a>, there is a wealth of @@ -284,7 +289,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo</span>, <span class='va'>f_nlme_dfop</span><span class='op'>)</span> </div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value #> f_nlme_sfo 1 5 625.0539 637.5529 -307.5269 -#> f_nlme_dfop 2 9 495.1270 517.6253 -238.5635 1 vs 2 137.9268 <.0001</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span> +#> f_nlme_dfop 2 9 495.1270 517.6253 -238.5635 1 vs 2 137.9269 <.0001</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span> </div><div class='output co'>#> Kinetic nonlinear mixed-effects model fit by maximum likelihood #> #> Structural model: @@ -312,7 +317,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as </div><div class='img'><img src='nlme.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span> </div><div class='output co'>#> $distimes #> DT50 DT90 DT50back DT50_k1 DT50_k2 -#> parent 10.79857 100.7937 30.34192 4.193937 43.85442 +#> parent 10.79857 100.7937 30.34193 4.193938 43.85443 #> </div><div class='input'> <span class='va'>ds_2</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='va'>x</span><span class='op'>$</span><span class='va'>data</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span> @@ -335,16 +340,17 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class='co'># f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])</span> <span class='co'>#plot(f_nlme_sfo_sfo_ff)</span> - <span class='co'># With the log-Cholesky parameterization, this converges in 11</span> - <span class='co'># iterations and around 100 seconds, but without tweaking control</span> - <span class='co'># parameters (with pdDiag, increasing the tolerance and pnlsMaxIter was</span> - <span class='co'># necessary)</span> - <span class='va'>f_nlme_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in nlme.formula(model = value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_A1, f_parent_qlogis, log_k1, log_k2, g_qlogis), data = structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L ), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 4.3, 4.6, 7, 7.2, 8.2, 8, 11, 13.7, 11.5, 12.7, 14.9, 14.5, 12.1, 12.3, 9.9, 10.2, 8.8, 7.8, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 3.9, 3.1, 6.9, 6.6, 10.4, 8.3, 14.4, 13.7, 22.1, 22.3, 27.5, 25.4, 28, 26.6, 25.8, 25.3, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 9.6, 7.7, 15, 15.1, 21.2, 21.1, 19.7, 18.9, 17.5, 15.9, 9.5, 9.8, 6.2, 6.1, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 4.2, 3.9, 7.4, 7.9, 14.5, 13.7, 14.2, 12.2, 13.7, 13.2, 13.6, 15.4, 10.4, 11.6, 10, 9.5, 9.1, 9, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3, 3.3, 3.4, 3.9, 2.9, 6.4, 7.2, 9.1, 8.5, 11.7, 12, 13.3, 13.2, 14.3, 12.1)), row.names = c(NA, -170L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE), start = list( fixed = c(parent_0 = 93.8101519326534, log_k_A1 = -9.76474551635931, f_parent_qlogis = -0.971114801595408, log_k1 = -1.87993711571859, log_k2 = -4.27081421366622, g_qlogis = 0.135644115277507 ), random = list(ds = structure(c(2.56569977430371, -3.49441920289139, -3.32614443321494, 4.35347873814922, -0.0986148763466161, 4.65850590018027, 1.8618544764481, 6.12693257601545, 4.91792724701579, -17.5652201996596, -0.466203822618637, 0.746660653597927, 0.282193987271096, -0.42053488943072, -0.142115928819667, 0.369240076779088, -1.38985563501659, 1.02592753494098, 0.73090914081534, -0.736221117518819, 0.768170629350299, -1.89347658079869, 1.72168783460352, 0.844607177798114, -1.44098906095325, -0.377731855445672, 0.168180098477565, 0.469683412912104, 0.500717664434525, -0.760849320378522), .Dim = 5:6, .Dimnames = list(c("1", "2", "3", "4", "5"), c("parent_0", "log_k_A1", "f_parent_qlogis", "log_k1", "log_k2", "g_qlogis"))))), fixed = list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), random = structure(numeric(0), class = c("pdDiag", "pdMat"), formula = structure(list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), class = "listForm"), Dimnames = list(NULL, NULL))): maximum number of iterations (maxIter = 50) reached without convergence</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 49.95 16.5 44.08</span></div><div class='input'> + <span class='co'># For the following, we need to increase pnlsMaxIter and the tolerance</span> + <span class='co'># to get convergence</span> + <span class='va'>f_nlme_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>5e-4</span><span class='op'>)</span><span class='op'>)</span> + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in plot(f_nlme_dfop_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='img'><img src='nlme.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value +#> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 +#> f_nlme_sfo_sfo 2 9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274 <.0001</div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> parent_sink parent_A1 A1_sink @@ -355,7 +361,15 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> parent 19.13518 63.5657 #> A1 66.02155 219.3189 #> </div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in endpoints(f_nlme_dfop_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='output co'>#> $ff +#> parent_A1 parent_sink +#> 0.2768574 0.7231426 +#> +#> $distimes +#> DT50 DT90 DT50back DT50_k1 DT50_k2 +#> parent 11.07091 104.6320 31.49737 4.462383 46.20825 +#> A1 162.30519 539.1662 NA NA NA +#> </div><div class='input'> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='fu'>findFunction</span><span class='op'>(</span><span class='st'>"varConstProp"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>></span> <span class='fl'>0</span><span class='op'>)</span> <span class='op'>{</span> <span class='co'># tc error model for nlme available</span> <span class='co'># Attempts to fit metabolite kinetics with the tc error model are possible,</span> <span class='co'># but need tweeking of control values and sometimes do not converge</span> @@ -381,7 +395,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> Fixed effects: #> list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) #> parent_0 log_k1 log_k2 g_qlogis -#> 94.04775 -1.82340 -4.16715 0.05685 +#> 94.04774 -1.82340 -4.16716 0.05686 #> #> Random effects: #> Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) @@ -395,10 +409,8 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> Formula: ~fitted(.) #> Parameter estimates: #> const prop -#> 2.23224114 0.01262341 </div><div class='input'> - <span class='va'>f_2_obs</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo</span>, - <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>m_dfop_sfo</span><span class='op'>)</span>, - <span class='va'>ds_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> +#> 2.23223147 0.01262395 </div><div class='input'> + <span class='va'>f_2_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_2</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> <span class='va'>f_nlme_sfo_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo_obs</span><span class='op'>)</span> </div><div class='output co'>#> Kinetic nonlinear mixed-effects model fit by maximum likelihood @@ -429,18 +441,21 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> Formula: ~1 | name #> Parameter estimates: #> parent A1 -#> 1.0000000 0.2050003 </div><div class='input'> <span class='va'>f_nlme_dfop_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in nlme.formula(model = value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_A1, f_parent_qlogis, log_k1, log_k2, g_qlogis), data = structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L ), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 4.3, 4.6, 7, 7.2, 8.2, 8, 11, 13.7, 11.5, 12.7, 14.9, 14.5, 12.1, 12.3, 9.9, 10.2, 8.8, 7.8, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 3.9, 3.1, 6.9, 6.6, 10.4, 8.3, 14.4, 13.7, 22.1, 22.3, 27.5, 25.4, 28, 26.6, 25.8, 25.3, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 9.6, 7.7, 15, 15.1, 21.2, 21.1, 19.7, 18.9, 17.5, 15.9, 9.5, 9.8, 6.2, 6.1, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 4.2, 3.9, 7.4, 7.9, 14.5, 13.7, 14.2, 12.2, 13.7, 13.2, 13.6, 15.4, 10.4, 11.6, 10, 9.5, 9.1, 9, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3, 3.3, 3.4, 3.9, 2.9, 6.4, 7.2, 9.1, 8.5, 11.7, 12, 13.3, 13.2, 14.3, 12.1)), row.names = c(NA, -170L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE), start = list( fixed = c(parent_0 = 93.4272167134207, log_k_A1 = -9.71590717106959, f_parent_qlogis = -0.953712099744438, log_k1 = -1.95256957646888, log_k2 = -4.42919226610318, g_qlogis = 0.193023137298073 ), random = list(ds = structure(c(2.85557330683041, -3.87630303729395, -2.78062140212751, 4.82042042600536, -1.01906929341432, 4.613992019697, 2.05871276943309, 6.0766404049189, 4.86471337131288, -17.6140585653619, -0.480721175257541, 0.773079218835614, 0.260464433006093, -0.440615012802434, -0.112207463781733, 0.445812953745225, -1.49588630006094, 1.13602040717272, 0.801850880762046, -0.887797941619048, 0.936480292463262, -2.43093808171905, 1.91256225793793, 0.984827519864443, -1.40293198854659, -0.455176326336681, 0.376355651864385, 0.343919720700401, 0.46329187713133, -0.728390923359434 ), .Dim = 5:6, .Dimnames = list(c("1", "2", "3", "4", "5"), c("parent_0", "log_k_A1", "f_parent_qlogis", "log_k1", "log_k2", "g_qlogis"))))), fixed = list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), random = structure(numeric(0), class = c("pdDiag", "pdMat"), formula = structure(list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), class = "listForm"), Dimnames = list(NULL, NULL)), weights = structure(numeric(0), formula = ~1 | name, class = c("varIdent", "varFunc"))): maximum number of iterations (maxIter = 50) reached without convergence</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 59.38 16.5 53.5</span></div><div class='input'> - <span class='va'>f_2_tc</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo</span>, - <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>m_dfop_sfo</span><span class='op'>)</span>, - <span class='va'>ds_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> - <span class='co'># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # stops with error message</span> - <span class='va'>f_nlme_dfop_sfo_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_tc</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='error'>Error in X[, fmap[[nm]]] <- gradnm: number of items to replace is not a multiple of replacement length</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 6.363 2.688 5.469</span></div><div class='input'> <span class='co'># We get warnings about false convergence in the LME step in several iterations</span> - <span class='co'># but as the last such warning occurs in iteration 25 and we have 28 iterations</span> - <span class='co'># we can ignore these</span> - <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_dfop_sfo_obs</span>, <span class='va'>f_nlme_dfop_sfo_tc</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs, f_nlme_dfop_sfo_tc): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +#> 1.0000000 0.2049995 </div><div class='input'> <span class='va'>f_nlme_dfop_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>5e-4</span><span class='op'>)</span><span class='op'>)</span> + + <span class='va'>f_2_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_2</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> + <span class='co'># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations</span> + <span class='co'># f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ],</span> + <span class='co'># control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm</span> + + <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_dfop_sfo_obs</span><span class='op'>)</span> +</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio +#> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 +#> f_nlme_dfop_sfo_obs 2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32091 +#> p-value +#> f_nlme_dfop_sfo +#> f_nlme_dfop_sfo_obs <.0001</div><div class='input'> <span class='co'># }</span> </div></pre> </div> diff --git a/docs/dev/reference/nlmixr.mmkin-1.png 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<header> + <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"> + <li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul 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navbar-right"> + <li> + <a href="https://github.com/jranke/mkin/"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul> + + </div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header> + +<div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Fit nonlinear mixed models using nlmixr</h1> + <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/nlmixr.R'><code>R/nlmixr.R</code></a></small> + <div class="hidden name"><code>nlmixr.mmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>This function uses <code><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr()</a></code> as a backend for fitting nonlinear mixed +effects models created from <a href='mmkin.html'>mmkin</a> row objects using the Stochastic Approximation +Expectation Maximisation algorithm (SAEM).</p> + </div> + + <pre class="usage"><span class='co'># S3 method for mmkin</span> +<span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span> + <span class='va'>object</span>, + data <span class='op'>=</span> <span class='cn'>NULL</span>, + est <span class='op'>=</span> <span class='cn'>NULL</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='op'>)</span>, + table <span class='op'>=</span> <span class='fu'>tableControl</span><span class='op'>(</span><span class='op'>)</span>, + error_model <span class='op'>=</span> <span class='va'>object</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>err_mod</span>, + test_log_parms <span class='op'>=</span> <span class='cn'>TRUE</span>, + conf.level <span class='op'>=</span> <span class='fl'>0.6</span>, + degparms_start <span class='op'>=</span> <span class='st'>"auto"</span>, + eta_start <span class='op'>=</span> <span class='st'>"auto"</span>, + <span class='va'>...</span>, + save <span class='op'>=</span> <span class='cn'>NULL</span>, + envir <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sys.parent.html'>parent.frame</a></span><span class='op'>(</span><span class='op'>)</span> +<span class='op'>)</span> + +<span class='co'># S3 method for nlmixr.mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, digits <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"digits"</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>3</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span> + +<span class='fu'>nlmixr_model</span><span class='op'>(</span> + <span class='va'>object</span>, + est <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"saem"</span>, <span class='st'>"focei"</span><span class='op'>)</span>, + degparms_start <span class='op'>=</span> <span class='st'>"auto"</span>, + eta_start <span class='op'>=</span> <span class='st'>"auto"</span>, + test_log_parms <span class='op'>=</span> <span class='cn'>TRUE</span>, + conf.level <span class='op'>=</span> <span class='fl'>0.6</span>, + error_model <span class='op'>=</span> <span class='va'>object</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>err_mod</span>, + add_attributes <span class='op'>=</span> <span class='cn'>FALSE</span> +<span class='op'>)</span> + +<span class='fu'>nlmixr_data</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span></pre> + + <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>object</th> + <td><p>An <a href='mmkin.html'>mmkin</a> row object containing several fits of the same +<a href='mkinmod.html'>mkinmod</a> model to different datasets</p></td> + </tr> + <tr> + <th>data</th> + <td><p>Not used, as the data are extracted from the mmkin row object</p></td> + </tr> + <tr> + <th>est</th> + <td><p>Estimation method passed to <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p></td> + </tr> + <tr> + <th>control</th> + <td><p>Passed to <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p></td> + </tr> + <tr> + <th>table</th> + <td><p>Passed to <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p></td> + </tr> + <tr> + <th>error_model</th> + <td><p>Possibility to override the error model which is being +set based on the error model used in the mmkin row object.</p></td> + </tr> + <tr> + <th>test_log_parms</th> + <td><p>If TRUE, an attempt is made to use more robust starting +values for population parameters fitted as log parameters in mkin (like +rate constants) by only considering rate constants that pass the t-test +when calculating mean degradation parameters using <a href='mean_degparms.html'>mean_degparms</a>.</p></td> + </tr> + <tr> + <th>conf.level</th> + <td><p>Possibility to adjust the required confidence level +for parameter that are tested if requested by 'test_log_parms'.</p></td> + </tr> + <tr> + <th>degparms_start</th> + <td><p>Parameter values given as a named numeric vector will +be used to override the starting values obtained from the 'mmkin' object.</p></td> + </tr> + <tr> + <th>eta_start</th> + <td><p>Standard deviations on the transformed scale given as a +named numeric vector will be used to override the starting values obtained +from the 'mmkin' object.</p></td> + </tr> + <tr> + <th>...</th> + <td><p>Passed to nlmixr_model</p></td> + </tr> + <tr> + <th>save</th> + <td><p>Passed to <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p></td> + </tr> + <tr> + <th>envir</th> + <td><p>Passed to <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p></td> + </tr> + <tr> + <th>x</th> + <td><p>An nlmixr.mmkin object to print</p></td> + </tr> + <tr> + <th>digits</th> + <td><p>Number of digits to use for printing</p></td> + </tr> + <tr> + <th>add_attributes</th> + <td><p>Should the starting values used for degradation model +parameters and their distribution and for the error model parameters +be returned as attributes?</p></td> + </tr> + </table> + + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>An S3 object of class 'nlmixr.mmkin', containing the fitted +<a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a> object as a list component named 'nm'. The +object also inherits from 'mixed.mmkin'.</p> +<p>An function defining a model suitable for fitting with <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a>.</p> +<p>An dataframe suitable for use with <a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr::nlmixr</a></p> + <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> + + <p>An mmkin row object is essentially a list of mkinfit objects that have been +obtained by fitting the same model to a list of datasets using <a href='mkinfit.html'>mkinfit</a>.</p> + <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2> + + <div class='dont-index'><p><a href='summary.nlmixr.mmkin.html'>summary.nlmixr.mmkin</a> <a href='plot.mixed.mmkin.html'>plot.mixed.mmkin</a></p></div> + + <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> + <pre class="examples"><div class='input'><span class='co'># \dontrun{</span> +<span class='va'>ds</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>, + <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Dataset"</span>, <span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>)</span> + +<span class='va'>f_mmkin_parent</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span>, <span class='st'>"HS"</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span> +<span class='va'>f_mmkin_parent_tc</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>ds</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, + cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> + +<span class='va'>f_nlmixr_sfo_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> 1: 86.5083 -3.1968 4.1673 1.7173 48.7028 +#> 2: 87.3628 -3.1468 3.9589 1.6315 45.1225 +#> 3: 86.8866 -3.2249 3.7610 1.8212 43.0034 +#> 4: 85.9210 -3.2427 3.5729 1.7302 39.4197 +#> 5: 85.8539 -3.2018 3.3943 1.7234 38.2933 +#> 6: 85.6934 -3.2262 3.2246 1.6843 39.0348 +#> 7: 85.7421 -3.2696 4.1298 1.7086 39.8152 +#> 8: 85.1605 -3.2190 3.9234 1.7588 41.7476 +#> 9: 84.7745 -3.2389 3.7361 1.6708 41.8512 +#> 10: 84.6549 -3.2078 3.5493 1.6489 41.6110 +#> 11: 84.4739 -3.2788 3.3718 1.5664 42.0076 +#> 12: 84.7871 -3.2674 3.4931 1.6097 40.9060 +#> 13: 84.5267 -3.2635 3.3185 1.6352 39.6914 +#> 14: 84.9806 -3.2353 3.1525 1.6470 39.2556 +#> 15: 84.9752 -3.2566 2.9949 1.6756 39.6152 +#> 16: 85.6293 -3.2232 2.8452 1.7076 39.4391 +#> 17: 85.9944 -3.2268 2.7029 1.6702 40.2731 +#> 18: 86.2811 -3.2260 2.5678 1.7100 41.4854 +#> 19: 86.2617 -3.2476 2.4489 1.7051 41.3066 +#> 20: 85.7552 -3.2032 3.3323 1.8885 42.2273 +#> 21: 85.6493 -3.2685 3.2317 1.7941 39.4198 +#> 22: 86.0133 -3.2457 4.0910 1.7044 39.0319 +#> 23: 86.1636 -3.2528 4.9399 1.6571 38.6728 +#> 24: 86.3086 -3.1708 7.0791 1.8182 39.6791 +#> 25: 85.7316 -3.2203 6.7252 1.7369 38.3546 +#> 26: 85.3476 -3.2341 6.3889 1.6864 38.0521 +#> 27: 85.6328 -3.2543 6.0695 1.6945 37.7990 +#> 28: 85.1715 -3.2191 5.7660 1.7898 38.5662 +#> 29: 85.4945 -3.2264 5.4777 1.7007 40.1659 +#> 30: 85.0864 -3.2463 5.2038 1.6156 39.0718 +#> 31: 85.8220 -3.2347 4.9436 1.6115 39.2011 +#> 32: 85.9869 -3.2400 4.6964 1.6818 41.2956 +#> 33: 85.9899 -3.2041 4.4616 1.6606 40.6657 +#> 34: 85.8353 -3.2065 4.2385 1.6868 41.5006 +#> 35: 85.8113 -3.2366 4.0266 1.8261 41.0403 +#> 36: 85.5233 -3.2389 3.8253 1.7348 39.5202 +#> 37: 85.1751 -3.2657 3.6340 1.6948 39.6097 +#> 38: 85.2768 -3.2380 3.4887 1.6820 38.7641 +#> 39: 84.8240 -3.2264 3.3143 1.5979 39.8074 +#> 40: 85.3754 -3.2147 3.1485 1.5810 39.1710 +#> 41: 85.0277 -3.2347 2.9911 1.7061 39.9948 +#> 42: 85.0113 -3.2651 3.1969 1.6208 39.7266 +#> 43: 85.0772 -3.2729 3.0371 1.6160 40.2919 +#> 44: 85.0769 -3.2272 3.3310 1.7321 38.5229 +#> 45: 85.1638 -3.2546 3.1644 1.6968 40.2382 +#> 46: 84.7966 -3.2597 5.0694 1.6816 38.7996 +#> 47: 85.0588 -3.2247 5.9549 1.7452 39.6569 +#> 48: 85.1769 -3.2557 5.6572 1.7441 37.9050 +#> 49: 84.9296 -3.2425 5.3743 1.6729 37.7885 +#> 50: 85.3414 -3.2421 5.1056 1.6646 38.2243 +#> 51: 84.9127 -3.2674 5.8827 1.7180 40.2859 +#> 52: 85.2014 -3.2471 5.5885 1.7318 39.1745 +#> 53: 85.9330 -3.2228 7.2369 1.8328 39.0461 +#> 54: 86.9718 -3.1447 6.9332 1.8404 39.3098 +#> 55: 87.2708 -3.1595 6.6308 1.8049 39.1338 +#> 56: 87.2006 -3.1746 6.2993 1.7541 38.2780 +#> 57: 87.8013 -3.2306 5.9843 1.6664 40.4876 +#> 58: 87.7294 -3.2120 5.6851 1.5831 41.5056 +#> 59: 87.4898 -3.2207 5.4008 1.5039 41.4401 +#> 60: 86.9156 -3.1861 5.1308 1.6408 39.8972 +#> 61: 86.4508 -3.1870 4.8742 1.5935 39.6871 +#> 62: 86.4028 -3.2191 4.6305 1.6267 39.2092 +#> 63: 86.2536 -3.2491 4.5199 1.5617 39.7603 +#> 64: 85.9775 -3.2650 4.2939 1.6077 39.1909 +#> 65: 85.8907 -3.2430 4.0792 1.6729 37.9420 +#> 66: 85.3450 -3.2888 3.8753 1.6201 40.8998 +#> 67: 85.1869 -3.2940 3.6815 1.6157 40.5107 +#> 68: 84.8029 -3.2830 3.4974 1.6040 40.6254 +#> 69: 85.3549 -3.2425 4.4768 1.5238 40.2418 +#> 70: 85.7957 -3.2296 4.2529 1.7175 40.8618 +#> 71: 85.4200 -3.2381 4.0403 1.6695 41.5731 +#> 72: 85.2950 -3.2566 3.8383 1.5998 40.6494 +#> 73: 85.0683 -3.2464 3.6464 1.5576 39.8095 +#> 74: 85.1667 -3.2436 3.4641 1.6383 39.4925 +#> 75: 84.6547 -3.2300 3.7226 1.6656 40.4684 +#> 76: 84.4882 -3.2521 3.6468 1.6035 40.1800 +#> 77: 84.5250 -3.2398 4.1501 1.6827 40.5269 +#> 78: 84.5191 -3.2372 5.5482 1.6309 41.1739 +#> 79: 84.7471 -3.2581 6.0637 1.6259 41.1003 +#> 80: 85.0581 -3.2680 5.7605 1.6841 40.8918 +#> 81: 84.8468 -3.2564 5.4725 1.6475 39.3456 +#> 82: 84.7614 -3.2385 5.1988 1.7550 38.7275 +#> 83: 85.2921 -3.2657 5.9253 1.6672 39.2423 +#> 84: 85.5760 -3.2261 5.6290 1.7505 39.5500 +#> 85: 85.3215 -3.2277 5.5987 1.8027 39.3145 +#> 86: 85.2656 -3.2023 5.3188 1.8024 40.3098 +#> 87: 84.8950 -3.2551 5.0528 1.7123 39.3470 +#> 88: 84.3157 -3.2661 4.8002 1.6267 38.7095 +#> 89: 84.5442 -3.2870 4.5602 1.5892 39.1735 +#> 90: 85.0956 -3.2195 4.8385 1.5796 39.5164 +#> 91: 84.8619 -3.2621 4.5966 1.6889 39.5512 +#> 92: 84.4901 -3.2735 6.1405 1.6704 39.3358 +#> 93: 84.0819 -3.2609 5.8335 1.6130 38.8618 +#> 94: 84.7585 -3.2336 5.5418 1.6301 38.6591 +#> 95: 85.2669 -3.2358 5.2647 1.6619 38.9136 +#> 96: 85.4955 -3.2064 5.0015 1.7673 39.0495 +#> 97: 85.6591 -3.2016 4.7514 1.7046 40.7861 +#> 98: 86.2097 -3.2833 7.4722 1.6413 42.2938 +#> 99: 85.9645 -3.2570 7.7124 1.5592 41.7216 +#> 100: 85.7018 -3.2605 8.2687 1.6798 40.6639 +#> 101: 85.9905 -3.1956 11.0194 1.7017 39.4324 +#> 102: 87.2679 -3.1741 10.4684 1.7063 38.6812 +#> 103: 86.1910 -3.1709 9.9450 1.7151 38.5198 +#> 104: 86.4413 -3.1544 9.4478 1.7123 38.7428 +#> 105: 85.9840 -3.1921 10.6297 1.8135 38.7775 +#> 106: 85.9926 -3.1839 10.0982 1.7228 40.3136 +#> 107: 85.1792 -3.2343 9.5933 1.6367 40.2709 +#> 108: 84.7583 -3.2332 9.1136 1.6907 41.2122 +#> 109: 85.3756 -3.2311 8.6579 1.7307 39.9303 +#> 110: 84.9686 -3.2365 8.2250 1.7221 40.0379 +#> 111: 84.8527 -3.2448 7.8138 1.6775 39.6794 +#> 112: 84.6271 -3.2609 7.4231 1.7321 41.5666 +#> 113: 84.8515 -3.3056 7.2514 1.7001 41.9758 +#> 114: 84.5991 -3.2319 7.8463 1.7690 41.1386 +#> 115: 85.0535 -3.2864 7.4540 1.7282 40.3883 +#> 116: 85.8661 -3.2355 7.0813 1.7801 39.3078 +#> 117: 85.9911 -3.2357 6.7272 1.6911 38.3913 +#> 118: 86.1894 -3.2424 6.3909 1.6701 38.1915 +#> 119: 85.5637 -3.1992 6.0713 1.7360 38.9386 +#> 120: 86.0733 -3.2069 5.7677 1.7185 36.5189 +#> 121: 86.0168 -3.2181 5.4794 1.7135 38.4044 +#> 122: 86.7470 -3.2319 6.1989 1.6840 38.2615 +#> 123: 86.2918 -3.2089 5.8890 1.6656 38.8486 +#> 124: 85.9387 -3.2124 5.5945 1.6334 37.9425 +#> 125: 86.1519 -3.2717 5.3148 1.7094 38.9708 +#> 126: 85.5194 -3.2391 5.4217 1.6799 39.4876 +#> 127: 85.9691 -3.2205 5.8051 1.6436 40.0593 +#> 128: 85.6171 -3.2309 5.5148 1.6852 39.5398 +#> 129: 84.9252 -3.2495 5.2391 1.7154 40.4020 +#> 130: 85.1496 -3.2882 5.0538 1.7189 40.0908 +#> 131: 85.8552 -3.2474 7.1203 1.6329 39.0547 +#> 132: 86.4666 -3.2151 6.7643 1.7342 38.6596 +#> 133: 86.1550 -3.1895 6.4261 1.7904 38.6211 +#> 134: 86.5040 -3.1785 6.1048 1.7180 39.0804 +#> 135: 85.9752 -3.2116 5.7996 1.6979 38.1745 +#> 136: 86.2161 -3.2075 5.5096 1.7408 38.9002 +#> 137: 85.8408 -3.2604 6.9319 1.7616 39.1657 +#> 138: 86.1261 -3.2179 7.0802 1.8115 37.6614 +#> 139: 85.9082 -3.2374 6.7262 1.7209 38.1986 +#> 140: 85.9556 -3.2641 6.3899 1.8300 39.2071 +#> 141: 86.2052 -3.1928 6.0704 1.7385 38.1745 +#> 142: 86.4062 -3.2076 5.8348 1.6693 38.0271 +#> 143: 86.0680 -3.2372 5.5431 1.7259 39.3885 +#> 144: 86.2001 -3.2040 5.2659 1.6803 38.1606 +#> 145: 86.5820 -3.2306 5.0026 1.6063 38.7208 +#> 146: 86.4522 -3.2072 4.7525 1.6572 37.5206 +#> 147: 85.8311 -3.2320 4.5149 1.7043 39.6955 +#> 148: 86.0754 -3.2072 5.4070 1.6707 38.8858 +#> 149: 87.0038 -3.1954 5.1367 1.7361 37.9862 +#> 150: 86.8647 -3.1903 4.8798 1.7995 39.6906 +#> 151: 86.4913 -3.2101 4.6358 1.7618 39.2462 +#> 152: 86.4667 -3.2254 4.6929 1.7762 38.0665 +#> 153: 86.0176 -3.2241 4.4586 1.7708 37.6367 +#> 154: 85.8680 -3.2359 5.2401 1.7272 37.7322 +#> 155: 85.6560 -3.2147 3.3340 1.7833 38.4605 +#> 156: 85.6927 -3.1987 1.9644 1.8176 39.4958 +#> 157: 86.3686 -3.2294 3.4959 1.6556 39.7058 +#> 158: 86.7614 -3.2051 2.3005 1.6413 40.3968 +#> 159: 86.6393 -3.2243 1.7824 1.6521 40.0846 +#> 160: 86.8686 -3.1850 1.6490 1.7211 39.6362 +#> 161: 86.7853 -3.2071 1.1720 1.6132 39.6921 +#> 162: 86.7337 -3.1825 1.0646 1.5897 41.1027 +#> 163: 86.9192 -3.1365 1.0339 1.6656 40.2410 +#> 164: 86.6652 -3.2052 0.9750 1.5817 40.6189 +#> 165: 86.6154 -3.1870 1.2602 1.6559 40.1832 +#> 166: 86.7300 -3.2096 1.2144 1.6571 39.8989 +#> 167: 86.4536 -3.2135 0.5155 1.7436 39.6313 +#> 168: 86.4848 -3.2315 0.5060 1.6681 39.1479 +#> 169: 86.2641 -3.2444 0.3935 1.6781 40.2903 +#> 170: 86.2482 -3.2628 0.3342 1.6177 40.2600 +#> 171: 86.2833 -3.2338 0.1701 1.6698 39.8946 +#> 172: 86.2155 -3.2175 0.1858 1.6090 39.9709 +#> 173: 86.2916 -3.2313 0.2088 1.6918 41.4421 +#> 174: 86.1920 -3.2050 0.2067 1.7521 40.7724 +#> 175: 86.2771 -3.2071 0.2213 1.5502 40.5055 +#> 176: 86.2589 -3.1867 0.2010 1.5814 40.0963 +#> 177: 86.2740 -3.2209 0.2679 1.6774 40.9479 +#> 178: 86.2210 -3.1896 0.4420 1.5512 40.3238 +#> 179: 86.1769 -3.2036 0.5592 1.6008 40.3873 +#> 180: 85.9366 -3.2046 0.5056 1.6948 41.4254 +#> 181: 85.9173 -3.2167 0.6033 1.6886 39.5784 +#> 182: 85.7077 -3.2508 0.5008 1.7501 40.4224 +#> 183: 85.8084 -3.2743 0.5737 1.7174 40.0576 +#> 184: 85.7776 -3.2518 0.7164 1.7495 39.8748 +#> 185: 85.6192 -3.2378 1.1401 1.7562 39.9841 +#> 186: 85.6951 -3.2460 1.5642 1.7330 39.1282 +#> 187: 85.5281 -3.2309 1.5452 1.7900 38.4833 +#> 188: 85.3476 -3.2018 1.1385 1.8106 39.2842 +#> 189: 85.1914 -3.2180 1.0465 1.7562 40.0715 +#> 190: 85.2759 -3.2275 1.0437 1.7160 39.9928 +#> 191: 85.3630 -3.2728 1.5672 1.7394 39.4749 +#> 192: 85.1334 -3.2467 0.9598 1.6243 39.7385 +#> 193: 84.9313 -3.2401 0.6441 1.6518 39.5447 +#> 194: 84.9097 -3.2361 0.4275 1.6509 40.3383 +#> 195: 84.9131 -3.2241 0.3344 1.5868 39.1438 +#> 196: 84.9117 -3.2419 0.2435 1.6882 40.1132 +#> 197: 84.9569 -3.2776 0.2352 1.6351 40.1070 +#> 198: 84.9113 -3.2334 0.2133 1.6282 39.9988 +#> 199: 84.9028 -3.2637 0.1859 1.6127 38.8695 +#> 200: 84.9020 -3.2456 0.2429 1.6172 40.2644 +#> 201: 84.9327 -3.2292 0.1787 1.6720 40.5826 +#> 202: 84.9313 -3.2363 0.1487 1.6641 40.1952 +#> 203: 84.9208 -3.2350 0.1445 1.6449 40.0176 +#> 204: 84.9312 -3.2296 0.1488 1.6292 40.1353 +#> 205: 84.9302 -3.2277 0.1454 1.6167 40.4137 +#> 206: 84.9378 -3.2314 0.1474 1.6263 40.2241 +#> 207: 84.9190 -3.2369 0.1454 1.6374 40.1459 +#> 208: 84.9085 -3.2385 0.1527 1.6439 40.1931 +#> 209: 84.8920 -3.2411 0.1566 1.6396 40.1558 +#> 210: 84.8787 -3.2435 0.1574 1.6381 40.1872 +#> 211: 84.8784 -3.2460 0.1528 1.6407 40.1825 +#> 212: 84.8745 -3.2469 0.1474 1.6439 40.0865 +#> 213: 84.8702 -3.2474 0.1429 1.6459 40.0164 +#> 214: 84.8592 -3.2476 0.1421 1.6506 39.9852 +#> 215: 84.8558 -3.2479 0.1389 1.6549 39.9882 +#> 216: 84.8542 -3.2488 0.1365 1.6625 39.9461 +#> 217: 84.8594 -3.2488 0.1354 1.6691 39.9751 +#> 218: 84.8634 -3.2487 0.1335 1.6751 39.9844 +#> 219: 84.8653 -3.2485 0.1298 1.6759 39.9263 +#> 220: 84.8722 -3.2496 0.1267 1.6748 39.8897 +#> 221: 84.8782 -3.2496 0.1267 1.6757 39.8504 +#> 222: 84.8772 -3.2483 0.1278 1.6761 39.8406 +#> 223: 84.8765 -3.2490 0.1296 1.6785 39.8138 +#> 224: 84.8750 -3.2492 0.1274 1.6772 39.8278 +#> 225: 84.8767 -3.2493 0.1266 1.6727 39.8642 +#> 226: 84.8741 -3.2495 0.1251 1.6711 39.8208 +#> 227: 84.8678 -3.2502 0.1234 1.6680 39.8193 +#> 228: 84.8618 -3.2509 0.1217 1.6660 39.7846 +#> 229: 84.8567 -3.2504 0.1208 1.6640 39.7538 +#> 230: 84.8559 -3.2503 0.1215 1.6624 39.7184 +#> 231: 84.8548 -3.2501 0.1203 1.6596 39.6840 +#> 232: 84.8528 -3.2505 0.1206 1.6550 39.6882 +#> 233: 84.8510 -3.2499 0.1229 1.6560 39.7083 +#> 234: 84.8479 -3.2502 0.1243 1.6568 39.7116 +#> 235: 84.8443 -3.2509 0.1244 1.6571 39.7504 +#> 236: 84.8391 -3.2515 0.1253 1.6584 39.7761 +#> 237: 84.8390 -3.2522 0.1246 1.6595 39.8188 +#> 238: 84.8433 -3.2520 0.1240 1.6606 39.8393 +#> 239: 84.8453 -3.2517 0.1233 1.6604 39.8360 +#> 240: 84.8439 -3.2519 0.1225 1.6597 39.8355 +#> 241: 84.8423 -3.2516 0.1215 1.6591 39.8154 +#> 242: 84.8403 -3.2521 0.1208 1.6572 39.7956 +#> 243: 84.8378 -3.2514 0.1199 1.6579 39.7842 +#> 244: 84.8375 -3.2501 0.1191 1.6582 39.7851 +#> 245: 84.8367 -3.2497 0.1200 1.6571 39.7873 +#> 246: 84.8348 -3.2499 0.1200 1.6561 39.7972 +#> 247: 84.8344 -3.2490 0.1196 1.6546 39.8425 +#> 248: 84.8320 -3.2485 0.1197 1.6551 39.8607 +#> 249: 84.8330 -3.2477 0.1212 1.6550 39.8643 +#> 250: 84.8348 -3.2481 0.1217 1.6561 39.8570 +#> 251: 84.8384 -3.2483 0.1214 1.6569 39.8535 +#> 252: 84.8394 -3.2487 0.1218 1.6578 39.8584 +#> 253: 84.8408 -3.2490 0.1229 1.6586 39.9146 +#> 254: 84.8414 -3.2497 0.1232 1.6602 39.9561 +#> 255: 84.8424 -3.2502 0.1229 1.6617 39.9734 +#> 256: 84.8428 -3.2506 0.1230 1.6609 39.9959 +#> 257: 84.8425 -3.2507 0.1221 1.6600 40.0029 +#> 258: 84.8420 -3.2513 0.1213 1.6585 40.0135 +#> 259: 84.8411 -3.2512 0.1212 1.6576 40.0261 +#> 260: 84.8404 -3.2513 0.1219 1.6562 40.0238 +#> 261: 84.8382 -3.2514 0.1226 1.6553 40.0140 +#> 262: 84.8358 -3.2511 0.1226 1.6547 40.0022 +#> 263: 84.8337 -3.2513 0.1224 1.6539 40.0037 +#> 264: 84.8318 -3.2511 0.1223 1.6531 39.9986 +#> 265: 84.8316 -3.2504 0.1213 1.6533 40.0094 +#> 266: 84.8325 -3.2503 0.1202 1.6549 40.0179 +#> 267: 84.8328 -3.2501 0.1189 1.6547 40.0438 +#> 268: 84.8324 -3.2505 0.1183 1.6532 40.0734 +#> 269: 84.8315 -3.2505 0.1177 1.6545 40.0714 +#> 270: 84.8304 -3.2508 0.1175 1.6545 40.0698 +#> 271: 84.8293 -3.2512 0.1173 1.6542 40.0623 +#> 272: 84.8279 -3.2512 0.1165 1.6537 40.0659 +#> 273: 84.8260 -3.2512 0.1171 1.6536 40.0580 +#> 274: 84.8241 -3.2512 0.1172 1.6523 40.0540 +#> 275: 84.8245 -3.2508 0.1171 1.6529 40.0513 +#> 276: 84.8240 -3.2510 0.1165 1.6523 40.0407 +#> 277: 84.8240 -3.2509 0.1160 1.6516 40.0290 +#> 278: 84.8250 -3.2507 0.1156 1.6505 40.0255 +#> 279: 84.8253 -3.2507 0.1147 1.6509 40.0301 +#> 280: 84.8252 -3.2507 0.1140 1.6503 40.0278 +#> 281: 84.8255 -3.2508 0.1135 1.6504 40.0238 +#> 282: 84.8246 -3.2506 0.1128 1.6505 40.0212 +#> 283: 84.8237 -3.2508 0.1120 1.6509 40.0206 +#> 284: 84.8235 -3.2507 0.1121 1.6518 40.0316 +#> 285: 84.8236 -3.2499 0.1121 1.6523 40.0330 +#> 286: 84.8230 -3.2490 0.1118 1.6530 40.0435 +#> 287: 84.8222 -3.2485 0.1119 1.6526 40.0428 +#> 288: 84.8211 -3.2486 0.1120 1.6512 40.0446 +#> 289: 84.8196 -3.2490 0.1121 1.6508 40.0355 +#> 290: 84.8189 -3.2494 0.1121 1.6503 40.0319 +#> 291: 84.8183 -3.2495 0.1126 1.6501 40.0263 +#> 292: 84.8174 -3.2496 0.1127 1.6495 40.0226 +#> 293: 84.8163 -3.2499 0.1126 1.6488 40.0255 +#> 294: 84.8165 -3.2499 0.1125 1.6479 40.0207 +#> 295: 84.8165 -3.2502 0.1130 1.6466 40.0406 +#> 296: 84.8158 -3.2508 0.1131 1.6464 40.0428 +#> 297: 84.8162 -3.2506 0.1129 1.6465 40.0432 +#> 298: 84.8166 -3.2501 0.1131 1.6460 40.0415 +#> 299: 84.8184 -3.2499 0.1138 1.6451 40.0513 +#> 300: 84.8205 -3.2499 0.1144 1.6450 40.0615 +#> 301: 84.8216 -3.2496 0.1156 1.6450 40.0591 +#> 302: 84.8225 -3.2498 0.1161 1.6448 40.0618 +#> 303: 84.8232 -3.2493 0.1163 1.6451 40.0612 +#> 304: 84.8233 -3.2488 0.1166 1.6450 40.0669 +#> 305: 84.8230 -3.2485 0.1163 1.6439 40.0714 +#> 306: 84.8221 -3.2482 0.1158 1.6440 40.0838 +#> 307: 84.8217 -3.2479 0.1154 1.6445 40.0835 +#> 308: 84.8219 -3.2477 0.1156 1.6450 40.0829 +#> 309: 84.8224 -3.2477 0.1152 1.6450 40.0836 +#> 310: 84.8224 -3.2480 0.1148 1.6457 40.0873 +#> 311: 84.8225 -3.2480 0.1143 1.6459 40.0894 +#> 312: 84.8219 -3.2482 0.1136 1.6460 40.0835 +#> 313: 84.8214 -3.2484 0.1131 1.6462 40.0810 +#> 314: 84.8208 -3.2485 0.1130 1.6471 40.0786 +#> 315: 84.8211 -3.2485 0.1128 1.6470 40.0707 +#> 316: 84.8211 -3.2483 0.1127 1.6469 40.0628 +#> 317: 84.8210 -3.2482 0.1124 1.6472 40.0580 +#> 318: 84.8201 -3.2484 0.1122 1.6472 40.0602 +#> 319: 84.8196 -3.2484 0.1117 1.6479 40.0555 +#> 320: 84.8183 -3.2480 0.1119 1.6486 40.0659 +#> 321: 84.8173 -3.2479 0.1122 1.6489 40.0713 +#> 322: 84.8164 -3.2479 0.1129 1.6491 40.0781 +#> 323: 84.8159 -3.2480 0.1136 1.6489 40.0790 +#> 324: 84.8158 -3.2480 0.1140 1.6489 40.0746 +#> 325: 84.8158 -3.2480 0.1138 1.6484 40.0845 +#> 326: 84.8157 -3.2482 0.1137 1.6482 40.0953 +#> 327: 84.8155 -3.2482 0.1134 1.6482 40.0955 +#> 328: 84.8156 -3.2482 0.1133 1.6471 40.1167 +#> 329: 84.8152 -3.2483 0.1129 1.6466 40.1195 +#> 330: 84.8152 -3.2482 0.1124 1.6459 40.1280 +#> 331: 84.8151 -3.2478 0.1120 1.6467 40.1282 +#> 332: 84.8147 -3.2477 0.1115 1.6471 40.1265 +#> 333: 84.8145 -3.2477 0.1110 1.6470 40.1333 +#> 334: 84.8144 -3.2479 0.1108 1.6468 40.1474 +#> 335: 84.8141 -3.2481 0.1106 1.6475 40.1549 +#> 336: 84.8135 -3.2481 0.1103 1.6481 40.1664 +#> 337: 84.8134 -3.2481 0.1106 1.6476 40.1837 +#> 338: 84.8129 -3.2479 0.1109 1.6482 40.1855 +#> 339: 84.8126 -3.2478 0.1107 1.6478 40.1830 +#> 340: 84.8120 -3.2482 0.1106 1.6471 40.1893 +#> 341: 84.8120 -3.2482 0.1106 1.6467 40.1931 +#> 342: 84.8119 -3.2482 0.1106 1.6473 40.2091 +#> 343: 84.8135 -3.2483 0.1109 1.6475 40.2113 +#> 344: 84.8153 -3.2483 0.1114 1.6472 40.2116 +#> 345: 84.8165 -3.2484 0.1119 1.6465 40.2110 +#> 346: 84.8171 -3.2481 0.1121 1.6462 40.2099 +#> 347: 84.8184 -3.2483 0.1126 1.6459 40.2120 +#> 348: 84.8189 -3.2483 0.1127 1.6455 40.2115 +#> 349: 84.8198 -3.2483 0.1127 1.6450 40.2087 +#> 350: 84.8202 -3.2482 0.1125 1.6454 40.2118 +#> 351: 84.8208 -3.2483 0.1120 1.6447 40.2094 +#> 352: 84.8213 -3.2483 0.1118 1.6444 40.2070 +#> 353: 84.8218 -3.2481 0.1115 1.6445 40.2077 +#> 354: 84.8226 -3.2482 0.1114 1.6439 40.2077 +#> 355: 84.8230 -3.2481 0.1113 1.6439 40.2072 +#> 356: 84.8232 -3.2479 0.1111 1.6439 40.2075 +#> 357: 84.8239 -3.2477 0.1109 1.6441 40.2021 +#> 358: 84.8245 -3.2476 0.1107 1.6445 40.2028 +#> 359: 84.8251 -3.2476 0.1107 1.6452 40.2032 +#> 360: 84.8252 -3.2474 0.1110 1.6462 40.2012 +#> 361: 84.8258 -3.2473 0.1108 1.6469 40.2043 +#> 362: 84.8260 -3.2475 0.1107 1.6467 40.2056 +#> 363: 84.8262 -3.2474 0.1106 1.6469 40.2028 +#> 364: 84.8266 -3.2472 0.1104 1.6473 40.1979 +#> 365: 84.8270 -3.2469 0.1102 1.6479 40.1923 +#> 366: 84.8273 -3.2469 0.1100 1.6482 40.1872 +#> 367: 84.8267 -3.2468 0.1099 1.6483 40.1836 +#> 368: 84.8263 -3.2470 0.1099 1.6483 40.1850 +#> 369: 84.8269 -3.2471 0.1098 1.6484 40.1864 +#> 370: 84.8274 -3.2472 0.1098 1.6484 40.1856 +#> 371: 84.8282 -3.2471 0.1101 1.6489 40.1839 +#> 372: 84.8288 -3.2469 0.1099 1.6492 40.1804 +#> 373: 84.8294 -3.2467 0.1098 1.6494 40.1806 +#> 374: 84.8301 -3.2466 0.1096 1.6491 40.1855 +#> 375: 84.8301 -3.2467 0.1093 1.6488 40.1951 +#> 376: 84.8302 -3.2467 0.1092 1.6484 40.1921 +#> 377: 84.8302 -3.2467 0.1092 1.6486 40.1842 +#> 378: 84.8300 -3.2467 0.1095 1.6485 40.1760 +#> 379: 84.8296 -3.2468 0.1094 1.6483 40.1701 +#> 380: 84.8297 -3.2469 0.1094 1.6483 40.1738 +#> 381: 84.8299 -3.2469 0.1093 1.6485 40.1801 +#> 382: 84.8302 -3.2470 0.1092 1.6488 40.1857 +#> 383: 84.8299 -3.2469 0.1090 1.6491 40.1859 +#> 384: 84.8297 -3.2470 0.1090 1.6488 40.1903 +#> 385: 84.8289 -3.2469 0.1095 1.6487 40.1978 +#> 386: 84.8282 -3.2470 0.1098 1.6487 40.1976 +#> 387: 84.8277 -3.2471 0.1101 1.6488 40.1910 +#> 388: 84.8270 -3.2471 0.1104 1.6486 40.1863 +#> 389: 84.8263 -3.2471 0.1108 1.6486 40.1837 +#> 390: 84.8259 -3.2472 0.1109 1.6491 40.1881 +#> 391: 84.8250 -3.2472 0.1111 1.6499 40.1919 +#> 392: 84.8248 -3.2471 0.1113 1.6501 40.1961 +#> 393: 84.8247 -3.2471 0.1113 1.6503 40.1941 +#> 394: 84.8241 -3.2470 0.1114 1.6508 40.1933 +#> 395: 84.8239 -3.2469 0.1115 1.6510 40.1916 +#> 396: 84.8239 -3.2468 0.1115 1.6515 40.1946 +#> 397: 84.8239 -3.2466 0.1113 1.6517 40.1979 +#> 398: 84.8241 -3.2467 0.1112 1.6519 40.1966 +#> 399: 84.8244 -3.2466 0.1112 1.6522 40.1975 +#> 400: 84.8248 -3.2466 0.1111 1.6523 40.1919 +#> 401: 84.8255 -3.2466 0.1109 1.6523 40.1889 +#> 402: 84.8259 -3.2468 0.1108 1.6523 40.1836 +#> 403: 84.8257 -3.2470 0.1109 1.6524 40.1787 +#> 404: 84.8251 -3.2470 0.1111 1.6528 40.1788 +#> 405: 84.8244 -3.2472 0.1113 1.6530 40.1761 +#> 406: 84.8235 -3.2472 0.1113 1.6529 40.1763 +#> 407: 84.8231 -3.2471 0.1112 1.6531 40.1742 +#> 408: 84.8229 -3.2471 0.1110 1.6530 40.1728 +#> 409: 84.8229 -3.2471 0.1109 1.6528 40.1698 +#> 410: 84.8233 -3.2473 0.1109 1.6524 40.1701 +#> 411: 84.8235 -3.2474 0.1109 1.6522 40.1714 +#> 412: 84.8236 -3.2474 0.1110 1.6517 40.1716 +#> 413: 84.8241 -3.2474 0.1111 1.6512 40.1741 +#> 414: 84.8238 -3.2476 0.1108 1.6508 40.1809 +#> 415: 84.8238 -3.2477 0.1108 1.6505 40.1803 +#> 416: 84.8234 -3.2475 0.1110 1.6504 40.1880 +#> 417: 84.8232 -3.2475 0.1112 1.6510 40.1938 +#> 418: 84.8232 -3.2475 0.1112 1.6511 40.1944 +#> 419: 84.8231 -3.2476 0.1114 1.6513 40.1921 +#> 420: 84.8226 -3.2477 0.1113 1.6511 40.1880 +#> 421: 84.8220 -3.2478 0.1111 1.6508 40.1859 +#> 422: 84.8213 -3.2478 0.1110 1.6503 40.1897 +#> 423: 84.8207 -3.2479 0.1110 1.6499 40.1876 +#> 424: 84.8203 -3.2479 0.1111 1.6498 40.1860 +#> 425: 84.8198 -3.2479 0.1111 1.6498 40.1817 +#> 426: 84.8191 -3.2479 0.1113 1.6498 40.1796 +#> 427: 84.8186 -3.2478 0.1112 1.6498 40.1781 +#> 428: 84.8183 -3.2478 0.1114 1.6496 40.1738 +#> 429: 84.8177 -3.2477 0.1116 1.6495 40.1695 +#> 430: 84.8172 -3.2477 0.1119 1.6496 40.1739 +#> 431: 84.8169 -3.2478 0.1120 1.6494 40.1741 +#> 432: 84.8169 -3.2479 0.1121 1.6490 40.1758 +#> 433: 84.8170 -3.2479 0.1121 1.6491 40.1793 +#> 434: 84.8171 -3.2480 0.1122 1.6488 40.1808 +#> 435: 84.8173 -3.2481 0.1123 1.6487 40.1845 +#> 436: 84.8176 -3.2481 0.1123 1.6489 40.1866 +#> 437: 84.8178 -3.2480 0.1122 1.6496 40.1872 +#> 438: 84.8183 -3.2480 0.1121 1.6502 40.1869 +#> 439: 84.8185 -3.2481 0.1119 1.6504 40.1834 +#> 440: 84.8185 -3.2480 0.1118 1.6506 40.1831 +#> 441: 84.8188 -3.2480 0.1120 1.6502 40.1893 +#> 442: 84.8192 -3.2480 0.1120 1.6501 40.1930 +#> 443: 84.8196 -3.2480 0.1120 1.6499 40.1917 +#> 444: 84.8202 -3.2478 0.1122 1.6498 40.1966 +#> 445: 84.8207 -3.2476 0.1124 1.6499 40.1977 +#> 446: 84.8210 -3.2473 0.1123 1.6496 40.2017 +#> 447: 84.8217 -3.2472 0.1123 1.6491 40.2030 +#> 448: 84.8221 -3.2473 0.1122 1.6488 40.2025 +#> 449: 84.8225 -3.2474 0.1121 1.6485 40.2069 +#> 450: 84.8224 -3.2473 0.1119 1.6484 40.2078 +#> 451: 84.8221 -3.2473 0.1118 1.6483 40.2032 +#> 452: 84.8220 -3.2472 0.1117 1.6484 40.1989 +#> 453: 84.8220 -3.2472 0.1117 1.6483 40.1953 +#> 454: 84.8220 -3.2473 0.1122 1.6483 40.1942 +#> 455: 84.8220 -3.2472 0.1124 1.6484 40.1932 +#> 456: 84.8220 -3.2470 0.1124 1.6478 40.1972 +#> 457: 84.8222 -3.2469 0.1125 1.6476 40.1989 +#> 458: 84.8226 -3.2468 0.1125 1.6479 40.1989 +#> 459: 84.8228 -3.2467 0.1126 1.6480 40.2035 +#> 460: 84.8231 -3.2467 0.1124 1.6479 40.2032 +#> 461: 84.8236 -3.2466 0.1126 1.6482 40.2030 +#> 462: 84.8238 -3.2466 0.1124 1.6481 40.2052 +#> 463: 84.8238 -3.2467 0.1123 1.6479 40.2023 +#> 464: 84.8233 -3.2467 0.1123 1.6479 40.2004 +#> 465: 84.8230 -3.2468 0.1123 1.6482 40.2043 +#> 466: 84.8233 -3.2469 0.1123 1.6480 40.2062 +#> 467: 84.8236 -3.2468 0.1121 1.6480 40.2026 +#> 468: 84.8238 -3.2468 0.1120 1.6477 40.2034 +#> 469: 84.8239 -3.2468 0.1119 1.6474 40.2035 +#> 470: 84.8241 -3.2469 0.1116 1.6473 40.2015 +#> 471: 84.8241 -3.2470 0.1116 1.6476 40.1993 +#> 472: 84.8240 -3.2469 0.1117 1.6478 40.1977 +#> 473: 84.8239 -3.2468 0.1119 1.6479 40.1949 +#> 474: 84.8239 -3.2466 0.1118 1.6480 40.1946 +#> 475: 84.8239 -3.2464 0.1119 1.6483 40.1941 +#> 476: 84.8237 -3.2462 0.1121 1.6488 40.1930 +#> 477: 84.8235 -3.2462 0.1122 1.6488 40.1901 +#> 478: 84.8235 -3.2462 0.1125 1.6488 40.1837 +#> 479: 84.8238 -3.2463 0.1128 1.6486 40.1814 +#> 480: 84.8238 -3.2464 0.1129 1.6484 40.1794 +#> 481: 84.8239 -3.2464 0.1129 1.6483 40.1783 +#> 482: 84.8237 -3.2465 0.1130 1.6482 40.1784 +#> 483: 84.8234 -3.2465 0.1130 1.6483 40.1764 +#> 484: 84.8227 -3.2465 0.1132 1.6482 40.1775 +#> 485: 84.8223 -3.2465 0.1133 1.6483 40.1764 +#> 486: 84.8219 -3.2465 0.1135 1.6484 40.1781 +#> 487: 84.8215 -3.2465 0.1136 1.6487 40.1770 +#> 488: 84.8214 -3.2466 0.1136 1.6486 40.1796 +#> 489: 84.8214 -3.2466 0.1134 1.6489 40.1801 +#> 490: 84.8214 -3.2466 0.1132 1.6490 40.1786 +#> 491: 84.8218 -3.2466 0.1131 1.6494 40.1805 +#> 492: 84.8220 -3.2465 0.1133 1.6495 40.1805 +#> 493: 84.8223 -3.2465 0.1137 1.6493 40.1791 +#> 494: 84.8223 -3.2465 0.1140 1.6494 40.1774 +#> 495: 84.8224 -3.2465 0.1142 1.6491 40.1764 +#> 496: 84.8225 -3.2465 0.1142 1.6491 40.1750 +#> 497: 84.8229 -3.2465 0.1142 1.6487 40.1742 +#> 498: 84.8230 -3.2466 0.1140 1.6485 40.1712 +#> 499: 84.8229 -3.2466 0.1137 1.6485 40.1688 +#> 500: 84.8228 -3.2468 0.1134 1.6488 40.1690</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='input'><span class='va'>f_nlmixr_sfo_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | parent_0 |log_k_parent | sigma | o1 | +#> <span style='text-decoration: underline;'>|.....................| o2 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 1</span>| 451.22394 | 1.000 | -1.000 | -0.7995 | -0.9125 | +#> <span style='text-decoration: underline;'>|.....................| -0.9081 |...........|...........|...........|</span> +#> | U| 451.22394 | 86.39 | -3.215 | 5.768 | 0.7049 | +#> <span style='text-decoration: underline;'>|.....................| 0.9021 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 451.22394</span> | 86.39 | 0.04015 | 5.768 | 0.7049 | +#> <span style='text-decoration: underline;'>|.....................| 0.9021 |...........|...........|...........|</span> +#> | G| Gill Diff. | 52.79 | 0.01520 | -15.05 | 0.6163 | +#> <span style='text-decoration: underline;'>|.....................| 2.488 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 2</span>| 3099.6543 | 0.03939 | -1.000 | -0.5255 | -0.9237 | +#> <span style='text-decoration: underline;'>|.....................| -0.9534 |...........|...........|...........|</span> +#> | U| 3099.6543 | 3.403 | -3.215 | 6.558 | 0.6970 | +#> <span style='text-decoration: underline;'>|.....................| 0.8613 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 3099.6543</span> | 3.403 | 0.04014 | 6.558 | 0.6970 | +#> <span style='text-decoration: underline;'>|.....................| 0.8613 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 3</span>| 473.10068 | 0.9039 | -1.000 | -0.7721 | -0.9136 | +#> <span style='text-decoration: underline;'>|.....................| -0.9126 |...........|...........|...........|</span> +#> | U| 473.10068 | 78.09 | -3.215 | 5.847 | 0.7041 | +#> <span style='text-decoration: underline;'>|.....................| 0.8980 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 473.10068</span> | 78.09 | 0.04015 | 5.847 | 0.7041 | +#> <span style='text-decoration: underline;'>|.....................| 0.8980 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 4</span>| 450.95086 | 0.9904 | -1.000 | -0.7967 | -0.9126 | +#> <span style='text-decoration: underline;'>|.....................| -0.9086 |...........|...........|...........|</span> +#> | U| 450.95086 | 85.56 | -3.215 | 5.776 | 0.7048 | +#> <span style='text-decoration: underline;'>|.....................| 0.9017 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 450.95086</span> | 85.56 | 0.04015 | 5.776 | 0.7048 | +#> <span style='text-decoration: underline;'>|.....................| 0.9017 |...........|...........|...........|</span> +#> | F| Forward Diff. | -4.520 | 0.09729 | -14.85 | -0.2941 | +#> <span style='text-decoration: underline;'>|.....................| 2.449 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 5</span>| 450.82239 | 0.9932 | -1.000 | -0.7873 | -0.9124 | +#> <span style='text-decoration: underline;'>|.....................| -0.9101 |...........|...........|...........|</span> +#> | U| 450.82239 | 85.81 | -3.215 | 5.804 | 0.7049 | +#> <span style='text-decoration: underline;'>|.....................| 0.9003 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 450.82239</span> | 85.81 | 0.04015 | 5.804 | 0.7049 | +#> <span style='text-decoration: underline;'>|.....................| 0.9003 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 6</span>| 450.73959 | 0.9981 | -1.000 | -0.7712 | -0.9121 | +#> <span style='text-decoration: underline;'>|.....................| -0.9128 |...........|...........|...........|</span> +#> | U| 450.73959 | 86.23 | -3.215 | 5.850 | 0.7051 | +#> <span style='text-decoration: underline;'>|.....................| 0.8979 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 450.73959</span> | 86.23 | 0.04015 | 5.850 | 0.7051 | +#> <span style='text-decoration: underline;'>|.....................| 0.8979 |...........|...........|...........|</span> +#> | F| Forward Diff. | 41.55 | 0.02901 | -12.22 | 0.2553 | +#> <span style='text-decoration: underline;'>|.....................| 2.069 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 7</span>| 450.34694 | 0.9875 | -1.000 | -0.7467 | -0.9114 | +#> <span style='text-decoration: underline;'>|.....................| -0.9169 |...........|...........|...........|</span> +#> | U| 450.34694 | 85.32 | -3.215 | 5.921 | 0.7056 | +#> <span style='text-decoration: underline;'>|.....................| 0.8942 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 450.34694</span> | 85.32 | 0.04014 | 5.921 | 0.7056 | +#> <span style='text-decoration: underline;'>|.....................| 0.8942 |...........|...........|...........|</span> +#> | F| Forward Diff. | -19.58 | 0.1161 | -10.02 | -0.6042 | +#> <span style='text-decoration: underline;'>|.....................| 1.700 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 8</span>| 450.09191 | 0.9931 | -1.001 | -0.7208 | -0.9093 | +#> <span style='text-decoration: underline;'>|.....................| -0.9217 |...........|...........|...........|</span> +#> | U| 450.09191 | 85.80 | -3.216 | 5.995 | 0.7071 | +#> <span style='text-decoration: underline;'>|.....................| 0.8899 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 450.09191</span> | 85.80 | 0.04012 | 5.995 | 0.7071 | +#> <span style='text-decoration: underline;'>|.....................| 0.8899 |...........|...........|...........|</span> +#> | F| Forward Diff. | 13.00 | 0.06566 | -7.570 | -0.3896 | +#> <span style='text-decoration: underline;'>|.....................| 1.273 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 9</span>| 449.93949 | 0.9873 | -1.002 | -0.6965 | -0.8998 | +#> <span style='text-decoration: underline;'>|.....................| -0.9259 |...........|...........|...........|</span> +#> | U| 449.93949 | 85.30 | -3.217 | 6.065 | 0.7138 | +#> <span style='text-decoration: underline;'>|.....................| 0.8861 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.93949</span> | 85.30 | 0.04009 | 6.065 | 0.7138 | +#> <span style='text-decoration: underline;'>|.....................| 0.8861 |...........|...........|...........|</span> +#> | F| Forward Diff. | -18.86 | 0.1073 | -5.670 | -0.6860 | +#> <span style='text-decoration: underline;'>|.....................| 0.8878 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 10</span>| 449.82026 | 0.9918 | -1.004 | -0.6799 | -0.8791 | +#> <span style='text-decoration: underline;'>|.....................| -0.9254 |...........|...........|...........|</span> +#> | U| 449.82026 | 85.69 | -3.219 | 6.113 | 0.7284 | +#> <span style='text-decoration: underline;'>|.....................| 0.8865 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.82026</span> | 85.69 | 0.04000 | 6.113 | 0.7284 | +#> <span style='text-decoration: underline;'>|.....................| 0.8865 |...........|...........|...........|</span> +#> | F| Forward Diff. | 8.164 | 0.05669 | -4.296 | -0.3775 | +#> <span style='text-decoration: underline;'>|.....................| 0.8823 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 11</span>| 449.76996 | 0.9897 | -1.006 | -0.6720 | -0.8560 | +#> <span style='text-decoration: underline;'>|.....................| -0.9364 |...........|...........|...........|</span> +#> | U| 449.76996 | 85.50 | -3.221 | 6.136 | 0.7447 | +#> <span style='text-decoration: underline;'>|.....................| 0.8766 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.76996</span> | 85.50 | 0.03990 | 6.136 | 0.7447 | +#> <span style='text-decoration: underline;'>|.....................| 0.8766 |...........|...........|...........|</span> +#> | F| Forward Diff. | -2.743 | 0.05613 | -3.782 | -0.3486 | +#> <span style='text-decoration: underline;'>|.....................| -0.07732 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 12</span>| 449.73800 | 0.9901 | -1.008 | -0.6600 | -0.8416 | +#> <span style='text-decoration: underline;'>|.....................| -0.9169 |...........|...........|...........|</span> +#> | U| 449.738 | 85.54 | -3.223 | 6.170 | 0.7549 | +#> <span style='text-decoration: underline;'>|.....................| 0.8942 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.738</span> | 85.54 | 0.03983 | 6.170 | 0.7549 | +#> <span style='text-decoration: underline;'>|.....................| 0.8942 |...........|...........|...........|</span> +#> | F| Forward Diff. | 0.5907 | 0.04688 | -2.910 | -0.3174 | +#> <span style='text-decoration: underline;'>|.....................| 1.529 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 13</span>| 449.73838 | 0.9854 | -1.008 | -0.6366 | -0.8390 | +#> <span style='text-decoration: underline;'>|.....................| -0.9292 |...........|...........|...........|</span> +#> | U| 449.73838 | 85.13 | -3.224 | 6.238 | 0.7567 | +#> <span style='text-decoration: underline;'>|.....................| 0.8831 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.73838</span> | 85.13 | 0.03981 | 6.238 | 0.7567 | +#> <span style='text-decoration: underline;'>|.....................| 0.8831 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 14</span>| 449.71577 | 0.9877 | -1.008 | -0.6484 | -0.8403 | +#> <span style='text-decoration: underline;'>|.....................| -0.9231 |...........|...........|...........|</span> +#> | U| 449.71577 | 85.33 | -3.223 | 6.204 | 0.7558 | +#> <span style='text-decoration: underline;'>|.....................| 0.8886 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.71577</span> | 85.33 | 0.03982 | 6.204 | 0.7558 | +#> <span style='text-decoration: underline;'>|.....................| 0.8886 |...........|...........|...........|</span> +#> | F| Forward Diff. | -13.00 | 0.06593 | -2.084 | -0.4341 | +#> <span style='text-decoration: underline;'>|.....................| 1.007 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 15</span>| 449.68436 | 0.9912 | -1.009 | -0.6401 | -0.8344 | +#> <span style='text-decoration: underline;'>|.....................| -0.9311 |...........|...........|...........|</span> +#> | U| 449.68436 | 85.64 | -3.224 | 6.228 | 0.7599 | +#> <span style='text-decoration: underline;'>|.....................| 0.8814 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.68436</span> | 85.64 | 0.03979 | 6.228 | 0.7599 | +#> <span style='text-decoration: underline;'>|.....................| 0.8814 |...........|...........|...........|</span> +#> | F| Forward Diff. | 7.939 | 0.02803 | -1.419 | -0.2659 | +#> <span style='text-decoration: underline;'>|.....................| 0.3125 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 16</span>| 449.66988 | 0.9896 | -1.010 | -0.6363 | -0.8221 | +#> <span style='text-decoration: underline;'>|.....................| -0.9344 |...........|...........|...........|</span> +#> | U| 449.66988 | 85.50 | -3.226 | 6.239 | 0.7686 | +#> <span style='text-decoration: underline;'>|.....................| 0.8784 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.66988</span> | 85.50 | 0.03973 | 6.239 | 0.7686 | +#> <span style='text-decoration: underline;'>|.....................| 0.8784 |...........|...........|...........|</span> +#> | F| Forward Diff. | -0.8695 | 0.03361 | -1.202 | -0.2917 | +#> <span style='text-decoration: underline;'>|.....................| 0.02327 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 17</span>| 449.66421 | 0.9900 | -1.012 | -0.6343 | -0.8088 | +#> <span style='text-decoration: underline;'>|.....................| -0.9351 |...........|...........|...........|</span> +#> | U| 449.66421 | 85.53 | -3.227 | 6.245 | 0.7779 | +#> <span style='text-decoration: underline;'>|.....................| 0.8778 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.66421</span> | 85.53 | 0.03969 | 6.245 | 0.7779 | +#> <span style='text-decoration: underline;'>|.....................| 0.8778 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 18</span>| 449.65407 | 0.9895 | -1.015 | -0.6307 | -0.7728 | +#> <span style='text-decoration: underline;'>|.....................| -0.9370 |...........|...........|...........|</span> +#> | U| 449.65407 | 85.49 | -3.230 | 6.255 | 0.8033 | +#> <span style='text-decoration: underline;'>|.....................| 0.8761 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.65407</span> | 85.49 | 0.03957 | 6.255 | 0.8033 | +#> <span style='text-decoration: underline;'>|.....................| 0.8761 |...........|...........|...........|</span> +#> | F| Forward Diff. | 0.6836 | 0.009868 | -0.9456 | -0.1262 | +#> <span style='text-decoration: underline;'>|.....................| -0.2597 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 19</span>| 449.64227 | 0.9890 | -1.006 | -0.6121 | -0.7274 | +#> <span style='text-decoration: underline;'>|.....................| -0.9339 |...........|...........|...........|</span> +#> | U| 449.64227 | 85.45 | -3.222 | 6.309 | 0.8353 | +#> <span style='text-decoration: underline;'>|.....................| 0.8789 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.64227</span> | 85.45 | 0.03989 | 6.309 | 0.8353 | +#> <span style='text-decoration: underline;'>|.....................| 0.8789 |...........|...........|...........|</span> +#> | F| Forward Diff. | -0.4372 | 0.06357 | 0.2445 | -0.08318 | +#> <span style='text-decoration: underline;'>|.....................| -0.05696 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 20</span>| 449.64227 | 0.9890 | -1.006 | -0.6121 | -0.7274 | +#> <span style='text-decoration: underline;'>|.....................| -0.9339 |...........|...........|...........|</span> +#> | U| 449.64227 | 85.45 | -3.222 | 6.309 | 0.8353 | +#> <span style='text-decoration: underline;'>|.....................| 0.8789 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 449.64227</span> | 85.45 | 0.03989 | 6.309 | 0.8353 | +#> <span style='text-decoration: underline;'>|.....................| 0.8789 |...........|...........|...........|</span> +#> calculating covariance matrix +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate and covariance; see $scaleInfo</span></div><div class='input'> +<span class='va'>f_nlmixr_fomc_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> 1: 93.6754 -0.2977 2.0254 2.7655 0.7032 0.5111 15.3443 +#> 2: 93.8828 -0.2006 2.0786 2.6886 0.6681 0.4855 7.5256 +#> 3: 94.0494 -0.2006 2.0891 2.9975 0.6347 0.4612 7.0501 +#> 4: 94.1641 -0.2446 2.0103 3.6008 0.6029 0.4382 6.2482 +#> 5: 93.8983 -0.2562 1.9851 4.5637 0.5728 0.4163 6.1507 +#> 6: 93.9311 -0.2542 1.9733 5.7516 0.5441 0.3954 6.1445 +#> 7: 93.8631 -0.2535 1.9876 5.4640 0.5169 0.3757 5.9234 +#> 8: 94.2851 -0.2327 1.9851 5.7884 0.4943 0.3569 5.9887 +#> 9: 94.2114 -0.2348 2.0169 5.4990 0.4733 0.3390 5.9730 +#> 10: 94.0782 -0.1951 2.0678 5.2240 0.4969 0.3221 5.7694 +#> 11: 94.0527 -0.1898 2.0988 4.9628 0.4924 0.3060 5.6429 +#> 12: 93.9845 -0.1795 2.1168 4.7147 0.4748 0.2907 5.4764 +#> 13: 93.9424 -0.1958 2.0924 4.4790 0.4551 0.2762 5.5598 +#> 14: 94.2255 -0.2005 2.0963 4.2910 0.4552 0.2623 5.4520 +#> 15: 94.6065 -0.1964 2.0794 4.0765 0.4516 0.2492 5.5275 +#> 16: 94.8393 -0.1872 2.0825 4.7814 0.4714 0.2368 5.4708 +#> 17: 94.5489 -0.1873 2.0822 5.3772 0.4714 0.2249 5.5790 +#> 18: 94.5797 -0.1994 2.0702 5.1083 0.4563 0.2137 5.5962 +#> 19: 94.7205 -0.1987 2.0942 5.1405 0.4580 0.2030 5.8328 +#> 20: 94.2162 -0.1961 2.0955 7.2352 0.4578 0.2081 5.5730 +#> 21: 94.2688 -0.1935 2.0980 6.8735 0.4539 0.2199 5.6561 +#> 22: 94.4008 -0.2294 2.0430 6.5298 0.4312 0.2528 5.4970 +#> 23: 93.8617 -0.2126 2.0861 6.2033 0.4420 0.2401 5.3679 +#> 24: 93.9223 -0.2173 2.0786 5.8931 0.4419 0.2281 5.4475 +#> 25: 94.1259 -0.2199 2.0790 5.5985 0.4429 0.2167 5.2610 +#> 26: 93.5597 -0.1966 2.1115 5.3186 0.4521 0.2059 5.0971 +#> 27: 93.5468 -0.2077 2.1016 5.0526 0.4458 0.2090 5.2223 +#> 28: 93.6901 -0.2106 2.0884 4.8000 0.4439 0.2114 5.1693 +#> 29: 93.4521 -0.1991 2.1349 4.5600 0.4236 0.2248 5.1834 +#> 30: 93.7678 -0.1998 2.1267 5.5252 0.4212 0.2297 5.0549 +#> 31: 93.5695 -0.2039 2.1244 5.2489 0.4165 0.2334 5.0965 +#> 32: 93.8288 -0.1855 2.1392 5.1872 0.4401 0.2286 5.0321 +#> 33: 93.9053 -0.1827 2.1426 4.9278 0.4479 0.2171 5.0706 +#> 34: 94.0876 -0.1871 2.1151 4.6814 0.4613 0.2063 5.1438 +#> 35: 94.5298 -0.1845 2.1221 4.4474 0.4586 0.2006 5.1897 +#> 36: 94.3221 -0.1765 2.1144 5.3164 0.4401 0.2193 5.0921 +#> 37: 94.3600 -0.1842 2.1021 5.3586 0.4507 0.2210 5.0926 +#> 38: 94.3734 -0.1790 2.1261 5.0907 0.4494 0.2100 5.1494 +#> 39: 94.5052 -0.1806 2.1319 4.8362 0.4514 0.1995 5.0177 +#> 40: 94.1042 -0.1906 2.0983 4.5944 0.4360 0.1984 5.2507 +#> 41: 94.1815 -0.1914 2.1166 4.3646 0.4385 0.1977 5.1065 +#> 42: 93.9837 -0.2144 2.0673 4.1464 0.4378 0.1878 5.1603 +#> 43: 93.8806 -0.2107 2.0840 3.9642 0.4456 0.1848 5.0904 +#> 44: 94.1765 -0.2107 2.0722 3.7660 0.4456 0.1881 5.1562 +#> 45: 94.2089 -0.2018 2.0874 3.5777 0.4482 0.1787 5.1219 +#> 46: 93.8851 -0.2111 2.0869 3.9421 0.4462 0.1697 5.0752 +#> 47: 94.1372 -0.2192 2.0731 3.7450 0.4517 0.1733 5.1784 +#> 48: 94.0436 -0.2157 2.0730 3.5578 0.4577 0.1854 5.1957 +#> 49: 93.9915 -0.2122 2.0740 3.3799 0.4450 0.1829 5.1116 +#> 50: 94.0579 -0.2233 2.0633 3.2109 0.4453 0.1964 5.0295 +#> 51: 94.0044 -0.2283 2.0544 3.9314 0.4563 0.2118 5.0457 +#> 52: 94.1080 -0.2174 2.0551 4.8914 0.4548 0.2182 5.0504 +#> 53: 94.3715 -0.2134 2.0598 6.2569 0.4509 0.2162 4.9574 +#> 54: 94.7344 -0.2119 2.0459 5.9440 0.4563 0.2121 5.1069 +#> 55: 94.2730 -0.2055 2.0625 5.6468 0.4758 0.2125 5.2656 +#> 56: 94.0206 -0.2017 2.0715 5.3645 0.4719 0.2045 5.1400 +#> 57: 94.0409 -0.1986 2.0837 5.0963 0.4801 0.2068 5.0902 +#> 58: 94.2392 -0.2122 2.0652 4.8415 0.4560 0.2334 5.1883 +#> 59: 93.9996 -0.1962 2.0764 4.5994 0.4686 0.2417 5.1242 +#> 60: 94.1448 -0.1840 2.1016 4.3694 0.4916 0.2296 5.0867 +#> 61: 94.4861 -0.1840 2.1239 4.3846 0.4916 0.2181 5.3979 +#> 62: 93.9892 -0.1781 2.1083 5.1623 0.5216 0.2072 5.0944 +#> 63: 94.0641 -0.1822 2.1129 4.9628 0.5123 0.1969 5.4228 +#> 64: 94.1414 -0.1733 2.1343 6.7238 0.5220 0.1879 5.3546 +#> 65: 94.0908 -0.1754 2.1160 8.4197 0.5165 0.1852 5.0873 +#> 66: 94.1490 -0.1753 2.1054 7.9987 0.5183 0.1857 5.0777 +#> 67: 93.8958 -0.1613 2.1295 7.5988 0.5004 0.2102 5.0641 +#> 68: 94.0579 -0.1683 2.1511 7.2188 0.5083 0.2110 5.3362 +#> 69: 94.0001 -0.1581 2.1629 6.8579 0.5225 0.2272 5.4399 +#> 70: 93.9712 -0.1733 2.1393 6.5150 0.5153 0.2403 5.5011 +#> 71: 94.3143 -0.1758 2.0989 6.1893 0.5043 0.2713 5.5366 +#> 72: 94.2138 -0.1842 2.1003 5.8798 0.5130 0.2578 5.2964 +#> 73: 94.1742 -0.1951 2.0773 5.5858 0.5165 0.2449 5.1986 +#> 74: 94.1287 -0.2003 2.0606 5.3065 0.5115 0.2326 4.8815 +#> 75: 94.4113 -0.1918 2.0811 5.6717 0.5153 0.2210 4.8370 +#> 76: 94.5175 -0.1940 2.0773 5.3881 0.5127 0.2127 4.9333 +#> 77: 94.4157 -0.1882 2.0714 5.1187 0.5189 0.2021 5.0162 +#> 78: 94.6190 -0.2000 2.0529 4.8628 0.5057 0.2064 4.9436 +#> 79: 94.8081 -0.2006 2.0458 4.6196 0.5053 0.2177 5.0159 +#> 80: 94.7817 -0.1943 2.0547 4.3886 0.5076 0.2099 5.1427 +#> 81: 94.5410 -0.1990 2.0686 4.8770 0.5032 0.2092 5.1192 +#> 82: 94.9536 -0.1936 2.0879 6.9870 0.4781 0.2068 5.1053 +#> 83: 94.7923 -0.1936 2.0777 6.6377 0.4734 0.2120 5.1233 +#> 84: 94.9314 -0.1881 2.0981 6.3058 0.4701 0.2088 5.2821 +#> 85: 94.8024 -0.1866 2.0975 5.9905 0.4684 0.2150 5.2088 +#> 86: 94.6506 -0.2019 2.0677 5.6910 0.4510 0.2043 5.2488 +#> 87: 94.9460 -0.1868 2.0823 5.4064 0.4625 0.2089 5.2663 +#> 88: 94.6365 -0.1901 2.0791 5.3471 0.4509 0.2203 5.2214 +#> 89: 94.5943 -0.2135 2.0521 5.0798 0.4585 0.2093 5.0161 +#> 90: 94.7957 -0.2131 2.0545 4.8258 0.4502 0.2026 5.1344 +#> 91: 94.6308 -0.2096 2.0565 4.5845 0.4566 0.2108 5.0403 +#> 92: 94.3521 -0.2059 2.0557 4.3553 0.4925 0.2072 5.3715 +#> 93: 94.5188 -0.2130 2.0646 4.1375 0.4980 0.1996 5.5624 +#> 94: 94.5995 -0.2056 2.0593 3.9306 0.4995 0.2167 5.3581 +#> 95: 94.7276 -0.1868 2.0922 3.7341 0.4863 0.2059 5.3610 +#> 96: 94.5986 -0.1900 2.0771 3.5474 0.4998 0.1956 5.2070 +#> 97: 94.2586 -0.1881 2.1051 3.9558 0.4757 0.1858 5.1561 +#> 98: 94.0716 -0.2098 2.0698 5.6441 0.4539 0.2044 5.1802 +#> 99: 94.2657 -0.2065 2.0679 5.6964 0.4679 0.2190 5.3608 +#> 100: 94.2331 -0.2203 2.0679 5.4116 0.4445 0.2256 5.4031 +#> 101: 93.8634 -0.2222 2.0720 5.1410 0.4279 0.2341 5.3774 +#> 102: 93.7675 -0.2496 2.0232 4.8839 0.4103 0.2224 5.1238 +#> 103: 93.9534 -0.2416 2.0249 4.6397 0.4144 0.2113 5.0031 +#> 104: 94.0631 -0.2442 2.0216 4.8203 0.4119 0.2007 5.1163 +#> 105: 94.0324 -0.2464 2.0092 4.5793 0.4135 0.2047 5.1666 +#> 106: 93.9954 -0.2482 2.0256 4.9167 0.4083 0.2052 5.2515 +#> 107: 94.2189 -0.2507 2.0121 4.6709 0.4072 0.2087 5.3430 +#> 108: 94.3707 -0.2448 2.0215 4.4373 0.4119 0.1996 5.1549 +#> 109: 94.1518 -0.2428 2.0197 4.2155 0.4155 0.1958 5.5480 +#> 110: 93.9287 -0.2571 2.0275 4.0047 0.4152 0.1931 5.8482 +#> 111: 93.9743 -0.2488 2.0202 3.8045 0.4171 0.2084 5.9798 +#> 112: 93.6245 -0.2350 2.0346 3.6142 0.4397 0.1980 6.0270 +#> 113: 94.5370 -0.2330 2.0593 3.9090 0.4422 0.1881 5.4431 +#> 114: 94.5052 -0.2289 2.0555 3.7135 0.4391 0.1787 5.5970 +#> 115: 94.5963 -0.2216 2.0579 3.5279 0.4446 0.1727 5.3901 +#> 116: 94.5059 -0.2293 2.0459 3.3515 0.4407 0.1705 5.2788 +#> 117: 94.6315 -0.2211 2.0564 3.1839 0.4279 0.1689 5.3258 +#> 118: 94.4868 -0.2194 2.0508 4.6523 0.4275 0.1604 5.1421 +#> 119: 94.1809 -0.2232 2.0444 7.0101 0.4302 0.1612 5.3468 +#> 120: 94.0950 -0.2231 2.0482 7.2110 0.4304 0.1625 5.1691 +#> 121: 94.1525 -0.2059 2.0682 6.8504 0.4474 0.1875 5.2811 +#> 122: 94.7122 -0.2154 2.0692 6.6747 0.4366 0.1906 5.3851 +#> 123: 94.2915 -0.2311 2.0431 6.9655 0.4351 0.2021 5.2103 +#> 124: 93.9984 -0.2310 2.0401 6.6173 0.4396 0.2091 5.0920 +#> 125: 94.3668 -0.2068 2.0505 6.2864 0.4983 0.1987 5.3263 +#> 126: 94.3570 -0.2043 2.0525 5.9721 0.5006 0.1887 5.3281 +#> 127: 94.7086 -0.2177 2.0377 5.6735 0.4762 0.1958 5.4003 +#> 128: 94.3565 -0.2173 2.0432 5.3898 0.4754 0.2055 5.5196 +#> 129: 94.4862 -0.2066 2.0639 5.1203 0.4807 0.1952 5.4783 +#> 130: 94.6107 -0.2026 2.0908 4.8643 0.4579 0.1855 5.6186 +#> 131: 94.6831 -0.1907 2.0920 4.6211 0.4710 0.1762 5.4859 +#> 132: 94.7035 -0.2052 2.0733 4.6333 0.4492 0.1723 5.2721 +#> 133: 94.1511 -0.2192 2.0615 5.7533 0.4362 0.1905 5.5019 +#> 134: 94.2758 -0.2101 2.0624 5.4656 0.4356 0.1810 5.3233 +#> 135: 94.6546 -0.1960 2.0826 5.1923 0.4281 0.1980 5.2515 +#> 136: 94.0322 -0.2100 2.0770 4.9327 0.4156 0.2103 5.3514 +#> 137: 94.0915 -0.2096 2.0859 5.6044 0.4159 0.2008 5.2755 +#> 138: 94.2452 -0.1983 2.1055 6.0837 0.4213 0.2185 5.0580 +#> 139: 94.5460 -0.1876 2.1093 6.8410 0.4301 0.2288 5.0840 +#> 140: 94.6905 -0.1863 2.1167 7.4689 0.4313 0.2173 5.0868 +#> 141: 94.6425 -0.1703 2.1240 7.0955 0.4522 0.2065 4.9715 +#> 142: 94.2538 -0.1632 2.1514 6.7407 0.4499 0.2059 5.0853 +#> 143: 94.3098 -0.1625 2.1567 6.4037 0.4499 0.2115 5.5860 +#> 144: 94.2802 -0.1716 2.1510 6.0835 0.4535 0.2081 5.1989 +#> 145: 94.1169 -0.1707 2.1523 5.7793 0.4531 0.2109 5.1407 +#> 146: 94.2558 -0.1579 2.1623 5.4903 0.4654 0.2427 5.2652 +#> 147: 93.9440 -0.1587 2.1673 5.2158 0.4611 0.2537 5.2699 +#> 148: 94.4271 -0.1587 2.1586 4.9550 0.4611 0.2595 5.1280 +#> 149: 94.2734 -0.1768 2.1160 4.7073 0.4809 0.2802 4.9251 +#> 150: 94.2406 -0.1928 2.0941 5.4176 0.4626 0.2662 5.0837 +#> 151: 94.4217 -0.1884 2.0965 5.1467 0.4677 0.2538 5.1728 +#> 152: 94.4856 -0.1826 2.1127 5.6736 0.4646 0.2373 5.1522 +#> 153: 94.3458 -0.1686 2.1381 6.3603 0.4760 0.2028 5.2197 +#> 154: 94.3945 -0.1633 2.1370 5.1586 0.4402 0.1955 5.3770 +#> 155: 94.6367 -0.1520 2.1596 6.4738 0.4533 0.1882 5.3345 +#> 156: 94.9050 -0.1521 2.1417 6.8382 0.4532 0.1729 5.2770 +#> 157: 94.5823 -0.1540 2.1326 5.5745 0.4487 0.1813 5.2760 +#> 158: 94.8355 -0.1691 2.1357 5.2979 0.4296 0.1990 5.3177 +#> 159: 94.7330 -0.1740 2.1148 4.0960 0.4476 0.1820 5.3001 +#> 160: 94.4926 -0.1731 2.1123 4.3550 0.4666 0.1817 5.1849 +#> 161: 94.4953 -0.1758 2.1063 4.0311 0.4698 0.1929 5.1371 +#> 162: 94.5639 -0.1753 2.1064 4.3044 0.4692 0.1911 5.1437 +#> 163: 94.5477 -0.1798 2.1041 4.1393 0.4804 0.2002 5.3561 +#> 164: 94.3812 -0.1934 2.1019 3.5760 0.4689 0.1908 5.3231 +#> 165: 94.0978 -0.1924 2.0973 2.2052 0.4743 0.1962 5.2813 +#> 166: 94.1374 -0.2043 2.0834 2.5477 0.4639 0.1904 5.3277 +#> 167: 94.1587 -0.2036 2.0797 2.7035 0.4561 0.1951 5.3106 +#> 168: 94.1518 -0.2166 2.0654 2.4969 0.4405 0.2090 5.3148 +#> 169: 94.3328 -0.2164 2.0652 2.3067 0.4455 0.1993 5.2385 +#> 170: 94.6029 -0.2176 2.0456 1.7913 0.4478 0.2085 5.4589 +#> 171: 94.2690 -0.2189 2.0635 1.8133 0.4496 0.1999 5.4918 +#> 172: 94.3227 -0.2120 2.0643 1.7763 0.4337 0.2063 5.4992 +#> 173: 94.3099 -0.2039 2.0892 1.1103 0.4350 0.2201 5.5148 +#> 174: 94.3192 -0.1895 2.1140 0.9817 0.4454 0.2078 5.5249 +#> 175: 94.2327 -0.1967 2.0939 0.9890 0.4361 0.1876 5.6321 +#> 176: 94.2707 -0.1989 2.0958 1.3001 0.4405 0.1790 5.6494 +#> 177: 94.0762 -0.2024 2.0908 0.9179 0.4426 0.1778 5.7085 +#> 178: 94.1807 -0.2074 2.0761 1.2663 0.4237 0.2064 5.5157 +#> 179: 94.2221 -0.2029 2.1083 2.0148 0.4270 0.2023 5.6770 +#> 180: 94.5889 -0.1975 2.0974 1.5302 0.4223 0.1778 5.7495 +#> 181: 94.4280 -0.2163 2.0648 1.8829 0.3908 0.1994 5.3948 +#> 182: 94.7076 -0.2247 2.0340 2.1148 0.4238 0.2062 5.4167 +#> 183: 94.5127 -0.2292 2.0317 3.0950 0.4302 0.2160 5.5009 +#> 184: 94.2522 -0.2335 2.0515 2.8900 0.4265 0.2038 5.2995 +#> 185: 94.2331 -0.2330 2.0431 3.3282 0.4276 0.2044 5.2220 +#> 186: 94.2207 -0.2259 2.0512 4.0568 0.4253 0.2008 5.2307 +#> 187: 94.5124 -0.2188 2.0603 3.0941 0.4381 0.1962 5.6927 +#> 188: 94.7691 -0.2454 2.0193 3.1090 0.4409 0.2012 5.5051 +#> 189: 94.5693 -0.2399 2.0169 3.1069 0.4292 0.1883 5.4354 +#> 190: 94.5742 -0.2318 2.0256 4.4216 0.4200 0.1932 5.3851 +#> 191: 94.3882 -0.2475 1.9949 4.5490 0.4366 0.1972 5.2470 +#> 192: 94.4267 -0.2478 1.9943 4.3327 0.4281 0.1995 5.2792 +#> 193: 94.6313 -0.2522 1.9703 3.5911 0.4321 0.1944 5.6218 +#> 194: 94.4345 -0.2616 1.9704 3.2209 0.4260 0.1925 5.5199 +#> 195: 94.6135 -0.2614 1.9622 2.1481 0.4264 0.1879 5.5750 +#> 196: 94.7574 -0.2324 2.0049 1.3351 0.4661 0.1738 5.6590 +#> 197: 94.8293 -0.2064 2.0452 1.6807 0.4904 0.1600 5.7639 +#> 198: 94.6372 -0.2157 2.0307 1.6350 0.5008 0.1524 5.6539 +#> 199: 94.5600 -0.2145 2.0318 1.5133 0.4982 0.1604 5.7178 +#> 200: 94.6945 -0.2100 2.0475 1.4526 0.5066 0.1649 5.6094 +#> 201: 94.5335 -0.2025 2.0594 1.3754 0.5066 0.1681 5.6560 +#> 202: 94.4663 -0.1992 2.0657 1.3622 0.5074 0.1665 5.6522 +#> 203: 94.4750 -0.1956 2.0762 1.3218 0.5051 0.1648 5.5985 +#> 204: 94.4206 -0.1916 2.0795 1.3219 0.5066 0.1593 5.5864 +#> 205: 94.4408 -0.1891 2.0816 1.2934 0.5089 0.1553 5.5967 +#> 206: 94.4631 -0.1863 2.0859 1.2768 0.5108 0.1522 5.6212 +#> 207: 94.4742 -0.1825 2.0912 1.3219 0.5122 0.1479 5.6704 +#> 208: 94.4802 -0.1789 2.0950 1.3488 0.5137 0.1450 5.7072 +#> 209: 94.4734 -0.1756 2.1019 1.3165 0.5155 0.1423 5.7458 +#> 210: 94.4589 -0.1742 2.1056 1.3379 0.5156 0.1409 5.7722 +#> 211: 94.4513 -0.1727 2.1083 1.3395 0.5192 0.1395 5.7707 +#> 212: 94.4422 -0.1718 2.1096 1.3506 0.5219 0.1384 5.7602 +#> 213: 94.4503 -0.1704 2.1112 1.3519 0.5233 0.1377 5.7705 +#> 214: 94.4387 -0.1688 2.1143 1.3620 0.5238 0.1374 5.7627 +#> 215: 94.4468 -0.1677 2.1171 1.3815 0.5236 0.1366 5.7552 +#> 216: 94.4314 -0.1671 2.1191 1.4034 0.5217 0.1362 5.7279 +#> 217: 94.4134 -0.1669 2.1206 1.4118 0.5197 0.1363 5.7109 +#> 218: 94.3896 -0.1665 2.1219 1.3959 0.5181 0.1381 5.6979 +#> 219: 94.3836 -0.1667 2.1226 1.3965 0.5160 0.1402 5.6829 +#> 220: 94.3740 -0.1674 2.1219 1.4130 0.5144 0.1419 5.6839 +#> 221: 94.3663 -0.1677 2.1216 1.4134 0.5131 0.1436 5.6717 +#> 222: 94.3498 -0.1683 2.1212 1.4170 0.5117 0.1453 5.6595 +#> 223: 94.3416 -0.1687 2.1219 1.4195 0.5105 0.1467 5.6587 +#> 224: 94.3412 -0.1687 2.1222 1.4245 0.5097 0.1474 5.6517 +#> 225: 94.3323 -0.1685 2.1235 1.4231 0.5093 0.1484 5.6419 +#> 226: 94.3228 -0.1686 2.1239 1.4167 0.5088 0.1493 5.6305 +#> 227: 94.3135 -0.1688 2.1241 1.4162 0.5084 0.1502 5.6197 +#> 228: 94.3088 -0.1686 2.1251 1.4170 0.5088 0.1515 5.6124 +#> 229: 94.2995 -0.1685 2.1257 1.4316 0.5092 0.1527 5.6079 +#> 230: 94.2864 -0.1690 2.1256 1.4492 0.5088 0.1534 5.6042 +#> 231: 94.2783 -0.1688 2.1260 1.4606 0.5085 0.1548 5.6037 +#> 232: 94.2725 -0.1687 2.1267 1.4571 0.5083 0.1557 5.6020 +#> 233: 94.2692 -0.1682 2.1279 1.4649 0.5076 0.1570 5.6027 +#> 234: 94.2697 -0.1678 2.1292 1.4540 0.5070 0.1584 5.5990 +#> 235: 94.2623 -0.1673 2.1302 1.4424 0.5064 0.1593 5.5919 +#> 236: 94.2610 -0.1667 2.1313 1.4255 0.5055 0.1599 5.5953 +#> 237: 94.2660 -0.1663 2.1322 1.4242 0.5053 0.1605 5.5922 +#> 238: 94.2753 -0.1666 2.1320 1.4370 0.5044 0.1611 5.5891 +#> 239: 94.2821 -0.1662 2.1326 1.4395 0.5036 0.1629 5.5864 +#> 240: 94.2886 -0.1661 2.1330 1.4375 0.5028 0.1644 5.5815 +#> 241: 94.2934 -0.1664 2.1329 1.4276 0.5020 0.1661 5.5777 +#> 242: 94.2963 -0.1664 2.1329 1.4247 0.5012 0.1677 5.5704 +#> 243: 94.2931 -0.1666 2.1328 1.4269 0.5008 0.1690 5.5631 +#> 244: 94.2919 -0.1667 2.1326 1.4279 0.5003 0.1701 5.5610 +#> 245: 94.2959 -0.1675 2.1316 1.4289 0.4993 0.1705 5.5524 +#> 246: 94.2992 -0.1683 2.1305 1.4378 0.4986 0.1706 5.5436 +#> 247: 94.2997 -0.1689 2.1296 1.4461 0.4977 0.1707 5.5383 +#> 248: 94.2978 -0.1693 2.1290 1.4430 0.4970 0.1714 5.5362 +#> 249: 94.2991 -0.1697 2.1285 1.4495 0.4963 0.1720 5.5379 +#> 250: 94.3068 -0.1702 2.1279 1.4556 0.4954 0.1723 5.5390 +#> 251: 94.3097 -0.1707 2.1272 1.4588 0.4936 0.1729 5.5342 +#> 252: 94.3104 -0.1711 2.1267 1.4582 0.4919 0.1739 5.5310 +#> 253: 94.3099 -0.1715 2.1262 1.4551 0.4903 0.1746 5.5279 +#> 254: 94.3110 -0.1721 2.1255 1.4592 0.4886 0.1758 5.5223 +#> 255: 94.3111 -0.1731 2.1236 1.4755 0.4878 0.1775 5.5175 +#> 256: 94.3096 -0.1735 2.1227 1.4971 0.4875 0.1784 5.5162 +#> 257: 94.3079 -0.1738 2.1222 1.5277 0.4874 0.1795 5.5132 +#> 258: 94.3103 -0.1741 2.1217 1.5521 0.4872 0.1806 5.5112 +#> 259: 94.3148 -0.1745 2.1212 1.5788 0.4868 0.1817 5.5066 +#> 260: 94.3170 -0.1750 2.1205 1.6038 0.4863 0.1832 5.5007 +#> 261: 94.3158 -0.1756 2.1197 1.6324 0.4857 0.1849 5.4968 +#> 262: 94.3141 -0.1763 2.1186 1.6503 0.4850 0.1866 5.4918 +#> 263: 94.3135 -0.1764 2.1184 1.6658 0.4849 0.1879 5.4910 +#> 264: 94.3121 -0.1767 2.1183 1.6841 0.4848 0.1893 5.4875 +#> 265: 94.3098 -0.1769 2.1184 1.7115 0.4847 0.1903 5.4832 +#> 266: 94.3087 -0.1768 2.1188 1.7162 0.4845 0.1911 5.4783 +#> 267: 94.3082 -0.1767 2.1191 1.7209 0.4842 0.1920 5.4735 +#> 268: 94.3094 -0.1764 2.1198 1.7314 0.4837 0.1926 5.4720 +#> 269: 94.3074 -0.1764 2.1199 1.7340 0.4831 0.1938 5.4718 +#> 270: 94.3025 -0.1764 2.1200 1.7440 0.4832 0.1949 5.4720 +#> 271: 94.3025 -0.1769 2.1194 1.7538 0.4829 0.1958 5.4748 +#> 272: 94.3039 -0.1772 2.1191 1.7664 0.4829 0.1966 5.4773 +#> 273: 94.3046 -0.1773 2.1192 1.7820 0.4826 0.1976 5.4754 +#> 274: 94.3051 -0.1774 2.1193 1.7895 0.4823 0.1988 5.4735 +#> 275: 94.3026 -0.1773 2.1193 1.7891 0.4819 0.1998 5.4749 +#> 276: 94.3034 -0.1771 2.1195 1.7875 0.4812 0.2010 5.4829 +#> 277: 94.3047 -0.1771 2.1197 1.7843 0.4805 0.2026 5.4878 +#> 278: 94.3067 -0.1771 2.1197 1.7747 0.4799 0.2039 5.4888 +#> 279: 94.3066 -0.1768 2.1202 1.7772 0.4795 0.2049 5.4889 +#> 280: 94.3035 -0.1768 2.1203 1.7797 0.4788 0.2062 5.4888 +#> 281: 94.2961 -0.1771 2.1203 1.7789 0.4782 0.2068 5.4874 +#> 282: 94.2893 -0.1772 2.1203 1.7797 0.4777 0.2072 5.4865 +#> 283: 94.2880 -0.1776 2.1198 1.7743 0.4772 0.2074 5.4856 +#> 284: 94.2897 -0.1779 2.1195 1.7717 0.4768 0.2076 5.4836 +#> 285: 94.2922 -0.1781 2.1194 1.7756 0.4765 0.2075 5.4818 +#> 286: 94.2964 -0.1783 2.1190 1.7759 0.4763 0.2074 5.4798 +#> 287: 94.2991 -0.1787 2.1181 1.7884 0.4761 0.2075 5.4769 +#> 288: 94.2980 -0.1793 2.1171 1.7901 0.4756 0.2077 5.4772 +#> 289: 94.2948 -0.1797 2.1166 1.7957 0.4752 0.2077 5.4763 +#> 290: 94.2922 -0.1801 2.1161 1.8012 0.4749 0.2074 5.4752 +#> 291: 94.2891 -0.1803 2.1157 1.8016 0.4747 0.2073 5.4743 +#> 292: 94.2890 -0.1805 2.1155 1.8012 0.4746 0.2072 5.4743 +#> 293: 94.2874 -0.1808 2.1152 1.8012 0.4743 0.2073 5.4743 +#> 294: 94.2841 -0.1811 2.1148 1.8003 0.4740 0.2075 5.4758 +#> 295: 94.2834 -0.1813 2.1143 1.7982 0.4743 0.2075 5.4766 +#> 296: 94.2817 -0.1816 2.1138 1.7997 0.4745 0.2074 5.4756 +#> 297: 94.2772 -0.1820 2.1131 1.8025 0.4747 0.2074 5.4778 +#> 298: 94.2759 -0.1822 2.1125 1.8097 0.4747 0.2073 5.4781 +#> 299: 94.2752 -0.1825 2.1120 1.8176 0.4748 0.2071 5.4784 +#> 300: 94.2758 -0.1828 2.1115 1.8353 0.4750 0.2069 5.4771 +#> 301: 94.2789 -0.1829 2.1113 1.8511 0.4749 0.2066 5.4767 +#> 302: 94.2808 -0.1833 2.1107 1.8541 0.4747 0.2065 5.4785 +#> 303: 94.2832 -0.1836 2.1103 1.8571 0.4745 0.2064 5.4789 +#> 304: 94.2838 -0.1840 2.1097 1.8584 0.4743 0.2064 5.4792 +#> 305: 94.2835 -0.1843 2.1090 1.8633 0.4741 0.2066 5.4790 +#> 306: 94.2868 -0.1847 2.1083 1.8633 0.4738 0.2069 5.4802 +#> 307: 94.2909 -0.1851 2.1076 1.8702 0.4737 0.2072 5.4787 +#> 308: 94.2916 -0.1857 2.1067 1.8754 0.4735 0.2075 5.4773 +#> 309: 94.2889 -0.1860 2.1062 1.8785 0.4732 0.2078 5.4774 +#> 310: 94.2875 -0.1863 2.1059 1.8854 0.4727 0.2082 5.4763 +#> 311: 94.2889 -0.1867 2.1053 1.8873 0.4722 0.2087 5.4746 +#> 312: 94.2889 -0.1870 2.1047 1.8956 0.4717 0.2090 5.4748 +#> 313: 94.2836 -0.1873 2.1044 1.8980 0.4711 0.2093 5.4721 +#> 314: 94.2801 -0.1876 2.1041 1.8924 0.4706 0.2096 5.4718 +#> 315: 94.2768 -0.1880 2.1038 1.8875 0.4701 0.2096 5.4727 +#> 316: 94.2766 -0.1883 2.1035 1.8854 0.4697 0.2097 5.4730 +#> 317: 94.2779 -0.1886 2.1030 1.8808 0.4693 0.2099 5.4725 +#> 318: 94.2806 -0.1889 2.1024 1.8789 0.4688 0.2101 5.4713 +#> 319: 94.2853 -0.1891 2.1018 1.8852 0.4684 0.2104 5.4690 +#> 320: 94.2867 -0.1894 2.1016 1.8898 0.4680 0.2106 5.4677 +#> 321: 94.2883 -0.1897 2.1013 1.8975 0.4676 0.2108 5.4656 +#> 322: 94.2864 -0.1899 2.1011 1.9078 0.4672 0.2109 5.4622 +#> 323: 94.2831 -0.1902 2.1009 1.9181 0.4668 0.2109 5.4593 +#> 324: 94.2799 -0.1904 2.1008 1.9355 0.4665 0.2109 5.4599 +#> 325: 94.2802 -0.1905 2.1007 1.9474 0.4660 0.2112 5.4608 +#> 326: 94.2808 -0.1907 2.1006 1.9656 0.4654 0.2114 5.4606 +#> 327: 94.2815 -0.1907 2.1006 1.9851 0.4649 0.2118 5.4596 +#> 328: 94.2805 -0.1908 2.1007 2.0051 0.4644 0.2120 5.4584 +#> 329: 94.2810 -0.1909 2.1004 2.0162 0.4638 0.2124 5.4566 +#> 330: 94.2812 -0.1912 2.0999 2.0210 0.4632 0.2131 5.4548 +#> 331: 94.2830 -0.1915 2.0994 2.0253 0.4625 0.2136 5.4520 +#> 332: 94.2835 -0.1920 2.0987 2.0288 0.4619 0.2142 5.4493 +#> 333: 94.2832 -0.1924 2.0981 2.0365 0.4615 0.2148 5.4463 +#> 334: 94.2845 -0.1928 2.0976 2.0433 0.4611 0.2153 5.4436 +#> 335: 94.2856 -0.1931 2.0971 2.0423 0.4607 0.2158 5.4405 +#> 336: 94.2886 -0.1936 2.0963 2.0400 0.4606 0.2165 5.4386 +#> 337: 94.2888 -0.1939 2.0957 2.0352 0.4604 0.2171 5.4376 +#> 338: 94.2879 -0.1944 2.0950 2.0360 0.4600 0.2179 5.4361 +#> 339: 94.2860 -0.1947 2.0946 2.0418 0.4599 0.2186 5.4342 +#> 340: 94.2842 -0.1951 2.0940 2.0455 0.4597 0.2192 5.4324 +#> 341: 94.2804 -0.1954 2.0934 2.0535 0.4596 0.2199 5.4310 +#> 342: 94.2772 -0.1958 2.0928 2.0586 0.4594 0.2204 5.4310 +#> 343: 94.2753 -0.1962 2.0921 2.0604 0.4592 0.2209 5.4304 +#> 344: 94.2749 -0.1965 2.0916 2.0591 0.4589 0.2214 5.4305 +#> 345: 94.2757 -0.1969 2.0911 2.0582 0.4586 0.2220 5.4302 +#> 346: 94.2774 -0.1972 2.0906 2.0554 0.4584 0.2225 5.4301 +#> 347: 94.2772 -0.1974 2.0901 2.0533 0.4583 0.2230 5.4298 +#> 348: 94.2769 -0.1977 2.0895 2.0497 0.4581 0.2235 5.4302 +#> 349: 94.2792 -0.1980 2.0890 2.0439 0.4579 0.2241 5.4327 +#> 350: 94.2825 -0.1983 2.0884 2.0391 0.4577 0.2245 5.4358 +#> 351: 94.2849 -0.1985 2.0879 2.0352 0.4576 0.2251 5.4399 +#> 352: 94.2871 -0.1988 2.0874 2.0396 0.4576 0.2257 5.4414 +#> 353: 94.2888 -0.1991 2.0869 2.0407 0.4573 0.2262 5.4417 +#> 354: 94.2914 -0.1994 2.0863 2.0383 0.4571 0.2268 5.4417 +#> 355: 94.2933 -0.1996 2.0859 2.0385 0.4570 0.2275 5.4418 +#> 356: 94.2932 -0.1999 2.0853 2.0377 0.4569 0.2284 5.4426 +#> 357: 94.2944 -0.2001 2.0850 2.0362 0.4566 0.2292 5.4423 +#> 358: 94.2948 -0.2003 2.0847 2.0415 0.4562 0.2299 5.4409 +#> 359: 94.2950 -0.2005 2.0843 2.0452 0.4558 0.2304 5.4393 +#> 360: 94.2967 -0.2008 2.0840 2.0514 0.4554 0.2307 5.4385 +#> 361: 94.2983 -0.2009 2.0839 2.0676 0.4551 0.2308 5.4386 +#> 362: 94.2992 -0.2009 2.0840 2.0770 0.4549 0.2307 5.4370 +#> 363: 94.2991 -0.2008 2.0841 2.0831 0.4550 0.2306 5.4348 +#> 364: 94.2982 -0.2007 2.0843 2.0892 0.4549 0.2304 5.4348 +#> 365: 94.2951 -0.2005 2.0847 2.1002 0.4551 0.2302 5.4347 +#> 366: 94.2938 -0.2004 2.0850 2.1176 0.4553 0.2300 5.4343 +#> 367: 94.2945 -0.2003 2.0850 2.1310 0.4553 0.2298 5.4346 +#> 368: 94.2956 -0.2003 2.0851 2.1436 0.4554 0.2295 5.4323 +#> 369: 94.2960 -0.2003 2.0850 2.1526 0.4555 0.2293 5.4309 +#> 370: 94.2964 -0.2003 2.0848 2.1577 0.4555 0.2292 5.4295 +#> 371: 94.2965 -0.2004 2.0847 2.1621 0.4555 0.2290 5.4278 +#> 372: 94.2972 -0.2004 2.0847 2.1635 0.4556 0.2285 5.4275 +#> 373: 94.2975 -0.2003 2.0848 2.1643 0.4556 0.2282 5.4275 +#> 374: 94.2985 -0.2004 2.0847 2.1648 0.4556 0.2277 5.4270 +#> 375: 94.3001 -0.2004 2.0846 2.1682 0.4555 0.2273 5.4255 +#> 376: 94.3024 -0.2005 2.0845 2.1692 0.4555 0.2268 5.4246 +#> 377: 94.3050 -0.2005 2.0843 2.1700 0.4555 0.2264 5.4239 +#> 378: 94.3041 -0.2005 2.0843 2.1680 0.4555 0.2258 5.4242 +#> 379: 94.3034 -0.2006 2.0842 2.1688 0.4554 0.2255 5.4233 +#> 380: 94.3027 -0.2007 2.0840 2.1754 0.4554 0.2250 5.4222 +#> 381: 94.3015 -0.2008 2.0839 2.1806 0.4553 0.2246 5.4205 +#> 382: 94.3006 -0.2009 2.0837 2.1812 0.4552 0.2242 5.4194 +#> 383: 94.3004 -0.2010 2.0835 2.1835 0.4551 0.2236 5.4178 +#> 384: 94.3001 -0.2011 2.0834 2.1895 0.4550 0.2232 5.4159 +#> 385: 94.3005 -0.2012 2.0834 2.1910 0.4547 0.2228 5.4148 +#> 386: 94.2993 -0.2013 2.0834 2.1926 0.4545 0.2224 5.4139 +#> 387: 94.2974 -0.2014 2.0834 2.1956 0.4543 0.2221 5.4135 +#> 388: 94.2964 -0.2014 2.0835 2.1979 0.4541 0.2218 5.4124 +#> 389: 94.2956 -0.2013 2.0837 2.1974 0.4540 0.2215 5.4117 +#> 390: 94.2962 -0.2013 2.0838 2.1995 0.4538 0.2213 5.4115 +#> 391: 94.2962 -0.2013 2.0838 2.1987 0.4537 0.2211 5.4116 +#> 392: 94.2956 -0.2013 2.0839 2.2007 0.4536 0.2209 5.4111 +#> 393: 94.2954 -0.2012 2.0839 2.2041 0.4535 0.2207 5.4106 +#> 394: 94.2953 -0.2012 2.0840 2.2033 0.4535 0.2205 5.4103 +#> 395: 94.2964 -0.2012 2.0841 2.2052 0.4533 0.2203 5.4098 +#> 396: 94.2950 -0.2012 2.0841 2.2123 0.4532 0.2202 5.4081 +#> 397: 94.2940 -0.2011 2.0843 2.2227 0.4533 0.2201 5.4070 +#> 398: 94.2938 -0.2011 2.0842 2.2283 0.4534 0.2201 5.4065 +#> 399: 94.2930 -0.2012 2.0842 2.2296 0.4535 0.2201 5.4066 +#> 400: 94.2931 -0.2011 2.0844 2.2345 0.4537 0.2199 5.4071 +#> 401: 94.2926 -0.2009 2.0846 2.2414 0.4539 0.2198 5.4067 +#> 402: 94.2916 -0.2008 2.0848 2.2478 0.4541 0.2196 5.4070 +#> 403: 94.2902 -0.2007 2.0849 2.2543 0.4544 0.2194 5.4071 +#> 404: 94.2895 -0.2007 2.0851 2.2578 0.4546 0.2192 5.4079 +#> 405: 94.2896 -0.2006 2.0853 2.2600 0.4548 0.2190 5.4082 +#> 406: 94.2897 -0.2004 2.0855 2.2636 0.4550 0.2188 5.4086 +#> 407: 94.2880 -0.2002 2.0859 2.2670 0.4554 0.2188 5.4079 +#> 408: 94.2883 -0.1999 2.0861 2.2735 0.4556 0.2189 5.4076 +#> 409: 94.2874 -0.1997 2.0865 2.2822 0.4559 0.2190 5.4073 +#> 410: 94.2861 -0.1995 2.0867 2.2861 0.4563 0.2190 5.4062 +#> 411: 94.2861 -0.1993 2.0869 2.2883 0.4566 0.2190 5.4049 +#> 412: 94.2869 -0.1991 2.0872 2.2926 0.4570 0.2190 5.4039 +#> 413: 94.2874 -0.1990 2.0873 2.2936 0.4574 0.2190 5.4031 +#> 414: 94.2881 -0.1988 2.0874 2.2972 0.4577 0.2189 5.4019 +#> 415: 94.2895 -0.1987 2.0876 2.2999 0.4580 0.2188 5.4004 +#> 416: 94.2900 -0.1985 2.0878 2.3003 0.4582 0.2186 5.3997 +#> 417: 94.2917 -0.1984 2.0880 2.2986 0.4583 0.2185 5.3993 +#> 418: 94.2937 -0.1982 2.0882 2.2986 0.4584 0.2183 5.3995 +#> 419: 94.2947 -0.1981 2.0885 2.2993 0.4584 0.2182 5.3995 +#> 420: 94.2954 -0.1979 2.0886 2.2993 0.4585 0.2180 5.3996 +#> 421: 94.2963 -0.1978 2.0888 2.3029 0.4587 0.2180 5.3992 +#> 422: 94.2982 -0.1976 2.0890 2.3074 0.4588 0.2178 5.4000 +#> 423: 94.3001 -0.1975 2.0891 2.3099 0.4589 0.2178 5.3999 +#> 424: 94.3007 -0.1974 2.0891 2.3106 0.4589 0.2177 5.4001 +#> 425: 94.3016 -0.1973 2.0893 2.3107 0.4589 0.2176 5.3997 +#> 426: 94.3021 -0.1972 2.0894 2.3119 0.4590 0.2175 5.3990 +#> 427: 94.3009 -0.1972 2.0894 2.3100 0.4590 0.2175 5.3971 +#> 428: 94.2998 -0.1972 2.0895 2.3070 0.4590 0.2175 5.3966 +#> 429: 94.2988 -0.1973 2.0895 2.3033 0.4590 0.2175 5.3958 +#> 430: 94.2968 -0.1973 2.0895 2.3028 0.4590 0.2174 5.3955 +#> 431: 94.2950 -0.1973 2.0895 2.3004 0.4589 0.2174 5.3954 +#> 432: 94.2944 -0.1973 2.0896 2.2966 0.4589 0.2174 5.3956 +#> 433: 94.2950 -0.1972 2.0897 2.2942 0.4589 0.2176 5.3959 +#> 434: 94.2949 -0.1972 2.0898 2.2911 0.4589 0.2177 5.3955 +#> 435: 94.2943 -0.1971 2.0900 2.2914 0.4588 0.2179 5.3943 +#> 436: 94.2943 -0.1970 2.0902 2.2895 0.4586 0.2180 5.3948 +#> 437: 94.2955 -0.1970 2.0903 2.2890 0.4585 0.2181 5.3954 +#> 438: 94.2961 -0.1969 2.0905 2.2918 0.4584 0.2183 5.3958 +#> 439: 94.2954 -0.1968 2.0906 2.2943 0.4583 0.2185 5.3953 +#> 440: 94.2944 -0.1968 2.0906 2.2977 0.4581 0.2187 5.3949 +#> 441: 94.2931 -0.1968 2.0907 2.2991 0.4578 0.2188 5.3952 +#> 442: 94.2926 -0.1968 2.0908 2.2990 0.4575 0.2188 5.3951 +#> 443: 94.2922 -0.1968 2.0909 2.2990 0.4573 0.2188 5.3938 +#> 444: 94.2917 -0.1969 2.0909 2.2995 0.4571 0.2188 5.3927 +#> 445: 94.2901 -0.1969 2.0910 2.3067 0.4568 0.2187 5.3911 +#> 446: 94.2898 -0.1969 2.0910 2.3082 0.4566 0.2187 5.3891 +#> 447: 94.2897 -0.1969 2.0910 2.3121 0.4564 0.2187 5.3871 +#> 448: 94.2883 -0.1970 2.0911 2.3180 0.4562 0.2188 5.3858 +#> 449: 94.2879 -0.1970 2.0912 2.3210 0.4561 0.2188 5.3851 +#> 450: 94.2874 -0.1970 2.0914 2.3243 0.4559 0.2188 5.3841 +#> 451: 94.2873 -0.1969 2.0915 2.3247 0.4557 0.2188 5.3834 +#> 452: 94.2873 -0.1969 2.0917 2.3249 0.4555 0.2187 5.3839 +#> 453: 94.2868 -0.1968 2.0920 2.3257 0.4554 0.2187 5.3831 +#> 454: 94.2857 -0.1967 2.0922 2.3240 0.4552 0.2187 5.3824 +#> 455: 94.2848 -0.1965 2.0925 2.3214 0.4551 0.2186 5.3822 +#> 456: 94.2838 -0.1964 2.0929 2.3204 0.4550 0.2185 5.3822 +#> 457: 94.2831 -0.1962 2.0932 2.3202 0.4549 0.2184 5.3819 +#> 458: 94.2831 -0.1961 2.0935 2.3174 0.4548 0.2183 5.3810 +#> 459: 94.2829 -0.1960 2.0938 2.3183 0.4546 0.2183 5.3807 +#> 460: 94.2818 -0.1958 2.0941 2.3213 0.4545 0.2183 5.3802 +#> 461: 94.2812 -0.1956 2.0945 2.3292 0.4544 0.2182 5.3785 +#> 462: 94.2813 -0.1955 2.0948 2.3328 0.4544 0.2182 5.3778 +#> 463: 94.2816 -0.1953 2.0951 2.3364 0.4543 0.2181 5.3770 +#> 464: 94.2810 -0.1952 2.0954 2.3365 0.4542 0.2180 5.3764 +#> 465: 94.2797 -0.1950 2.0957 2.3341 0.4541 0.2179 5.3756 +#> 466: 94.2777 -0.1949 2.0960 2.3368 0.4541 0.2178 5.3750 +#> 467: 94.2755 -0.1949 2.0962 2.3417 0.4539 0.2178 5.3738 +#> 468: 94.2741 -0.1948 2.0965 2.3426 0.4537 0.2177 5.3731 +#> 469: 94.2735 -0.1947 2.0967 2.3410 0.4535 0.2175 5.3729 +#> 470: 94.2731 -0.1946 2.0970 2.3440 0.4534 0.2173 5.3733 +#> 471: 94.2727 -0.1945 2.0972 2.3505 0.4533 0.2171 5.3724 +#> 472: 94.2734 -0.1944 2.0973 2.3550 0.4533 0.2169 5.3719 +#> 473: 94.2745 -0.1944 2.0974 2.3593 0.4533 0.2167 5.3715 +#> 474: 94.2746 -0.1944 2.0975 2.3622 0.4533 0.2166 5.3708 +#> 475: 94.2753 -0.1943 2.0975 2.3673 0.4533 0.2165 5.3701 +#> 476: 94.2760 -0.1943 2.0976 2.3745 0.4534 0.2166 5.3698 +#> 477: 94.2771 -0.1942 2.0978 2.3812 0.4535 0.2166 5.3695 +#> 478: 94.2767 -0.1941 2.0981 2.3891 0.4535 0.2166 5.3691 +#> 479: 94.2762 -0.1940 2.0984 2.3931 0.4534 0.2166 5.3691 +#> 480: 94.2754 -0.1939 2.0986 2.3958 0.4533 0.2166 5.3685 +#> 481: 94.2743 -0.1938 2.0987 2.3990 0.4532 0.2165 5.3677 +#> 482: 94.2733 -0.1937 2.0988 2.3996 0.4531 0.2164 5.3670 +#> 483: 94.2724 -0.1937 2.0989 2.4031 0.4531 0.2163 5.3659 +#> 484: 94.2726 -0.1937 2.0989 2.4035 0.4530 0.2162 5.3651 +#> 485: 94.2722 -0.1937 2.0989 2.4033 0.4530 0.2162 5.3649 +#> 486: 94.2716 -0.1936 2.0991 2.4046 0.4529 0.2163 5.3645 +#> 487: 94.2710 -0.1936 2.0992 2.4078 0.4527 0.2165 5.3643 +#> 488: 94.2693 -0.1936 2.0992 2.4088 0.4525 0.2167 5.3653 +#> 489: 94.2689 -0.1936 2.0993 2.4116 0.4523 0.2170 5.3645 +#> 490: 94.2686 -0.1936 2.0993 2.4105 0.4520 0.2172 5.3644 +#> 491: 94.2685 -0.1935 2.0994 2.4097 0.4518 0.2174 5.3651 +#> 492: 94.2677 -0.1935 2.0995 2.4103 0.4517 0.2175 5.3657 +#> 493: 94.2670 -0.1935 2.0996 2.4112 0.4515 0.2177 5.3661 +#> 494: 94.2668 -0.1935 2.0996 2.4140 0.4514 0.2178 5.3662 +#> 495: 94.2667 -0.1936 2.0996 2.4157 0.4513 0.2179 5.3660 +#> 496: 94.2670 -0.1936 2.0996 2.4163 0.4511 0.2180 5.3668 +#> 497: 94.2664 -0.1936 2.0996 2.4170 0.4510 0.2181 5.3676 +#> 498: 94.2654 -0.1937 2.0996 2.4128 0.4509 0.2181 5.3683 +#> 499: 94.2643 -0.1937 2.0996 2.4109 0.4508 0.2181 5.3679 +#> 500: 94.2635 -0.1938 2.0995 2.4122 0.4508 0.2181 5.3682</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='input'><span class='va'>f_nlmixr_fomc_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | parent_0 | log_alpha | log_beta | sigma | +#> <span style='text-decoration: underline;'>|.....................| o1 | o2 | o3 |...........|</span> +#> |<span style='font-weight: bold;'> 1</span>| 296.31831 | 1.000 | -1.000 | -0.9520 | -0.9547 | +#> |.....................| -0.9791 | -0.9725 | -0.9706 |...........| +#> | U| 296.31831 | 94.44 | -0.2226 | 2.048 | 1.920 | +#> |.....................| 0.7656 | 1.078 | 1.168 |...........| +#> | X|<span style='font-weight: bold;'> 296.31831</span> | 94.44 | 0.8004 | 7.754 | 1.920 | +#> <span style='text-decoration: underline;'>|.....................| 0.7656 | 1.078 | 1.168 |...........|</span> +#> | G| Gill Diff. | 9.126 | 0.009097 | -0.01177 | -32.33 | +#> <span style='text-decoration: underline;'>|.....................| 6.099 | -8.436 | -11.35 |...........|</span> +#> |<span style='font-weight: bold;'> 2</span>| 594.25462 | 0.7531 | -1.000 | -0.9517 | -0.07988 | +#> |.....................| -1.144 | -0.7442 | -0.6636 |...........| +#> | U| 594.25462 | 71.12 | -0.2229 | 2.049 | 2.760 | +#> |.....................| 0.6392 | 1.324 | 1.526 |...........| +#> | X|<span style='font-weight: bold;'> 594.25462</span> | 71.12 | 0.8002 | 7.756 | 2.760 | +#> <span style='text-decoration: underline;'>|.....................| 0.6392 | 1.324 | 1.526 |...........|</span> +#> |<span style='font-weight: bold;'> 3</span>| 298.71818 | 0.9753 | -1.000 | -0.9520 | -0.8672 | +#> |.....................| -0.9956 | -0.9497 | -0.9399 |...........| +#> | U| 298.71818 | 92.11 | -0.2226 | 2.048 | 2.004 | +#> |.....................| 0.7529 | 1.103 | 1.204 |...........| +#> | X|<span style='font-weight: bold;'> 298.71818</span> | 92.11 | 0.8004 | 7.754 | 2.004 | +#> <span style='text-decoration: underline;'>|.....................| 0.7529 | 1.103 | 1.204 |...........|</span> +#> |<span style='font-weight: bold;'> 4</span>| 295.79061 | 0.9925 | -1.000 | -0.9520 | -0.9282 | +#> |.....................| -0.9841 | -0.9656 | -0.9613 |...........| +#> | U| 295.79061 | 93.73 | -0.2226 | 2.048 | 1.945 | +#> |.....................| 0.7617 | 1.086 | 1.179 |...........| +#> | X|<span style='font-weight: bold;'> 295.79061</span> | 93.73 | 0.8004 | 7.754 | 1.945 | +#> <span style='text-decoration: underline;'>|.....................| 0.7617 | 1.086 | 1.179 |...........|</span> +#> | F| Forward Diff. | -134.6 | -0.07715 | -0.3541 | -29.37 | +#> <span style='text-decoration: underline;'>|.....................| 6.863 | -7.752 | -10.79 |...........|</span> +#> |<span style='font-weight: bold;'> 5</span>| 294.44078 | 1.001 | -1.000 | -0.9520 | -0.9020 | +#> |.....................| -0.9892 | -0.9588 | -0.9521 |...........| +#> | U| 294.44078 | 94.55 | -0.2226 | 2.048 | 1.970 | +#> |.....................| 0.7578 | 1.093 | 1.189 |...........| +#> | X|<span style='font-weight: bold;'> 294.44078</span> | 94.55 | 0.8004 | 7.754 | 1.970 | +#> <span style='text-decoration: underline;'>|.....................| 0.7578 | 1.093 | 1.189 |...........|</span> +#> | F| Forward Diff. | 30.39 | 0.01643 | 0.02646 | -26.06 | +#> <span style='text-decoration: underline;'>|.....................| 5.336 | -7.397 | -10.44 |...........|</span> +#> |<span style='font-weight: bold;'> 6</span>| 293.62741 | 0.9971 | -1.000 | -0.9519 | -0.8750 | +#> |.....................| -0.9945 | -0.9516 | -0.9423 |...........| +#> | U| 293.62741 | 94.17 | -0.2226 | 2.048 | 1.996 | +#> |.....................| 0.7538 | 1.101 | 1.201 |...........| +#> | X|<span style='font-weight: bold;'> 293.62741</span> | 94.17 | 0.8004 | 7.754 | 1.996 | +#> <span style='text-decoration: underline;'>|.....................| 0.7538 | 1.101 | 1.201 |...........|</span> +#> |<span style='font-weight: bold;'> 7</span>| 292.50099 | 0.9961 | -1.000 | -0.9519 | -0.8316 | +#> |.....................| -1.003 | -0.9401 | -0.9267 |...........| +#> | U| 292.50099 | 94.07 | -0.2226 | 2.048 | 2.038 | +#> |.....................| 0.7474 | 1.113 | 1.219 |...........| +#> | X|<span style='font-weight: bold;'> 292.50099</span> | 94.07 | 0.8004 | 7.755 | 2.038 | +#> <span style='text-decoration: underline;'>|.....................| 0.7474 | 1.113 | 1.219 |...........|</span> +#> |<span style='font-weight: bold;'> 8</span>| 290.76125 | 0.9939 | -1.000 | -0.9518 | -0.7361 | +#> |.....................| -1.021 | -0.9149 | -0.8925 |...........| +#> | U| 290.76125 | 93.87 | -0.2226 | 2.048 | 2.130 | +#> |.....................| 0.7332 | 1.140 | 1.259 |...........| +#> | X|<span style='font-weight: bold;'> 290.76125</span> | 93.87 | 0.8004 | 7.756 | 2.130 | +#> <span style='text-decoration: underline;'>|.....................| 0.7332 | 1.140 | 1.259 |...........|</span> +#> | F| Forward Diff. | -91.20 | -0.08176 | -0.4010 | -10.74 | +#> <span style='text-decoration: underline;'>|.....................| 3.658 | -4.872 | -7.770 |...........|</span> +#> |<span style='font-weight: bold;'> 9</span>| 293.40175 | 1.024 | -0.9990 | -0.9455 | -0.7012 | +#> |.....................| -1.060 | -0.8302 | -0.7398 |...........| +#> | U| 293.40175 | 96.67 | -0.2216 | 2.055 | 2.163 | +#> |.....................| 0.7035 | 1.231 | 1.437 |...........| +#> | X|<span style='font-weight: bold;'> 293.40175</span> | 96.67 | 0.8012 | 7.804 | 2.163 | +#> <span style='text-decoration: underline;'>|.....................| 0.7035 | 1.231 | 1.437 |...........|</span> +#> |<span style='font-weight: bold;'> 10</span>| 292.85583 | 1.019 | -0.9997 | -0.9499 | -0.7242 | +#> |.....................| -1.033 | -0.8898 | -0.8474 |...........| +#> | U| 292.85583 | 96.21 | -0.2223 | 2.050 | 2.141 | +#> |.....................| 0.7242 | 1.167 | 1.312 |...........| +#> | X|<span style='font-weight: bold;'> 292.85583</span> | 96.21 | 0.8007 | 7.770 | 2.141 | +#> <span style='text-decoration: underline;'>|.....................| 0.7242 | 1.167 | 1.312 |...........|</span> +#> |<span style='font-weight: bold;'> 11</span>| 291.55187 | 1.011 | -1.000 | -0.9517 | -0.7341 | +#> |.....................| -1.022 | -0.9140 | -0.8910 |...........| +#> | U| 291.55187 | 95.48 | -0.2226 | 2.048 | 2.132 | +#> |.....................| 0.7326 | 1.141 | 1.261 |...........| +#> | X|<span style='font-weight: bold;'> 291.55187</span> | 95.48 | 0.8004 | 7.756 | 2.132 | +#> <span style='text-decoration: underline;'>|.....................| 0.7326 | 1.141 | 1.261 |...........|</span> +#> |<span style='font-weight: bold;'> 12</span>| 290.49268 | 0.9997 | -1.000 | -0.9518 | -0.7354 | +#> |.....................| -1.022 | -0.9146 | -0.8920 |...........| +#> | U| 290.49268 | 94.41 | -0.2226 | 2.048 | 2.130 | +#> |.....................| 0.7330 | 1.141 | 1.259 |...........| +#> | X|<span style='font-weight: bold;'> 290.49268</span> | 94.41 | 0.8004 | 7.756 | 2.130 | +#> <span style='text-decoration: underline;'>|.....................| 0.7330 | 1.141 | 1.259 |...........|</span> +#> | F| Forward Diff. | 2.619 | -0.007793 | -0.07320 | -10.57 | +#> <span style='text-decoration: underline;'>|.....................| 3.077 | -4.876 | -7.795 |...........|</span> +#> |<span style='font-weight: bold;'> 13</span>| 290.41825 | 0.9986 | -1.000 | -0.9517 | -0.7312 | +#> |.....................| -1.023 | -0.9126 | -0.8889 |...........| +#> | U| 290.41825 | 94.31 | -0.2226 | 2.048 | 2.134 | +#> |.....................| 0.7321 | 1.143 | 1.263 |...........| +#> | X|<span style='font-weight: bold;'> 290.41825</span> | 94.31 | 0.8004 | 7.756 | 2.134 | +#> <span style='text-decoration: underline;'>|.....................| 0.7321 | 1.143 | 1.263 |...........|</span> +#> |<span style='font-weight: bold;'> 14</span>| 290.31205 | 0.9955 | -1.000 | -0.9517 | -0.7186 | +#> |.....................| -1.027 | -0.9068 | -0.8796 |...........| +#> | U| 290.31205 | 94.01 | -0.2226 | 2.049 | 2.146 | +#> |.....................| 0.7292 | 1.149 | 1.274 |...........| +#> | X|<span style='font-weight: bold;'> 290.31205</span> | 94.01 | 0.8004 | 7.757 | 2.146 | +#> <span style='text-decoration: underline;'>|.....................| 0.7292 | 1.149 | 1.274 |...........|</span> +#> | F| Forward Diff. | -64.45 | -0.06351 | -0.3251 | -9.485 | +#> <span style='text-decoration: underline;'>|.....................| 2.861 | -4.414 | -7.225 |...........|</span> +#> |<span style='font-weight: bold;'> 15</span>| 290.00198 | 1.000 | -0.9999 | -0.9510 | -0.7191 | +#> |.....................| -1.030 | -0.8965 | -0.8595 |...........| +#> | U| 290.00198 | 94.46 | -0.2225 | 2.049 | 2.146 | +#> |.....................| 0.7268 | 1.160 | 1.297 |...........| +#> | X|<span style='font-weight: bold;'> 290.00198</span> | 94.46 | 0.8005 | 7.762 | 2.146 | +#> <span style='text-decoration: underline;'>|.....................| 0.7268 | 1.160 | 1.297 |...........|</span> +#> | F| Forward Diff. | 11.27 | -0.003123 | -0.03408 | -9.156 | +#> <span style='text-decoration: underline;'>|.....................| 2.235 | -3.823 | -6.423 |...........|</span> +#> |<span style='font-weight: bold;'> 16</span>| 289.83558 | 0.9983 | -0.9998 | -0.9502 | -0.7180 | +#> |.....................| -1.031 | -0.8872 | -0.8384 |...........| +#> | U| 289.83558 | 94.28 | -0.2224 | 2.050 | 2.147 | +#> |.....................| 0.7259 | 1.170 | 1.322 |...........| +#> | X|<span style='font-weight: bold;'> 289.83558</span> | 94.28 | 0.8006 | 7.768 | 2.147 | +#> <span style='text-decoration: underline;'>|.....................| 0.7259 | 1.170 | 1.322 |...........|</span> +#> |<span style='font-weight: bold;'> 17</span>| 289.63307 | 0.9979 | -0.9995 | -0.9489 | -0.7184 | +#> |.....................| -1.032 | -0.8720 | -0.8037 |...........| +#> | U| 289.63307 | 94.24 | -0.2221 | 2.051 | 2.147 | +#> |.....................| 0.7248 | 1.186 | 1.363 |...........| +#> | X|<span style='font-weight: bold;'> 289.63307</span> | 94.24 | 0.8008 | 7.778 | 2.147 | +#> <span style='text-decoration: underline;'>|.....................| 0.7248 | 1.186 | 1.363 |...........|</span> +#> |<span style='font-weight: bold;'> 18</span>| 289.44450 | 0.9972 | -0.9991 | -0.9468 | -0.7190 | +#> |.....................| -1.035 | -0.8473 | -0.7469 |...........| +#> | U| 289.4445 | 94.18 | -0.2217 | 2.053 | 2.146 | +#> |.....................| 0.7231 | 1.213 | 1.429 |...........| +#> | X|<span style='font-weight: bold;'> 289.4445</span> | 94.18 | 0.8011 | 7.794 | 2.146 | +#> <span style='text-decoration: underline;'>|.....................| 0.7231 | 1.213 | 1.429 |...........|</span> +#> | F| Forward Diff. | -36.76 | -0.05208 | -0.1861 | -9.057 | +#> <span style='text-decoration: underline;'>|.....................| 2.429 | -0.6853 | -1.924 |...........|</span> +#> |<span style='font-weight: bold;'> 19</span>| 288.93351 | 0.9984 | -0.9961 | -0.9370 | -0.6306 | +#> |.....................| -1.080 | -0.9120 | -0.7149 |...........| +#> | U| 288.93351 | 94.29 | -0.2187 | 2.063 | 2.231 | +#> |.....................| 0.6885 | 1.143 | 1.466 |...........| +#> | X|<span style='font-weight: bold;'> 288.93351</span> | 94.29 | 0.8035 | 7.871 | 2.231 | +#> <span style='text-decoration: underline;'>|.....................| 0.6885 | 1.143 | 1.466 |...........|</span> +#> | F| Forward Diff. | -14.48 | -0.02726 | 0.2181 | -3.062 | +#> <span style='text-decoration: underline;'>|.....................| -0.1976 | -4.306 | -0.8806 |...........|</span> +#> |<span style='font-weight: bold;'> 20</span>| 288.85238 | 1.002 | -0.9934 | -0.9444 | -0.5654 | +#> |.....................| -1.062 | -0.8288 | -0.7747 |...........| +#> | U| 288.85238 | 94.67 | -0.2160 | 2.056 | 2.293 | +#> |.....................| 0.7024 | 1.233 | 1.396 |...........| +#> | X|<span style='font-weight: bold;'> 288.85238</span> | 94.67 | 0.8057 | 7.813 | 2.293 | +#> <span style='text-decoration: underline;'>|.....................| 0.7024 | 1.233 | 1.396 |...........|</span> +#> | F| Forward Diff. | 40.49 | 0.1537 | 0.2940 | 0.6524 | +#> <span style='text-decoration: underline;'>|.....................| 0.4942 | 0.3489 | -3.099 |...........|</span> +#> |<span style='font-weight: bold;'> 21</span>| 289.09335 | 0.9960 | -1.025 | -1.050 | -0.5645 | +#> |.....................| -1.111 | -0.8117 | -0.7552 |...........| +#> | U| 289.09335 | 94.07 | -0.2476 | 1.951 | 2.294 | +#> |.....................| 0.6648 | 1.251 | 1.419 |...........| +#> | X|<span style='font-weight: bold;'> 289.09335</span> | 94.07 | 0.7806 | 7.034 | 2.294 | +#> <span style='text-decoration: underline;'>|.....................| 0.6648 | 1.251 | 1.419 |...........|</span> +#> |<span style='font-weight: bold;'> 22</span>| 288.97418 | 0.9945 | -1.003 | -0.9755 | -0.5652 | +#> |.....................| -1.076 | -0.8238 | -0.7685 |...........| +#> | U| 288.97418 | 93.92 | -0.2254 | 2.025 | 2.294 | +#> |.....................| 0.6912 | 1.238 | 1.404 |...........| +#> | X|<span style='font-weight: bold;'> 288.97418</span> | 93.92 | 0.7982 | 7.574 | 2.294 | +#> <span style='text-decoration: underline;'>|.....................| 0.6912 | 1.238 | 1.404 |...........|</span> +#> |<span style='font-weight: bold;'> 23</span>| 288.99640 | 0.9941 | -0.9963 | -0.9538 | -0.5655 | +#> |.....................| -1.066 | -0.8273 | -0.7723 |...........| +#> | U| 288.9964 | 93.88 | -0.2189 | 2.046 | 2.293 | +#> |.....................| 0.6990 | 1.235 | 1.399 |...........| +#> | X|<span style='font-weight: bold;'> 288.9964</span> | 93.88 | 0.8034 | 7.740 | 2.293 | +#> <span style='text-decoration: underline;'>|.....................| 0.6990 | 1.235 | 1.399 |...........|</span> +#> |<span style='font-weight: bold;'> 24</span>| 288.82158 | 0.9975 | -0.9934 | -0.9445 | -0.5655 | +#> |.....................| -1.062 | -0.8288 | -0.7743 |...........| +#> | U| 288.82158 | 94.20 | -0.2160 | 2.056 | 2.293 | +#> |.....................| 0.7023 | 1.233 | 1.397 |...........| +#> | X|<span style='font-weight: bold;'> 288.82158</span> | 94.20 | 0.8057 | 7.813 | 2.293 | +#> <span style='text-decoration: underline;'>|.....................| 0.7023 | 1.233 | 1.397 |...........|</span> +#> | F| Forward Diff. | -27.98 | 0.07663 | -0.09902 | 0.6250 | +#> <span style='text-decoration: underline;'>|.....................| 0.3387 | 0.3777 | -3.049 |...........|</span> +#> |<span style='font-weight: bold;'> 25</span>| 288.78525 | 0.9995 | -0.9943 | -0.9465 | -0.5657 | +#> |.....................| -1.059 | -0.8303 | -0.7716 |...........| +#> | U| 288.78525 | 94.39 | -0.2169 | 2.054 | 2.293 | +#> |.....................| 0.7042 | 1.231 | 1.400 |...........| +#> | X|<span style='font-weight: bold;'> 288.78525</span> | 94.39 | 0.8050 | 7.797 | 2.293 | +#> <span style='text-decoration: underline;'>|.....................| 0.7042 | 1.231 | 1.400 |...........|</span> +#> | F| Forward Diff. | -0.7037 | 0.08814 | -0.009566 | 0.5597 | +#> <span style='text-decoration: underline;'>|.....................| 0.2999 | 0.2778 | -2.968 |...........|</span> +#> |<span style='font-weight: bold;'> 26</span>| 288.77680 | 1.000 | -0.9946 | -0.9467 | -0.5664 | +#> |.....................| -1.059 | -0.8311 | -0.7670 |...........| +#> | U| 288.7768 | 94.48 | -0.2172 | 2.053 | 2.292 | +#> |.....................| 0.7047 | 1.231 | 1.405 |...........| +#> | X|<span style='font-weight: bold;'> 288.7768</span> | 94.48 | 0.8048 | 7.795 | 2.292 | +#> <span style='text-decoration: underline;'>|.....................| 0.7047 | 1.231 | 1.405 |...........|</span> +#> | F| Forward Diff. | 12.46 | 0.09472 | 0.05753 | 0.4960 | +#> <span style='text-decoration: underline;'>|.....................| 0.3156 | 0.2411 | -2.796 |...........|</span> +#> |<span style='font-weight: bold;'> 27</span>| 288.76499 | 0.9995 | -0.9954 | -0.9482 | -0.5665 | +#> |.....................| -1.055 | -0.8326 | -0.7642 |...........| +#> | U| 288.76499 | 94.39 | -0.2180 | 2.052 | 2.292 | +#> |.....................| 0.7071 | 1.229 | 1.409 |...........| +#> | X|<span style='font-weight: bold;'> 288.76499</span> | 94.39 | 0.8042 | 7.783 | 2.292 | +#> <span style='text-decoration: underline;'>|.....................| 0.7071 | 1.229 | 1.409 |...........|</span> +#> | F| Forward Diff. | -0.8358 | 0.06465 | -0.06858 | 0.5747 | +#> <span style='text-decoration: underline;'>|.....................| 0.6430 | 0.1630 | -2.683 |...........|</span> +#> |<span style='font-weight: bold;'> 28</span>| 288.75697 | 1.000 | -0.9957 | -0.9484 | -0.5681 | +#> |.....................| -1.059 | -0.8325 | -0.7609 |...........| +#> | U| 288.75697 | 94.45 | -0.2183 | 2.052 | 2.291 | +#> |.....................| 0.7046 | 1.229 | 1.413 |...........| +#> | X|<span style='font-weight: bold;'> 288.75697</span> | 94.45 | 0.8039 | 7.782 | 2.291 | +#> <span style='text-decoration: underline;'>|.....................| 0.7046 | 1.229 | 1.413 |...........|</span> +#> | F| Forward Diff. | 8.673 | 0.06496 | -0.02049 | 0.4885 | +#> <span style='text-decoration: underline;'>|.....................| 0.5066 | 0.1747 | -2.560 |...........|</span> +#> |<span style='font-weight: bold;'> 29</span>| 288.75050 | 0.9994 | -0.9958 | -0.9480 | -0.5696 | +#> |.....................| -1.063 | -0.8317 | -0.7600 |...........| +#> | U| 288.7505 | 94.38 | -0.2184 | 2.052 | 2.289 | +#> |.....................| 0.7012 | 1.230 | 1.414 |...........| +#> | X|<span style='font-weight: bold;'> 288.7505</span> | 94.38 | 0.8038 | 7.785 | 2.289 | +#> <span style='text-decoration: underline;'>|.....................| 0.7012 | 1.230 | 1.414 |...........|</span> +#> | F| Forward Diff. | -2.463 | 0.04955 | -0.07455 | 0.3979 | +#> <span style='text-decoration: underline;'>|.....................| 0.1788 | 0.2263 | -2.511 |...........|</span> +#> |<span style='font-weight: bold;'> 30</span>| 288.74110 | 0.9997 | -0.9954 | -0.9459 | -0.5705 | +#> |.....................| -1.061 | -0.8331 | -0.7562 |...........| +#> | U| 288.7411 | 94.41 | -0.2180 | 2.054 | 2.289 | +#> |.....................| 0.7025 | 1.228 | 1.418 |...........| +#> | X|<span style='font-weight: bold;'> 288.7411</span> | 94.41 | 0.8041 | 7.801 | 2.289 | +#> <span style='text-decoration: underline;'>|.....................| 0.7025 | 1.228 | 1.418 |...........|</span> +#> |<span style='font-weight: bold;'> 31</span>| 288.72064 | 0.9993 | -0.9939 | -0.9392 | -0.5730 | +#> |.....................| -1.056 | -0.8374 | -0.7455 |...........| +#> | U| 288.72064 | 94.37 | -0.2166 | 2.061 | 2.286 | +#> |.....................| 0.7068 | 1.224 | 1.431 |...........| +#> | X|<span style='font-weight: bold;'> 288.72064</span> | 94.37 | 0.8053 | 7.854 | 2.286 | +#> <span style='text-decoration: underline;'>|.....................| 0.7068 | 1.224 | 1.431 |...........|</span> +#> |<span style='font-weight: bold;'> 32</span>| 288.70690 | 0.9989 | -0.9915 | -0.9277 | -0.5774 | +#> |.....................| -1.046 | -0.8449 | -0.7267 |...........| +#> | U| 288.7069 | 94.33 | -0.2141 | 2.072 | 2.282 | +#> |.....................| 0.7141 | 1.216 | 1.453 |...........| +#> | X|<span style='font-weight: bold;'> 288.7069</span> | 94.33 | 0.8073 | 7.944 | 2.282 | +#> <span style='text-decoration: underline;'>|.....................| 0.7141 | 1.216 | 1.453 |...........|</span> +#> | F| Forward Diff. | -8.246 | 0.08782 | 0.6230 | -0.2261 | +#> <span style='text-decoration: underline;'>|.....................| 0.9054 | -0.5290 | -1.268 |...........|</span> +#> |<span style='font-weight: bold;'> 33</span>| 288.68146 | 1.000 | -0.9932 | -0.9567 | -0.5899 | +#> |.....................| -1.067 | -0.8479 | -0.7019 |...........| +#> | U| 288.68146 | 94.46 | -0.2158 | 2.043 | 2.270 | +#> |.....................| 0.6982 | 1.212 | 1.481 |...........| +#> | X|<span style='font-weight: bold;'> 288.68146</span> | 94.46 | 0.8059 | 7.717 | 2.270 | +#> <span style='text-decoration: underline;'>|.....................| 0.6982 | 1.212 | 1.481 |...........|</span> +#> | F| Forward Diff. | 8.603 | 0.1068 | -0.4021 | -0.6499 | +#> <span style='text-decoration: underline;'>|.....................| 0.1745 | -0.5873 | -0.4459 |...........|</span> +#> |<span style='font-weight: bold;'> 34</span>| 288.70236 | 1.001 | -1.018 | -0.9264 | -0.5930 | +#> |.....................| -1.088 | -0.8392 | -0.6985 |...........| +#> | U| 288.70236 | 94.50 | -0.2403 | 2.074 | 2.267 | +#> |.....................| 0.6822 | 1.222 | 1.485 |...........| +#> | X|<span style='font-weight: bold;'> 288.70236</span> | 94.50 | 0.7864 | 7.955 | 2.267 | +#> <span style='text-decoration: underline;'>|.....................| 0.6822 | 1.222 | 1.485 |...........|</span> +#> |<span style='font-weight: bold;'> 35</span>| 288.67546 | 0.9997 | -0.9992 | -0.9493 | -0.5906 | +#> |.....................| -1.072 | -0.8457 | -0.7010 |...........| +#> | U| 288.67546 | 94.41 | -0.2218 | 2.051 | 2.269 | +#> |.....................| 0.6943 | 1.215 | 1.482 |...........| +#> | X|<span style='font-weight: bold;'> 288.67546</span> | 94.41 | 0.8011 | 7.775 | 2.269 | +#> <span style='text-decoration: underline;'>|.....................| 0.6943 | 1.215 | 1.482 |...........|</span> +#> | F| Forward Diff. | 1.309 | -0.03968 | -0.1448 | -0.6596 | +#> <span style='text-decoration: underline;'>|.....................| 0.05856 | -0.4617 | -0.3123 |...........|</span> +#> |<span style='font-weight: bold;'> 36</span>| 288.67323 | 0.9995 | -0.9891 | -0.9462 | -0.5890 | +#> |.....................| -1.074 | -0.8436 | -0.6999 |...........| +#> | U| 288.67323 | 94.40 | -0.2117 | 2.054 | 2.271 | +#> |.....................| 0.6929 | 1.217 | 1.484 |...........| +#> | X|<span style='font-weight: bold;'> 288.67323</span> | 94.40 | 0.8092 | 7.800 | 2.271 | +#> <span style='text-decoration: underline;'>|.....................| 0.6929 | 1.217 | 1.484 |...........|</span> +#> | F| Forward Diff. | -0.3529 | 0.1695 | -0.04594 | -0.6688 | +#> <span style='text-decoration: underline;'>|.....................| -0.2932 | -0.3576 | -0.2566 |...........|</span> +#> |<span style='font-weight: bold;'> 37</span>| 288.67323 | 0.9995 | -0.9891 | -0.9462 | -0.5890 | +#> |.....................| -1.074 | -0.8436 | -0.6999 |...........| +#> | U| 288.67323 | 94.40 | -0.2117 | 2.054 | 2.271 | +#> |.....................| 0.6929 | 1.217 | 1.484 |...........| +#> | X|<span style='font-weight: bold;'> 288.67323</span> | 94.40 | 0.8092 | 7.800 | 2.271 | +#> <span style='text-decoration: underline;'>|.....................| 0.6929 | 1.217 | 1.484 |...........|</span> +#> calculating covariance matrix +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate and covariance; see $scaleInfo</span></div><div class='input'> +<span class='va'>f_nlmixr_dfop_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> 1: 93.2375 -1.6690 -4.0126 0.0336 3.3441 0.9789 2.1220 0.5342 18.1447 +#> 2: 92.9778 -1.6369 -3.9297 0.0067 3.1769 1.2515 2.0460 0.5166 11.1022 +#> 3: 92.9382 -1.6747 -3.9496 -0.0050 3.0181 1.1889 1.9437 0.4908 9.5980 +#> 4: 93.4481 -1.8083 -3.9734 -0.0250 2.8672 1.1295 1.8797 0.4662 8.6240 +#> 5: 93.4584 -1.8288 -4.0221 0.0414 2.7238 1.0730 1.8467 0.5161 8.1404 +#> 6: 93.7533 -1.8675 -4.0215 0.0158 2.5876 1.0194 1.8017 0.4911 7.5848 +#> 7: 93.6006 -1.8542 -4.0241 -0.0026 2.4582 0.9684 1.7860 0.4916 7.0796 +#> 8: 93.6918 -1.8416 -3.9940 0.0121 2.3353 0.9200 1.7061 0.4681 6.9985 +#> 9: 93.4789 -1.8738 -3.9845 0.0318 3.1307 0.8740 1.7845 0.4553 6.8335 +#> 10: 93.6048 -1.8723 -4.0154 0.0112 3.1962 0.8303 1.7434 0.4325 7.0681 +#> 11: 93.5135 -1.8675 -3.9905 0.0295 3.2177 0.7888 1.6910 0.4619 6.9572 +#> 12: 93.4407 -1.8790 -3.9877 0.0509 3.4194 0.7493 1.6324 0.5060 6.5755 +#> 13: 93.5033 -1.9250 -4.0416 0.0734 3.2485 0.7295 1.7369 0.4807 6.3881 +#> 14: 93.4276 -1.9082 -4.0516 0.0558 3.0860 0.7281 1.7241 0.4567 5.9840 +#> 15: 93.3041 -1.9256 -4.0718 0.0854 3.4389 0.7293 1.7446 0.4524 5.8195 +#> 16: 93.2979 -1.9297 -4.0624 0.0730 3.2670 0.7239 1.7476 0.4298 5.7629 +#> 17: 93.3522 -1.9570 -4.0876 0.1304 3.3053 0.7020 1.7402 0.4083 5.6926 +#> 18: 93.3500 -1.9652 -4.0816 0.1350 3.1400 0.7130 1.7217 0.3879 5.5714 +#> 19: 93.3822 -1.9519 -4.0961 0.1322 2.9830 0.7087 1.7228 0.3745 5.4176 +#> 20: 93.2823 -1.9490 -4.0841 0.1238 2.8339 0.6988 1.7659 0.3753 5.5279 +#> 21: 93.5951 -1.9298 -4.0874 0.1345 2.6922 0.6665 1.7724 0.3645 5.4414 +#> 22: 93.5052 -1.9469 -4.0739 0.1260 3.1244 0.6776 1.7629 0.3618 5.5395 +#> 23: 93.4734 -1.9952 -4.0909 0.1472 3.0340 0.7225 1.8104 0.3437 5.5072 +#> 24: 93.8816 -1.9639 -4.0914 0.1511 2.8824 0.7215 1.8586 0.3324 5.6009 +#> 25: 93.5874 -1.9750 -4.1026 0.1296 2.7383 0.7178 1.8209 0.3680 5.6274 +#> 26: 93.4057 -1.9316 -4.0922 0.1224 3.8103 0.7331 1.7796 0.3639 5.6861 +#> 27: 93.5013 -1.9188 -4.0698 0.0758 3.7127 0.7670 1.8750 0.3457 5.6624 +#> 28: 93.5703 -1.9523 -4.0758 0.0731 4.6390 0.7489 1.8583 0.3445 5.8077 +#> 29: 93.4694 -1.9559 -4.0566 0.0444 5.1290 0.8062 1.9344 0.3273 5.8688 +#> 30: 93.2290 -1.9824 -4.0475 0.0674 4.8726 0.8702 2.0343 0.3109 5.7579 +#> 31: 93.8652 -1.9771 -4.0510 0.0679 4.6289 0.8565 2.0529 0.2954 5.5526 +#> 32: 93.5854 -1.9573 -4.0510 0.0643 5.1320 0.8417 2.0138 0.2806 5.4199 +#> 33: 93.9870 -1.9503 -4.0513 0.0542 4.8754 0.8412 2.0433 0.2666 5.6945 +#> 34: 93.6884 -1.9172 -4.0633 0.0556 4.6317 0.8847 2.0861 0.2702 5.2687 +#> 35: 94.0375 -1.9365 -4.0576 0.0753 5.2320 0.8404 2.0791 0.2582 5.2760 +#> 36: 94.1588 -1.9423 -4.0499 0.0792 4.9704 0.8221 2.1145 0.2669 5.2050 +#> 37: 93.8626 -1.9356 -4.0538 0.0591 5.2723 0.8360 2.1407 0.2536 5.3218 +#> 38: 93.7237 -1.9357 -4.0611 0.0543 5.0087 0.8361 2.0788 0.2710 5.2866 +#> 39: 93.6513 -1.9327 -4.0408 0.0712 4.7582 0.8408 2.0051 0.2899 5.4693 +#> 40: 93.4619 -1.9634 -4.0360 0.1232 4.5203 0.8317 2.0367 0.3288 5.4324 +#> 41: 93.4809 -1.9601 -4.0351 0.1261 4.2943 0.8424 2.0081 0.3306 5.4573 +#> 42: 93.5851 -1.9745 -4.0428 0.1250 4.9744 0.8003 1.9818 0.3141 5.5168 +#> 43: 93.7820 -1.9597 -4.0401 0.1305 5.9118 0.7603 2.1332 0.2984 5.4899 +#> 44: 93.7419 -1.9509 -4.0495 0.1345 5.6162 0.7743 2.0459 0.2998 5.5344 +#> 45: 93.6967 -1.9366 -4.0522 0.1215 5.3354 0.7968 2.0566 0.2848 5.7738 +#> 46: 93.3665 -1.9553 -4.0018 0.0951 5.0686 0.7583 2.1124 0.2706 5.3850 +#> 47: 93.2974 -1.9332 -4.0091 0.0869 5.2792 0.8149 2.1009 0.2597 5.6743 +#> 48: 93.3967 -1.9540 -4.0218 0.0623 5.0152 0.8006 2.1538 0.2467 5.5889 +#> 49: 93.1652 -1.9724 -4.0350 0.0506 4.7645 0.8055 2.1445 0.2344 5.3586 +#> 50: 93.1464 -1.9377 -4.0185 0.0591 5.3658 0.8149 2.1523 0.2226 5.2483 +#> 51: 93.5217 -1.9246 -4.0272 0.0423 5.8579 0.8368 2.1596 0.2115 5.2746 +#> 52: 93.5512 -1.9257 -4.0204 0.0307 7.2345 0.8463 2.1903 0.2065 5.2405 +#> 53: 93.5400 -1.9428 -4.0300 0.0572 6.8728 0.8268 2.0807 0.2139 5.4127 +#> 54: 93.9868 -1.9502 -4.0129 0.0282 9.6651 0.8468 2.0823 0.2032 5.0396 +#> 55: 94.0505 -1.9393 -4.0073 0.0390 10.0994 0.8375 2.1018 0.2016 4.9147 +#> 56: 93.8010 -1.9493 -4.0026 0.0415 10.1741 0.8816 2.1117 0.2207 5.0723 +#> 57: 93.7596 -1.9762 -4.0154 0.0651 9.6654 0.8952 2.1662 0.2096 5.2311 +#> 58: 94.3399 -1.9353 -4.0095 0.0446 9.1821 0.9498 2.2103 0.1991 5.1009 +#> 59: 94.4036 -1.9283 -4.0279 0.0475 8.7230 0.9480 2.3209 0.1892 4.9930 +#> 60: 94.6395 -1.9260 -4.0348 0.0457 8.8651 0.9006 2.2565 0.1797 5.1751 +#> 61: 94.6499 -1.9291 -4.0216 0.0297 8.4218 0.9206 2.2220 0.1843 5.1124 +#> 62: 94.3847 -1.9010 -4.0300 0.0257 9.0591 0.9331 2.2795 0.1816 5.0834 +#> 63: 94.5510 -1.9120 -4.0116 0.0179 8.6061 0.9256 2.1791 0.1736 5.1513 +#> 64: 94.2510 -1.9213 -4.0184 0.0204 8.1758 0.9124 2.2131 0.1682 5.0698 +#> 65: 94.1173 -1.9044 -4.0279 0.0286 8.6773 0.9211 2.2202 0.1598 5.1120 +#> 66: 94.2093 -1.9098 -4.0206 0.0160 8.2435 0.9230 2.2475 0.1750 5.0175 +#> 67: 94.2814 -1.9339 -4.0041 0.0146 7.8313 0.9377 2.2350 0.1709 5.1478 +#> 68: 94.3001 -1.9079 -4.0127 -0.0103 7.4397 0.9163 2.2245 0.1640 5.2529 +#> 69: 94.3820 -1.9167 -4.0176 0.0296 7.0678 0.8704 2.2236 0.1888 5.2574 +#> 70: 94.2691 -1.9037 -4.0156 0.0388 6.7144 0.8601 2.1833 0.2128 5.0230 +#> 71: 94.3827 -1.9183 -4.0056 0.0485 6.3786 0.8491 2.2147 0.2345 5.1212 +#> 72: 94.3104 -1.9291 -4.0099 0.0330 6.0597 0.9007 2.2316 0.2255 5.3748 +#> 73: 94.1778 -1.9238 -4.0054 0.0222 5.7567 0.9479 2.2969 0.2142 5.2827 +#> 74: 94.1022 -1.9149 -4.0017 0.0497 5.4689 0.9305 2.3058 0.2035 5.3117 +#> 75: 94.2343 -1.9045 -4.0141 0.0189 5.1954 0.9141 2.3227 0.1933 5.1047 +#> 76: 94.0905 -1.9019 -4.0166 0.0170 5.5411 0.8978 2.3315 0.1836 5.1233 +#> 77: 94.2772 -1.9117 -4.0053 0.0584 5.2641 0.9238 2.3678 0.1866 4.9803 +#> 78: 94.7235 -1.9141 -4.0464 0.0758 5.0735 0.9308 2.3720 0.2062 5.0544 +#> 79: 94.4674 -1.9287 -4.0494 0.0724 5.7355 0.9063 2.3680 0.1959 5.0910 +#> 80: 93.9895 -1.9271 -4.0456 0.0366 7.2150 0.8857 2.4000 0.1861 5.0612 +#> 81: 94.3190 -1.9358 -4.0402 0.0506 7.5591 0.8891 2.3317 0.1814 4.8617 +#> 82: 94.1898 -1.9126 -4.0552 0.0595 7.6462 0.9157 2.3848 0.1854 4.7335 +#> 83: 94.2044 -1.9145 -4.0359 0.0295 7.8610 0.9451 2.4305 0.1871 4.9258 +#> 84: 93.8197 -1.9058 -3.9879 -0.0409 10.4218 0.9604 2.3848 0.2177 5.0619 +#> 85: 94.0219 -1.8957 -3.9753 -0.0441 9.9007 0.9637 2.4476 0.2219 5.0532 +#> 86: 94.0737 -1.8889 -3.9753 -0.0220 9.4056 0.9675 2.4476 0.2284 5.2694 +#> 87: 93.8548 -1.8755 -3.9707 -0.0024 8.9354 1.0066 2.4895 0.2340 5.4019 +#> 88: 93.7578 -1.9046 -3.9804 -0.0042 8.4886 0.9656 2.5006 0.2271 5.3724 +#> 89: 93.6848 -1.8936 -3.9689 -0.0396 10.6813 0.9805 2.4561 0.2254 5.2615 +#> 90: 93.3617 -1.9167 -3.9801 -0.0221 10.1472 1.0147 2.3589 0.2141 5.4193 +#> 91: 93.7419 -1.8964 -3.9888 -0.0363 9.6398 1.0077 2.3748 0.2066 5.3463 +#> 92: 93.8635 -1.8994 -3.9783 -0.0625 9.1578 1.0028 2.3282 0.2239 5.3026 +#> 93: 94.0864 -1.8648 -3.9426 -0.0813 8.8693 1.0348 2.3654 0.2127 5.2637 +#> 94: 93.9789 -1.8949 -3.9840 -0.0549 10.0871 1.0752 2.4551 0.2021 5.4225 +#> 95: 93.9008 -1.9141 -4.0080 -0.0644 9.8584 1.1599 2.4184 0.1920 5.2179 +#> 96: 93.6926 -2.0270 -3.8911 -0.0777 10.3968 1.1019 3.0518 0.1824 5.3163 +#> 97: 93.2478 -2.0074 -3.9034 -0.0427 10.7200 1.0468 2.9960 0.1732 5.5172 +#> 98: 93.4556 -2.0118 -3.9034 -0.0294 10.1840 1.0007 2.9960 0.1646 5.5887 +#> 99: 93.7548 -2.0076 -3.8894 -0.0157 9.7519 0.9507 3.0357 0.1569 5.7139 +#> 100: 93.8962 -2.0112 -3.8887 -0.0406 9.2643 0.9048 3.0369 0.1491 5.6145 +#> 101: 94.0889 -2.0221 -3.8612 -0.0145 8.8011 0.8728 3.1466 0.1499 5.4224 +#> 102: 94.5428 -2.0206 -3.8489 0.0115 8.3611 0.8292 3.1577 0.1473 5.6634 +#> 103: 94.4882 -2.0447 -3.8594 0.0514 7.9430 0.8202 3.1812 0.1562 5.5136 +#> 104: 94.3185 -2.0389 -3.8584 0.0258 8.3364 0.8346 3.1801 0.1484 5.3612 +#> 105: 94.2858 -2.0345 -3.8738 -0.0001 10.6008 0.8415 3.2251 0.1410 5.3359 +#> 106: 94.1264 -2.0415 -3.8756 0.0411 10.0707 0.8554 3.2182 0.1658 5.2280 +#> 107: 93.9801 -2.0574 -3.8674 0.0403 10.0269 0.8807 3.2628 0.1744 5.0299 +#> 108: 93.6911 -2.0295 -3.8693 0.0355 9.5255 0.8683 3.2708 0.1803 5.1880 +#> 109: 94.0646 -2.0260 -3.8806 0.0506 9.0493 0.8729 3.3140 0.1759 5.1927 +#> 110: 94.4591 -2.0378 -3.8962 0.0360 8.5968 0.8890 3.3076 0.1675 4.8961 +#> 111: 94.3748 -2.0319 -3.9053 0.0397 8.1670 0.8995 3.3254 0.1591 4.8066 +#> 112: 94.2370 -2.0338 -3.9017 0.0603 7.7586 0.8545 3.2484 0.1512 4.8856 +#> 113: 94.1242 -2.0237 -3.8954 0.0795 7.3707 0.8980 3.2127 0.1530 5.1859 +#> 114: 94.1452 -2.0298 -3.9197 0.0530 7.0021 0.8771 3.0744 0.1628 5.1303 +#> 115: 94.1403 -2.0410 -3.9093 0.0476 6.9173 0.9383 3.0223 0.1621 5.2563 +#> 116: 94.1612 -2.0424 -3.9063 0.0593 7.6367 0.8914 3.0420 0.1856 5.1566 +#> 117: 94.2018 -2.0488 -3.9041 0.0539 7.2549 0.8549 3.0204 0.1796 5.2119 +#> 118: 94.1315 -2.0579 -3.9139 0.0564 6.8922 0.8121 3.0180 0.1948 5.0302 +#> 119: 93.7398 -2.0747 -3.9202 0.0570 6.7510 0.7838 3.0084 0.1906 5.0863 +#> 120: 93.5945 -2.0511 -3.9388 0.0534 6.4134 0.7885 3.0100 0.2128 5.0597 +#> 121: 93.9845 -2.0613 -3.9338 0.0568 6.0928 0.7793 2.9944 0.2022 5.3179 +#> 122: 93.7779 -2.0831 -3.9338 0.0630 5.7881 0.7778 2.9944 0.1921 5.2399 +#> 123: 93.9128 -2.0623 -3.9135 0.0493 5.4987 0.8329 2.9729 0.1825 5.0752 +#> 124: 93.5190 -2.0804 -3.9315 0.0538 5.2238 0.8581 3.0220 0.1733 4.9713 +#> 125: 93.7427 -2.0649 -3.9309 0.0499 4.9626 0.8431 3.0260 0.1882 5.0718 +#> 126: 9.3540e+01 -2.0238e+00 -3.9006e+00 -6.8989e-05 4.7145e+00 8.3548e-01 2.9498e+00 1.9993e-01 5.2080e+00 +#> 127: 93.4310 -2.0496 -3.8898 -0.0173 4.4788 0.8864 2.9614 0.2302 5.6432 +#> 128: 93.7512 -2.0285 -3.9180 -0.0096 4.2548 0.8653 3.0768 0.2312 5.3906 +#> 129: 93.6908 -2.0718 -3.9113 -0.0194 4.0421 0.9022 3.0506 0.2386 5.3278 +#> 130: 93.5805 -1.9753 -4.0480 0.0065 3.8400 1.0388 2.8980 0.2276 5.2583 +#> 131: 93.8050 -1.9501 -4.0447 0.0040 3.8738 1.0957 2.7531 0.2162 5.3026 +#> 132: 93.6470 -1.9322 -4.0411 0.0048 3.6801 1.0618 2.6155 0.2159 5.2552 +#> 133: 94.2927 -1.9445 -4.0067 -0.0040 5.6903 1.0378 2.5425 0.2094 5.2430 +#> 134: 94.2814 -1.9286 -4.0021 -0.0144 6.9123 1.1316 2.5172 0.1990 5.3877 +#> 135: 94.0440 -1.9285 -4.0415 0.0254 6.5667 1.1416 2.4394 0.1975 5.3248 +#> 136: 94.0122 -1.9256 -4.0542 0.0156 6.6147 1.1511 2.4728 0.1954 5.2109 +#> 137: 93.8613 -1.9095 -4.0629 -0.0007 6.2840 1.1789 2.5078 0.2045 5.2876 +#> 138: 93.7410 -1.9345 -4.0788 -0.0005 6.0718 1.1507 2.5026 0.2086 5.3284 +#> 139: 93.6437 -1.9499 -4.0788 0.0159 5.7682 1.0932 2.5026 0.1982 5.4211 +#> 140: 93.4066 -1.9591 -4.0720 0.0472 6.9432 1.0883 2.4756 0.1947 5.4439 +#> 141: 93.6086 -1.9625 -4.1026 0.0785 7.7204 1.1027 2.3974 0.2084 5.6595 +#> 142: 93.8693 -1.9640 -4.1003 0.0670 10.1206 1.1196 2.2775 0.1980 5.4918 +#> 143: 93.6954 -1.9890 -4.0792 0.0824 9.6146 1.0636 2.3366 0.1881 5.2818 +#> 144: 93.5119 -1.9888 -4.0603 0.0645 9.1339 1.0557 2.3380 0.1787 5.3491 +#> 145: 93.3539 -1.9874 -4.0563 0.0764 8.6772 1.0340 2.3573 0.1697 5.4214 +#> 146: 93.2812 -1.9734 -4.0620 0.0674 8.4698 1.0504 2.3604 0.1641 5.5968 +#> 147: 93.8919 -1.9657 -4.0863 0.0596 8.0463 1.0288 2.4569 0.1668 5.3476 +#> 148: 93.7841 -1.9719 -4.0688 0.0880 9.4571 1.0719 2.4020 0.1692 5.1664 +#> 149: 93.6361 -1.9912 -4.0523 0.0895 8.9842 1.0183 2.5236 0.1671 5.5060 +#> 150: 93.6402 -1.9940 -4.0365 0.0730 9.1100 0.9674 2.3974 0.1669 5.5402 +#> 151: 93.4283 -1.9861 -4.0594 0.0805 8.6545 0.9567 2.4304 0.1652 5.3571 +#> 152: 93.7431 -1.9444 -4.0833 0.0612 9.2738 0.9789 2.3602 0.1571 5.0632 +#> 153: 93.7239 -1.9307 -4.0780 0.0780 8.9915 0.9995 2.3398 0.1600 5.1077 +#> 154: 94.0115 -1.9655 -4.0978 0.0859 9.0507 0.9894 2.3313 0.1628 5.2272 +#> 155: 94.3207 -1.9792 -4.0905 0.1114 8.5756 0.9988 2.3790 0.1873 5.0916 +#> 156: 94.3160 -1.9811 -4.0894 0.0906 5.0717 0.9968 2.3662 0.2003 4.9973 +#> 157: 94.3042 -1.9641 -4.1031 0.0966 5.1875 0.9911 2.3908 0.1943 4.9993 +#> 158: 94.0102 -1.9635 -4.1047 0.1003 5.2398 0.9834 2.3905 0.1809 5.2765 +#> 159: 94.5686 -2.0012 -4.1459 0.1212 6.8800 1.0317 2.5969 0.1215 5.3943 +#> 160: 94.2433 -1.9673 -4.1420 0.1165 8.0930 1.0286 2.5827 0.1092 5.2904 +#> 161: 94.1327 -1.9644 -4.1595 0.1196 9.5810 1.0786 2.7063 0.1123 5.1723 +#> 162: 94.0779 -1.9525 -4.1608 0.1103 6.6456 1.0562 2.7111 0.1277 5.0224 +#> 163: 94.0995 -1.9687 -4.1910 0.1320 8.2582 1.0701 2.8394 0.1232 5.1593 +#> 164: 94.4575 -1.9800 -4.1936 0.1208 6.4860 1.1603 2.8332 0.1254 5.1325 +#> 165: 94.3298 -1.9968 -4.1963 0.1506 5.7592 1.1484 2.9143 0.1196 5.3059 +#> 166: 94.2531 -1.9977 -4.1748 0.1566 5.3810 1.1262 2.8044 0.1142 5.2569 +#> 167: 94.4593 -1.9985 -4.1758 0.1435 7.0082 1.1247 2.8542 0.1125 5.4332 +#> 168: 94.0868 -2.0117 -4.2259 0.1345 7.5364 1.1395 3.0314 0.1137 5.2790 +#> 169: 93.7927 -2.0072 -4.2177 0.1276 6.7023 1.1292 3.0535 0.1135 5.1357 +#> 170: 93.8094 -2.0309 -4.2244 0.1298 6.7343 1.0975 3.2542 0.1065 5.2372 +#> 171: 93.7263 -2.0349 -4.2115 0.1204 8.2555 1.0626 3.2292 0.1020 5.4467 +#> 172: 93.3380 -2.0022 -4.2262 0.1193 6.6891 1.0822 3.2762 0.0989 5.3641 +#> 173: 93.5334 -2.0224 -4.2488 0.1145 6.0685 1.0328 3.4694 0.0978 5.4780 +#> 174: 93.1805 -2.0207 -4.2344 0.1025 6.1648 1.0612 3.2079 0.0976 5.2570 +#> 175: 93.3423 -2.0255 -4.1644 0.1070 5.9418 1.0701 2.8555 0.1059 5.3415 +#> 176: 93.3387 -2.0192 -4.1473 0.0786 4.7649 1.0508 2.9102 0.1101 5.3381 +#> 177: 93.4640 -2.0177 -4.1504 0.0709 4.5672 1.0590 2.9447 0.1103 5.3245 +#> 178: 93.4930 -2.0147 -4.1568 0.0777 4.5325 1.1063 2.7902 0.1247 5.2036 +#> 179: 93.7455 -2.0101 -4.1580 0.0823 4.2094 1.1020 2.8075 0.1246 5.1184 +#> 180: 93.4838 -1.9989 -4.1631 0.0868 3.6999 1.0782 2.8790 0.1280 5.2677 +#> 181: 93.5207 -1.9975 -4.1926 0.1013 4.5693 1.0706 2.9216 0.1375 5.3783 +#> 182: 93.6695 -2.0251 -4.1717 0.0809 3.8373 1.0341 2.9954 0.1328 5.3774 +#> 183: 93.7238 -2.0095 -4.1222 0.0861 3.8354 1.0138 2.7536 0.1512 5.2600 +#> 184: 93.7106 -2.0032 -4.1244 0.0853 4.1968 1.0250 2.6849 0.1590 5.1996 +#> 185: 93.2862 -2.0028 -4.1628 0.0743 5.4347 1.0373 2.6528 0.1640 5.3269 +#> 186: 93.5567 -2.0040 -4.1438 0.0807 6.5150 1.0562 2.6486 0.1589 5.4158 +#> 187: 93.7894 -2.0023 -4.1137 0.1288 5.1401 1.0207 2.5217 0.1745 5.6484 +#> 188: 93.4911 -1.8872 -4.2405 0.1324 4.3165 0.8176 2.2483 0.1870 5.5214 +#> 189: 93.9184 -1.8982 -4.2936 0.1606 3.7995 0.8383 2.2555 0.1766 5.6320 +#> 190: 93.7487 -1.8878 -4.2872 0.1651 3.6764 0.8860 2.2088 0.1748 5.4829 +#> 191: 93.8940 -1.8715 -4.3244 0.1650 2.8119 0.9024 2.1141 0.1903 5.7768 +#> 192: 93.9378 -1.9105 -4.3010 0.1954 2.5239 0.8232 2.1331 0.1831 5.8507 +#> 193: 94.5609 -1.8766 -4.3303 0.2042 3.9595 0.8413 2.0662 0.2095 5.6119 +#> 194: 94.7465 -1.9036 -4.3363 0.2112 5.0784 0.8176 2.1071 0.2149 5.6051 +#> 195: 94.4761 -1.8852 -4.3375 0.2021 4.7026 0.7615 2.0556 0.2333 5.3997 +#> 196: 93.7678 -1.9037 -4.3676 0.2273 5.6976 0.7824 2.1487 0.2478 5.2531 +#> 197: 94.0788 -1.9208 -4.3670 0.2203 3.8352 0.7644 2.0893 0.2354 5.2196 +#> 198: 94.3424 -1.8825 -4.3288 0.2075 4.9447 0.7304 1.9525 0.2502 5.1387 +#> 199: 94.0613 -1.9911 -4.1676 0.2379 3.6248 0.6126 2.8184 0.2801 5.3421 +#> 200: 94.4814 -2.0045 -4.1782 0.2245 3.5637 0.6427 2.7132 0.3014 5.3984 +#> 201: 94.3903 -1.9973 -4.1773 0.2165 3.4686 0.6525 2.7040 0.2901 5.4178 +#> 202: 94.1840 -1.9928 -4.1742 0.2117 3.6920 0.6576 2.7046 0.2870 5.3743 +#> 203: 94.1832 -1.9865 -4.1670 0.2025 3.8180 0.6618 2.7097 0.2758 5.3389 +#> 204: 94.1550 -1.9832 -4.1631 0.1955 3.9449 0.6613 2.6998 0.2691 5.2948 +#> 205: 94.1853 -1.9824 -4.1602 0.1948 4.1753 0.6598 2.6909 0.2695 5.2556 +#> 206: 94.1775 -1.9800 -4.1564 0.1918 4.1962 0.6581 2.6778 0.2678 5.2316 +#> 207: 94.1754 -1.9736 -4.1532 0.1864 4.2107 0.6580 2.6645 0.2694 5.2553 +#> 208: 94.1591 -1.9695 -4.1498 0.1811 4.2621 0.6596 2.6537 0.2712 5.2543 +#> 209: 94.1225 -1.9675 -4.1454 0.1744 4.1977 0.6651 2.6519 0.2687 5.3075 +#> 210: 94.1047 -1.9628 -4.1424 0.1666 4.1981 0.6663 2.6570 0.2717 5.3160 +#> 211: 94.1161 -1.9587 -4.1398 0.1600 4.1858 0.6674 2.6614 0.2728 5.3307 +#> 212: 94.0976 -1.9551 -4.1379 0.1529 4.2002 0.6693 2.6737 0.2709 5.3288 +#> 213: 94.0845 -1.9511 -4.1365 0.1449 4.1381 0.6710 2.6727 0.2680 5.3322 +#> 214: 94.0582 -1.9493 -4.1351 0.1394 4.0630 0.6733 2.6729 0.2663 5.3504 +#> 215: 94.0449 -1.9493 -4.1338 0.1340 3.9607 0.6733 2.6719 0.2641 5.3681 +#> 216: 94.0030 -1.9496 -4.1321 0.1299 4.0200 0.6742 2.6727 0.2622 5.3619 +#> 217: 93.9560 -1.9514 -4.1315 0.1267 4.0642 0.6778 2.6764 0.2612 5.3584 +#> 218: 93.9485 -1.9520 -4.1297 0.1235 4.1822 0.6795 2.6745 0.2599 5.3471 +#> 219: 93.9650 -1.9523 -4.1289 0.1211 4.3244 0.6807 2.6851 0.2591 5.3531 +#> 220: 93.9961 -1.9519 -4.1284 0.1193 4.4276 0.6837 2.6936 0.2577 5.3528 +#> 221: 94.0080 -1.9517 -4.1275 0.1183 4.5303 0.6866 2.6979 0.2578 5.3538 +#> 222: 94.0143 -1.9505 -4.1272 0.1159 4.5882 0.6887 2.7039 0.2570 5.3489 +#> 223: 94.0189 -1.9491 -4.1269 0.1138 4.5674 0.6910 2.7092 0.2562 5.3424 +#> 224: 94.0136 -1.9464 -4.1270 0.1126 4.5582 0.6923 2.7161 0.2548 5.3421 +#> 225: 94.0118 -1.9444 -4.1276 0.1112 4.6000 0.6929 2.7269 0.2533 5.3525 +#> 226: 93.9884 -1.9428 -4.1260 0.1099 4.6720 0.6935 2.7428 0.2530 5.3427 +#> 227: 93.9657 -1.9416 -4.1247 0.1097 4.7197 0.6937 2.7581 0.2529 5.3455 +#> 228: 93.9586 -1.9410 -4.1234 0.1105 4.7731 0.6945 2.7801 0.2528 5.3408 +#> 229: 93.9574 -1.9409 -4.1215 0.1102 4.7898 0.6963 2.7970 0.2518 5.3366 +#> 230: 93.9495 -1.9410 -4.1201 0.1096 4.7966 0.6982 2.8117 0.2505 5.3301 +#> 231: 93.9378 -1.9416 -4.1193 0.1093 4.7947 0.6993 2.8274 0.2492 5.3270 +#> 232: 93.9362 -1.9421 -4.1184 0.1086 4.8132 0.7011 2.8411 0.2477 5.3191 +#> 233: 93.9412 -1.9424 -4.1167 0.1074 4.8188 0.7028 2.8514 0.2459 5.3134 +#> 234: 93.9436 -1.9424 -4.1152 0.1061 4.7865 0.7040 2.8618 0.2440 5.3153 +#> 235: 93.9413 -1.9425 -4.1134 0.1051 4.8017 0.7062 2.8679 0.2426 5.3137 +#> 236: 93.9480 -1.9423 -4.1119 0.1033 4.8537 0.7085 2.8730 0.2416 5.3089 +#> 237: 93.9560 -1.9408 -4.1105 0.1020 4.9091 0.7098 2.8777 0.2411 5.2970 +#> 238: 93.9610 -1.9393 -4.1091 0.1003 4.9394 0.7113 2.8824 0.2409 5.2902 +#> 239: 93.9634 -1.9378 -4.1080 0.0993 4.9304 0.7121 2.8875 0.2407 5.2868 +#> 240: 93.9727 -1.9360 -4.1063 0.0980 4.9651 0.7128 2.8918 0.2404 5.2825 +#> 241: 93.9736 -1.9348 -4.1045 0.0969 5.0080 0.7139 2.8917 0.2395 5.2751 +#> 242: 93.9779 -1.9334 -4.1030 0.0959 5.0856 0.7150 2.8923 0.2389 5.2656 +#> 243: 93.9807 -1.9322 -4.1015 0.0953 5.1490 0.7158 2.8929 0.2385 5.2560 +#> 244: 93.9858 -1.9317 -4.0998 0.0942 5.2172 0.7171 2.8922 0.2380 5.2514 +#> 245: 93.9798 -1.9309 -4.0984 0.0920 5.2903 0.7172 2.8892 0.2383 5.2502 +#> 246: 93.9782 -1.9296 -4.0971 0.0903 5.3132 0.7180 2.8866 0.2384 5.2482 +#> 247: 93.9809 -1.9290 -4.0958 0.0886 5.3342 0.7188 2.8839 0.2386 5.2466 +#> 248: 93.9731 -1.9281 -4.0944 0.0873 5.3438 0.7187 2.8812 0.2393 5.2480 +#> 249: 93.9594 -1.9273 -4.0932 0.0852 5.3449 0.7181 2.8781 0.2401 5.2489 +#> 250: 93.9508 -1.9261 -4.0919 0.0835 5.3194 0.7173 2.8752 0.2406 5.2495 +#> 251: 93.9421 -1.9248 -4.0903 0.0812 5.3051 0.7180 2.8714 0.2410 5.2480 +#> 252: 93.9291 -1.9240 -4.0888 0.0793 5.3122 0.7175 2.8681 0.2415 5.2447 +#> 253: 93.9233 -1.9232 -4.0876 0.0777 5.3289 0.7170 2.8636 0.2420 5.2423 +#> 254: 93.9189 -1.9217 -4.0863 0.0760 5.3708 0.7165 2.8593 0.2425 5.2395 +#> 255: 93.9130 -1.9205 -4.0850 0.0743 5.4093 0.7157 2.8548 0.2428 5.2393 +#> 256: 93.9031 -1.9195 -4.0837 0.0731 5.4400 0.7153 2.8501 0.2432 5.2417 +#> 257: 93.9079 -1.9183 -4.0821 0.0720 5.4612 0.7138 2.8454 0.2434 5.2469 +#> 258: 93.9117 -1.9173 -4.0807 0.0711 5.4979 0.7126 2.8412 0.2439 5.2491 +#> 259: 93.9199 -1.9164 -4.0797 0.0708 5.5145 0.7107 2.8364 0.2449 5.2481 +#> 260: 93.9300 -1.9150 -4.0782 0.0699 5.5067 0.7086 2.8316 0.2453 5.2501 +#> 261: 93.9382 -1.9140 -4.0768 0.0689 5.5191 0.7070 2.8271 0.2455 5.2518 +#> 262: 93.9467 -1.9126 -4.0755 0.0681 5.5261 0.7049 2.8227 0.2454 5.2564 +#> 263: 93.9594 -1.9110 -4.0739 0.0667 5.5365 0.7039 2.8196 0.2455 5.2613 +#> 264: 93.9697 -1.9096 -4.0718 0.0650 5.5589 0.7033 2.8174 0.2459 5.2628 +#> 265: 93.9784 -1.9080 -4.0698 0.0631 5.5668 0.7025 2.8153 0.2458 5.2627 +#> 266: 93.9865 -1.9068 -4.0686 0.0615 5.5819 0.7012 2.8114 0.2456 5.2638 +#> 267: 93.9940 -1.9055 -4.0673 0.0599 5.5887 0.7000 2.8076 0.2452 5.2644 +#> 268: 93.9991 -1.9045 -4.0660 0.0584 5.5989 0.6986 2.8039 0.2453 5.2657 +#> 269: 94.0034 -1.9036 -4.0649 0.0573 5.6276 0.6972 2.7990 0.2453 5.2648 +#> 270: 94.0104 -1.9028 -4.0639 0.0561 5.6456 0.6959 2.7945 0.2453 5.2614 +#> 271: 94.0190 -1.9022 -4.0629 0.0550 5.6409 0.6950 2.7900 0.2451 5.2606 +#> 272: 94.0244 -1.9017 -4.0623 0.0542 5.6452 0.6944 2.7863 0.2449 5.2626 +#> 273: 94.0312 -1.9010 -4.0620 0.0531 5.6581 0.6939 2.7821 0.2450 5.2620 +#> 274: 94.0387 -1.9004 -4.0615 0.0520 5.6569 0.6932 2.7774 0.2456 5.2657 +#> 275: 94.0381 -1.9000 -4.0611 0.0510 5.6525 0.6938 2.7727 0.2463 5.2662 +#> 276: 94.0426 -1.8994 -4.0606 0.0498 5.6664 0.6955 2.7682 0.2472 5.2687 +#> 277: 94.0437 -1.8988 -4.0604 0.0486 5.6705 0.6969 2.7646 0.2479 5.2699 +#> 278: 94.0470 -1.8982 -4.0606 0.0476 5.6495 0.6983 2.7620 0.2487 5.2741 +#> 279: 94.0475 -1.8980 -4.0608 0.0470 5.6561 0.6990 2.7590 0.2494 5.2749 +#> 280: 94.0485 -1.8977 -4.0609 0.0462 5.6510 0.6997 2.7565 0.2501 5.2755 +#> 281: 94.0473 -1.8975 -4.0609 0.0456 5.6493 0.6998 2.7529 0.2504 5.2764 +#> 282: 94.0448 -1.8972 -4.0608 0.0448 5.6523 0.7003 2.7495 0.2506 5.2773 +#> 283: 94.0392 -1.8975 -4.0608 0.0440 5.6543 0.7011 2.7463 0.2507 5.2772 +#> 284: 94.0315 -1.8976 -4.0609 0.0432 5.6575 0.7017 2.7431 0.2506 5.2792 +#> 285: 94.0262 -1.8980 -4.0611 0.0427 5.6632 0.7018 2.7402 0.2505 5.2805 +#> 286: 94.0255 -1.8986 -4.0615 0.0427 5.6683 0.7018 2.7371 0.2507 5.2795 +#> 287: 94.0234 -1.8992 -4.0619 0.0427 5.6533 0.7014 2.7340 0.2513 5.2803 +#> 288: 94.0227 -1.9000 -4.0631 0.0431 5.6485 0.7016 2.7352 0.2517 5.2802 +#> 289: 94.0179 -1.9008 -4.0641 0.0433 5.6553 0.7016 2.7358 0.2523 5.2808 +#> 290: 94.0135 -1.9017 -4.0650 0.0435 5.6776 0.7015 2.7363 0.2528 5.2839 +#> 291: 94.0101 -1.9025 -4.0660 0.0440 5.7028 0.7012 2.7372 0.2531 5.2883 +#> 292: 94.0066 -1.9034 -4.0672 0.0442 5.7277 0.7007 2.7369 0.2536 5.2890 +#> 293: 94.0002 -1.9042 -4.0681 0.0441 5.7462 0.7004 2.7366 0.2538 5.2906 +#> 294: 93.9917 -1.9049 -4.0690 0.0440 5.7707 0.7001 2.7363 0.2539 5.2927 +#> 295: 93.9864 -1.9055 -4.0703 0.0440 5.7816 0.7001 2.7362 0.2542 5.2950 +#> 296: 93.9807 -1.9060 -4.0716 0.0441 5.7884 0.7000 2.7362 0.2545 5.2974 +#> 297: 93.9749 -1.9063 -4.0729 0.0442 5.7926 0.7005 2.7362 0.2548 5.3032 +#> 298: 93.9700 -1.9070 -4.0735 0.0442 5.7850 0.7005 2.7323 0.2553 5.3067 +#> 299: 93.9668 -1.9075 -4.0740 0.0442 5.7688 0.7000 2.7293 0.2558 5.3100 +#> 300: 93.9654 -1.9080 -4.0742 0.0441 5.7541 0.6993 2.7260 0.2563 5.3123 +#> 301: 93.9678 -1.9082 -4.0744 0.0439 5.7383 0.6980 2.7217 0.2568 5.3165 +#> 302: 93.9687 -1.9087 -4.0747 0.0435 5.7262 0.6977 2.7175 0.2574 5.3179 +#> 303: 93.9675 -1.9090 -4.0751 0.0430 5.7050 0.6966 2.7137 0.2580 5.3197 +#> 304: 93.9641 -1.9092 -4.0755 0.0428 5.6977 0.6954 2.7097 0.2583 5.3215 +#> 305: 93.9624 -1.9095 -4.0759 0.0427 5.6986 0.6947 2.7061 0.2585 5.3200 +#> 306: 93.9623 -1.9098 -4.0763 0.0428 5.7065 0.6941 2.7025 0.2587 5.3174 +#> 307: 93.9635 -1.9105 -4.0767 0.0430 5.7229 0.6938 2.6992 0.2585 5.3153 +#> 308: 93.9658 -1.9112 -4.0778 0.0435 5.7340 0.6935 2.6992 0.2580 5.3131 +#> 309: 93.9671 -1.9119 -4.0784 0.0440 5.7510 0.6929 2.6990 0.2576 5.3113 +#> 310: 93.9669 -1.9124 -4.0791 0.0441 5.7560 0.6926 2.6988 0.2569 5.3128 +#> 311: 93.9670 -1.9129 -4.0795 0.0443 5.7557 0.6922 2.6972 0.2563 5.3134 +#> 312: 93.9689 -1.9132 -4.0799 0.0446 5.7554 0.6921 2.6959 0.2559 5.3125 +#> 313: 93.9685 -1.9136 -4.0806 0.0448 5.7489 0.6921 2.6960 0.2553 5.3110 +#> 314: 93.9673 -1.9138 -4.0812 0.0447 5.7562 0.6925 2.6964 0.2545 5.3107 +#> 315: 93.9635 -1.9139 -4.0818 0.0447 5.7392 0.6931 2.6971 0.2539 5.3127 +#> 316: 93.9581 -1.9139 -4.0823 0.0442 5.7376 0.6937 2.6974 0.2532 5.3140 +#> 317: 93.9541 -1.9140 -4.0826 0.0437 5.7426 0.6946 2.6968 0.2526 5.3155 +#> 318: 93.9521 -1.9141 -4.0829 0.0432 5.7378 0.6951 2.6970 0.2521 5.3158 +#> 319: 93.9520 -1.9139 -4.0829 0.0423 5.7366 0.6959 2.6977 0.2516 5.3138 +#> 320: 93.9538 -1.9136 -4.0828 0.0414 5.7416 0.6964 2.6980 0.2510 5.3135 +#> 321: 93.9557 -1.9132 -4.0827 0.0406 5.7539 0.6969 2.6983 0.2503 5.3141 +#> 322: 93.9568 -1.9130 -4.0825 0.0399 5.7460 0.6971 2.6988 0.2497 5.3155 +#> 323: 93.9594 -1.9125 -4.0824 0.0393 5.7274 0.6972 2.6993 0.2492 5.3166 +#> 324: 93.9608 -1.9122 -4.0823 0.0386 5.7161 0.6973 2.7006 0.2487 5.3156 +#> 325: 93.9601 -1.9120 -4.0822 0.0379 5.7036 0.6973 2.7019 0.2483 5.3161 +#> 326: 93.9602 -1.9118 -4.0822 0.0372 5.6817 0.6977 2.7023 0.2480 5.3182 +#> 327: 93.9615 -1.9115 -4.0820 0.0364 5.6682 0.6986 2.7024 0.2476 5.3203 +#> 328: 93.9601 -1.9114 -4.0814 0.0355 5.6746 0.6999 2.7012 0.2472 5.3224 +#> 329: 93.9580 -1.9112 -4.0809 0.0348 5.6670 0.7014 2.7003 0.2469 5.3229 +#> 330: 93.9577 -1.9111 -4.0808 0.0341 5.6613 0.7023 2.7007 0.2466 5.3224 +#> 331: 93.9570 -1.9109 -4.0808 0.0334 5.6607 0.7029 2.7020 0.2463 5.3223 +#> 332: 93.9599 -1.9106 -4.0806 0.0328 5.6610 0.7037 2.7023 0.2459 5.3212 +#> 333: 93.9638 -1.9102 -4.0806 0.0320 5.6751 0.7043 2.7029 0.2458 5.3187 +#> 334: 93.9672 -1.9096 -4.0805 0.0311 5.6801 0.7051 2.7033 0.2456 5.3168 +#> 335: 93.9714 -1.9093 -4.0805 0.0302 5.6855 0.7058 2.7038 0.2453 5.3156 +#> 336: 93.9755 -1.9090 -4.0804 0.0294 5.6979 0.7062 2.7040 0.2452 5.3158 +#> 337: 93.9796 -1.9088 -4.0803 0.0286 5.7025 0.7069 2.7038 0.2447 5.3159 +#> 338: 93.9845 -1.9087 -4.0803 0.0278 5.7100 0.7074 2.7042 0.2443 5.3166 +#> 339: 93.9889 -1.9084 -4.0803 0.0273 5.7123 0.7080 2.7045 0.2438 5.3165 +#> 340: 93.9916 -1.9082 -4.0801 0.0267 5.7289 0.7086 2.7045 0.2434 5.3167 +#> 341: 93.9938 -1.9080 -4.0800 0.0263 5.7602 0.7091 2.7048 0.2430 5.3173 +#> 342: 93.9971 -1.9076 -4.0799 0.0257 5.7951 0.7096 2.7046 0.2427 5.3171 +#> 343: 93.9979 -1.9073 -4.0794 0.0251 5.8156 0.7101 2.7044 0.2424 5.3157 +#> 344: 94.0015 -1.9070 -4.0792 0.0246 5.8378 0.7105 2.7047 0.2420 5.3153 +#> 345: 94.0040 -1.9067 -4.0789 0.0241 5.8559 0.7111 2.7046 0.2414 5.3149 +#> 346: 94.0073 -1.9066 -4.0787 0.0237 5.8810 0.7119 2.7045 0.2409 5.3131 +#> 347: 94.0084 -1.9066 -4.0785 0.0232 5.8815 0.7127 2.7044 0.2406 5.3125 +#> 348: 94.0084 -1.9067 -4.0785 0.0229 5.8870 0.7132 2.7051 0.2403 5.3110 +#> 349: 94.0079 -1.9068 -4.0785 0.0225 5.8882 0.7136 2.7048 0.2401 5.3127 +#> 350: 94.0075 -1.9067 -4.0785 0.0220 5.8857 0.7137 2.7045 0.2396 5.3133 +#> 351: 94.0068 -1.9068 -4.0786 0.0218 5.8849 0.7140 2.7041 0.2393 5.3135 +#> 352: 94.0059 -1.9067 -4.0788 0.0216 5.8778 0.7141 2.7039 0.2390 5.3139 +#> 353: 94.0073 -1.9067 -4.0792 0.0215 5.8709 0.7140 2.7047 0.2388 5.3129 +#> 354: 94.0078 -1.9065 -4.0795 0.0214 5.8623 0.7139 2.7054 0.2386 5.3135 +#> 355: 94.0065 -1.9064 -4.0795 0.0211 5.8637 0.7137 2.7048 0.2383 5.3122 +#> 356: 94.0080 -1.9063 -4.0796 0.0209 5.8613 0.7134 2.7041 0.2380 5.3121 +#> 357: 94.0105 -1.9061 -4.0797 0.0206 5.8613 0.7132 2.7036 0.2379 5.3119 +#> 358: 94.0114 -1.9059 -4.0798 0.0205 5.8539 0.7130 2.7029 0.2377 5.3107 +#> 359: 94.0154 -1.9058 -4.0799 0.0203 5.8559 0.7126 2.7024 0.2374 5.3112 +#> 360: 94.0165 -1.9057 -4.0800 0.0201 5.8544 0.7124 2.7020 0.2372 5.3099 +#> 361: 94.0198 -1.9056 -4.0802 0.0199 5.8511 0.7121 2.7018 0.2370 5.3089 +#> 362: 94.0224 -1.9054 -4.0811 0.0198 5.8509 0.7122 2.7071 0.2368 5.3077 +#> 363: 94.0241 -1.9053 -4.0821 0.0197 5.8582 0.7121 2.7135 0.2366 5.3073 +#> 364: 94.0254 -1.9052 -4.0824 0.0195 5.8606 0.7122 2.7147 0.2362 5.3079 +#> 365: 94.0276 -1.9052 -4.0831 0.0195 5.8668 0.7119 2.7197 0.2359 5.3081 +#> 366: 94.0276 -1.9052 -4.0836 0.0195 5.8765 0.7121 2.7217 0.2357 5.3074 +#> 367: 94.0276 -1.9051 -4.0842 0.0194 5.8627 0.7120 2.7240 0.2354 5.3083 +#> 368: 94.0292 -1.9050 -4.0847 0.0195 5.8579 0.7120 2.7254 0.2352 5.3096 +#> 369: 94.0289 -1.9049 -4.0852 0.0195 5.8590 0.7122 2.7271 0.2350 5.3095 +#> 370: 94.0300 -1.9049 -4.0855 0.0194 5.8712 0.7123 2.7284 0.2348 5.3094 +#> 371: 94.0309 -1.9050 -4.0858 0.0194 5.8766 0.7122 2.7295 0.2346 5.3095 +#> 372: 94.0306 -1.9050 -4.0860 0.0196 5.8800 0.7121 2.7306 0.2344 5.3101 +#> 373: 94.0315 -1.9051 -4.0861 0.0196 5.8840 0.7120 2.7305 0.2341 5.3091 +#> 374: 94.0323 -1.9052 -4.0862 0.0194 5.8755 0.7120 2.7301 0.2337 5.3101 +#> 375: 94.0344 -1.9055 -4.0863 0.0193 5.8744 0.7122 2.7308 0.2333 5.3121 +#> 376: 94.0341 -1.9056 -4.0865 0.0191 5.8738 0.7122 2.7311 0.2327 5.3136 +#> 377: 94.0320 -1.9055 -4.0868 0.0188 5.8703 0.7121 2.7311 0.2322 5.3161 +#> 378: 94.0291 -1.9058 -4.0869 0.0186 5.8771 0.7124 2.7311 0.2317 5.3187 +#> 379: 94.0273 -1.9062 -4.0872 0.0184 5.8829 0.7127 2.7316 0.2312 5.3206 +#> 380: 94.0259 -1.9067 -4.0875 0.0181 5.8786 0.7130 2.7321 0.2306 5.3235 +#> 381: 94.0231 -1.9068 -4.0877 0.0178 5.8716 0.7132 2.7331 0.2300 5.3231 +#> 382: 94.0210 -1.9069 -4.0879 0.0172 5.8636 0.7134 2.7340 0.2294 5.3240 +#> 383: 94.0189 -1.9070 -4.0880 0.0167 5.8596 0.7140 2.7351 0.2287 5.3246 +#> 384: 94.0171 -1.9070 -4.0882 0.0161 5.8588 0.7147 2.7365 0.2281 5.3251 +#> 385: 94.0141 -1.9070 -4.0880 0.0154 5.8659 0.7152 2.7365 0.2276 5.3263 +#> 386: 94.0116 -1.9070 -4.0879 0.0148 5.8785 0.7158 2.7364 0.2270 5.3272 +#> 387: 94.0090 -1.9070 -4.0877 0.0142 5.8874 0.7164 2.7363 0.2264 5.3286 +#> 388: 94.0068 -1.9069 -4.0875 0.0136 5.9016 0.7169 2.7364 0.2258 5.3299 +#> 389: 94.0063 -1.9067 -4.0873 0.0131 5.9114 0.7175 2.7363 0.2253 5.3332 +#> 390: 94.0074 -1.9064 -4.0872 0.0126 5.9258 0.7175 2.7362 0.2249 5.3353 +#> 391: 94.0092 -1.9061 -4.0870 0.0121 5.9426 0.7174 2.7359 0.2245 5.3370 +#> 392: 94.0112 -1.9060 -4.0870 0.0119 5.9499 0.7175 2.7358 0.2242 5.3375 +#> 393: 94.0120 -1.9058 -4.0869 0.0116 5.9514 0.7177 2.7351 0.2237 5.3364 +#> 394: 94.0137 -1.9056 -4.0867 0.0112 5.9560 0.7179 2.7342 0.2234 5.3371 +#> 395: 94.0150 -1.9054 -4.0866 0.0109 5.9566 0.7184 2.7340 0.2229 5.3376 +#> 396: 94.0175 -1.9054 -4.0866 0.0106 5.9564 0.7189 2.7341 0.2226 5.3370 +#> 397: 94.0195 -1.9055 -4.0866 0.0104 5.9447 0.7193 2.7344 0.2223 5.3378 +#> 398: 94.0201 -1.9056 -4.0867 0.0102 5.9353 0.7197 2.7348 0.2220 5.3380 +#> 399: 94.0204 -1.9056 -4.0868 0.0101 5.9282 0.7201 2.7350 0.2217 5.3387 +#> 400: 94.0198 -1.9058 -4.0867 0.0099 5.9243 0.7206 2.7348 0.2214 5.3383 +#> 401: 94.0194 -1.9059 -4.0867 0.0097 5.9225 0.7210 2.7345 0.2211 5.3379 +#> 402: 94.0176 -1.9060 -4.0868 0.0096 5.9237 0.7215 2.7342 0.2209 5.3370 +#> 403: 94.0172 -1.9061 -4.0869 0.0095 5.9259 0.7220 2.7337 0.2206 5.3371 +#> 404: 94.0147 -1.9062 -4.0870 0.0093 5.9322 0.7226 2.7330 0.2203 5.3382 +#> 405: 94.0131 -1.9065 -4.0872 0.0092 5.9354 0.7232 2.7326 0.2202 5.3385 +#> 406: 94.0117 -1.9066 -4.0872 0.0091 5.9399 0.7237 2.7318 0.2200 5.3388 +#> 407: 94.0114 -1.9069 -4.0871 0.0090 5.9495 0.7238 2.7314 0.2199 5.3397 +#> 408: 94.0133 -1.9071 -4.0870 0.0089 5.9505 0.7238 2.7310 0.2197 5.3401 +#> 409: 94.0159 -1.9074 -4.0868 0.0090 5.9523 0.7237 2.7309 0.2196 5.3417 +#> 410: 94.0171 -1.9076 -4.0864 0.0087 5.9503 0.7235 2.7307 0.2195 5.3449 +#> 411: 94.0193 -1.9078 -4.0862 0.0086 5.9528 0.7234 2.7304 0.2194 5.3476 +#> 412: 94.0193 -1.9082 -4.0860 0.0088 5.9516 0.7236 2.7303 0.2195 5.3509 +#> 413: 94.0192 -1.9085 -4.0859 0.0087 5.9491 0.7235 2.7302 0.2195 5.3517 +#> 414: 94.0175 -1.9086 -4.0860 0.0087 5.9453 0.7237 2.7297 0.2196 5.3523 +#> 415: 94.0156 -1.9088 -4.0861 0.0088 5.9408 0.7238 2.7289 0.2196 5.3528 +#> 416: 94.0145 -1.9090 -4.0861 0.0088 5.9442 0.7236 2.7281 0.2197 5.3540 +#> 417: 94.0140 -1.9093 -4.0862 0.0092 5.9459 0.7235 2.7274 0.2198 5.3549 +#> 418: 94.0144 -1.9097 -4.0864 0.0095 5.9495 0.7233 2.7269 0.2199 5.3551 +#> 419: 94.0142 -1.9102 -4.0866 0.0099 5.9425 0.7233 2.7265 0.2200 5.3555 +#> 420: 94.0134 -1.9107 -4.0867 0.0102 5.9338 0.7234 2.7260 0.2200 5.3563 +#> 421: 94.0096 -1.9113 -4.0869 0.0105 5.9272 0.7236 2.7260 0.2200 5.3571 +#> 422: 94.0069 -1.9118 -4.0872 0.0108 5.9238 0.7238 2.7261 0.2200 5.3576 +#> 423: 94.0034 -1.9124 -4.0874 0.0111 5.9217 0.7240 2.7260 0.2200 5.3579 +#> 424: 94.0009 -1.9129 -4.0876 0.0114 5.9258 0.7240 2.7259 0.2200 5.3578 +#> 425: 94.0000 -1.9134 -4.0879 0.0119 5.9330 0.7240 2.7258 0.2199 5.3572 +#> 426: 93.9991 -1.9138 -4.0881 0.0122 5.9526 0.7243 2.7256 0.2198 5.3572 +#> 427: 93.9969 -1.9140 -4.0882 0.0124 5.9692 0.7247 2.7258 0.2196 5.3587 +#> 428: 93.9940 -1.9143 -4.0883 0.0124 5.9777 0.7247 2.7259 0.2194 5.3591 +#> 429: 93.9935 -1.9145 -4.0882 0.0123 5.9781 0.7247 2.7260 0.2192 5.3601 +#> 430: 93.9925 -1.9147 -4.0881 0.0122 5.9772 0.7247 2.7260 0.2190 5.3606 +#> 431: 93.9928 -1.9150 -4.0879 0.0120 5.9824 0.7249 2.7262 0.2189 5.3616 +#> 432: 93.9930 -1.9152 -4.0879 0.0120 5.9797 0.7251 2.7267 0.2188 5.3618 +#> 433: 93.9930 -1.9154 -4.0878 0.0119 5.9785 0.7254 2.7271 0.2187 5.3626 +#> 434: 93.9930 -1.9156 -4.0878 0.0120 5.9711 0.7255 2.7273 0.2186 5.3638 +#> 435: 93.9935 -1.9157 -4.0878 0.0120 5.9659 0.7255 2.7269 0.2186 5.3643 +#> 436: 93.9951 -1.9158 -4.0876 0.0120 5.9570 0.7253 2.7263 0.2184 5.3667 +#> 437: 93.9980 -1.9158 -4.0874 0.0119 5.9492 0.7252 2.7259 0.2182 5.3680 +#> 438: 93.9999 -1.9158 -4.0872 0.0117 5.9361 0.7250 2.7255 0.2179 5.3700 +#> 439: 93.9990 -1.9159 -4.0868 0.0115 5.9312 0.7249 2.7247 0.2177 5.3700 +#> 440: 93.9986 -1.9160 -4.0865 0.0114 5.9280 0.7248 2.7235 0.2175 5.3698 +#> 441: 93.9996 -1.9160 -4.0863 0.0114 5.9248 0.7246 2.7222 0.2173 5.3696 +#> 442: 94.0001 -1.9160 -4.0861 0.0114 5.9266 0.7243 2.7213 0.2171 5.3702 +#> 443: 94.0004 -1.9159 -4.0859 0.0113 5.9228 0.7241 2.7202 0.2169 5.3707 +#> 444: 93.9989 -1.9161 -4.0858 0.0113 5.9200 0.7239 2.7194 0.2166 5.3722 +#> 445: 93.9971 -1.9162 -4.0857 0.0114 5.9257 0.7238 2.7182 0.2165 5.3736 +#> 446: 93.9970 -1.9164 -4.0858 0.0114 5.9286 0.7238 2.7177 0.2164 5.3738 +#> 447: 93.9959 -1.9163 -4.0858 0.0113 5.9407 0.7237 2.7166 0.2165 5.3731 +#> 448: 93.9947 -1.9163 -4.0856 0.0113 5.9442 0.7237 2.7159 0.2167 5.3723 +#> 449: 93.9948 -1.9164 -4.0854 0.0114 5.9386 0.7234 2.7151 0.2170 5.3730 +#> 450: 93.9937 -1.9164 -4.0853 0.0115 5.9368 0.7231 2.7142 0.2172 5.3732 +#> 451: 93.9929 -1.9164 -4.0851 0.0114 5.9312 0.7229 2.7135 0.2173 5.3735 +#> 452: 93.9923 -1.9163 -4.0850 0.0112 5.9288 0.7227 2.7121 0.2175 5.3747 +#> 453: 93.9918 -1.9162 -4.0849 0.0111 5.9339 0.7225 2.7112 0.2178 5.3759 +#> 454: 93.9912 -1.9164 -4.0849 0.0111 5.9355 0.7224 2.7103 0.2181 5.3777 +#> 455: 93.9902 -1.9164 -4.0849 0.0111 5.9412 0.7223 2.7097 0.2183 5.3784 +#> 456: 93.9894 -1.9164 -4.0848 0.0110 5.9554 0.7223 2.7076 0.2186 5.3801 +#> 457: 93.9902 -1.9161 -4.0846 0.0110 5.9675 0.7219 2.7054 0.2188 5.3807 +#> 458: 93.9907 -1.9159 -4.0845 0.0109 5.9710 0.7216 2.7032 0.2191 5.3815 +#> 459: 93.9926 -1.9157 -4.0844 0.0108 5.9751 0.7213 2.7011 0.2193 5.3817 +#> 460: 93.9930 -1.9155 -4.0845 0.0107 5.9788 0.7210 2.6985 0.2197 5.3818 +#> 461: 93.9933 -1.9153 -4.0845 0.0106 5.9809 0.7208 2.6959 0.2200 5.3822 +#> 462: 93.9941 -1.9153 -4.0845 0.0105 5.9904 0.7205 2.6935 0.2203 5.3820 +#> 463: 93.9945 -1.9152 -4.0844 0.0105 5.9971 0.7201 2.6913 0.2206 5.3817 +#> 464: 93.9942 -1.9151 -4.0844 0.0104 6.0010 0.7198 2.6892 0.2209 5.3818 +#> 465: 93.9931 -1.9152 -4.0843 0.0103 6.0113 0.7193 2.6872 0.2212 5.3823 +#> 466: 93.9937 -1.9152 -4.0840 0.0101 6.0145 0.7188 2.6853 0.2215 5.3828 +#> 467: 93.9939 -1.9152 -4.0838 0.0099 6.0189 0.7182 2.6835 0.2218 5.3832 +#> 468: 93.9933 -1.9153 -4.0835 0.0097 6.0247 0.7177 2.6818 0.2221 5.3830 +#> 469: 93.9933 -1.9153 -4.0832 0.0095 6.0251 0.7173 2.6801 0.2224 5.3822 +#> 470: 93.9914 -1.9153 -4.0829 0.0092 6.0332 0.7169 2.6785 0.2226 5.3823 +#> 471: 93.9894 -1.9153 -4.0826 0.0089 6.0455 0.7165 2.6769 0.2230 5.3822 +#> 472: 93.9869 -1.9152 -4.0824 0.0086 6.0454 0.7161 2.6754 0.2232 5.3836 +#> 473: 93.9852 -1.9152 -4.0822 0.0084 6.0501 0.7159 2.6740 0.2234 5.3832 +#> 474: 93.9829 -1.9152 -4.0821 0.0082 6.0579 0.7155 2.6725 0.2235 5.3831 +#> 475: 93.9826 -1.9152 -4.0819 0.0082 6.0661 0.7150 2.6711 0.2238 5.3829 +#> 476: 93.9837 -1.9152 -4.0819 0.0082 6.0774 0.7147 2.6696 0.2241 5.3824 +#> 477: 93.9852 -1.9151 -4.0819 0.0081 6.0890 0.7145 2.6681 0.2244 5.3817 +#> 478: 93.9851 -1.9151 -4.0820 0.0080 6.0957 0.7144 2.6665 0.2246 5.3827 +#> 479: 93.9857 -1.9150 -4.0820 0.0079 6.0981 0.7144 2.6651 0.2250 5.3838 +#> 480: 93.9856 -1.9151 -4.0821 0.0080 6.0944 0.7144 2.6638 0.2255 5.3854 +#> 481: 93.9864 -1.9152 -4.0823 0.0081 6.0912 0.7144 2.6624 0.2258 5.3865 +#> 482: 93.9870 -1.9153 -4.0825 0.0081 6.0954 0.7142 2.6613 0.2262 5.3864 +#> 483: 93.9888 -1.9153 -4.0826 0.0081 6.0888 0.7141 2.6602 0.2267 5.3870 +#> 484: 93.9903 -1.9154 -4.0828 0.0082 6.0848 0.7139 2.6592 0.2272 5.3861 +#> 485: 93.9914 -1.9154 -4.0831 0.0085 6.0851 0.7138 2.6586 0.2275 5.3858 +#> 486: 93.9909 -1.9154 -4.0834 0.0088 6.0824 0.7137 2.6581 0.2278 5.3850 +#> 487: 93.9899 -1.9155 -4.0838 0.0091 6.0870 0.7137 2.6577 0.2281 5.3838 +#> 488: 93.9882 -1.9156 -4.0842 0.0095 6.0877 0.7135 2.6574 0.2284 5.3835 +#> 489: 93.9865 -1.9163 -4.0841 0.0099 6.0839 0.7139 2.6581 0.2287 5.3835 +#> 490: 93.9859 -1.9170 -4.0841 0.0104 6.0783 0.7143 2.6587 0.2290 5.3830 +#> 491: 93.9847 -1.9177 -4.0838 0.0108 6.0773 0.7148 2.6596 0.2293 5.3824 +#> 492: 93.9840 -1.9183 -4.0836 0.0110 6.0833 0.7152 2.6606 0.2295 5.3817 +#> 493: 93.9832 -1.9188 -4.0834 0.0113 6.0832 0.7157 2.6613 0.2297 5.3814 +#> 494: 93.9824 -1.9195 -4.0832 0.0115 6.0859 0.7163 2.6620 0.2299 5.3819 +#> 495: 93.9813 -1.9200 -4.0830 0.0117 6.0878 0.7169 2.6633 0.2300 5.3820 +#> 496: 93.9798 -1.9206 -4.0827 0.0118 6.0871 0.7173 2.6644 0.2302 5.3825 +#> 497: 93.9787 -1.9213 -4.0824 0.0120 6.0856 0.7178 2.6653 0.2304 5.3834 +#> 498: 93.9771 -1.9220 -4.0822 0.0123 6.0759 0.7181 2.6660 0.2308 5.3850 +#> 499: 93.9744 -1.9225 -4.0819 0.0125 6.0692 0.7183 2.6666 0.2311 5.3868 +#> 500: 93.9728 -1.9229 -4.0816 0.0129 6.0609 0.7184 2.6675 0.2314 5.3884</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='input'><span class='va'>f_nlmixr_dfop_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | parent_0 | log_k1 | log_k2 | g_qlogis | +#> |.....................| sigma | o1 | o2 | o3 | +#> <span style='text-decoration: underline;'>|.....................| o4 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 1</span>| 319.20504 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 319.20504 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 319.20504</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | G| Gill Diff. | 17.25 | -0.06517 | -0.2231 | 0.05323 | +#> |.....................| -31.06 | 10.54 | -5.521 | 3.149 | +#> <span style='text-decoration: underline;'>|.....................| -10.19 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 2</span>| 930.59637 | 0.5572 | -0.9500 | -0.9943 | -0.9135 | +#> |.....................| -0.07749 | -1.170 | -0.7520 | -0.9767 | +#> <span style='text-decoration: underline;'>|.....................| -0.6292 |...........|...........|...........|</span> +#> | U| 930.59637 | 52.42 | -1.832 | -4.205 | 0.1099 | +#> |.....................| 2.723 | 0.5378 | 1.159 | 0.8352 | +#> <span style='text-decoration: underline;'>|.....................| 1.457 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 930.59637</span> | 52.42 | 0.1600 | 0.01492 | 0.5274 | +#> |.....................| 2.723 | 0.5378 | 1.159 | 0.8352 | +#> <span style='text-decoration: underline;'>|.....................| 1.457 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 3</span>| 366.81009 | 0.9557 | -0.9515 | -0.9994 | -0.9122 | +#> |.....................| -0.7950 | -0.9264 | -0.8795 | -0.9039 | +#> <span style='text-decoration: underline;'>|.....................| -0.8647 |...........|...........|...........|</span> +#> | U| 366.81009 | 89.92 | -1.834 | -4.210 | 0.1100 | +#> |.....................| 2.024 | 0.7174 | 1.030 | 0.9013 | +#> <span style='text-decoration: underline;'>|.....................| 1.185 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 366.81009</span> | 89.92 | 0.1598 | 0.01484 | 0.5275 | +#> |.....................| 2.024 | 0.7174 | 1.030 | 0.9013 | +#> <span style='text-decoration: underline;'>|.....................| 1.185 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 4</span>| 354.05577 | 0.9956 | -0.9516 | -0.9999 | -0.9121 | +#> |.....................| -0.8667 | -0.9020 | -0.8922 | -0.8966 | +#> <span style='text-decoration: underline;'>|.....................| -0.8882 |...........|...........|...........|</span> +#> | U| 354.05577 | 93.67 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.954 | 0.7353 | 1.017 | 0.9079 | +#> <span style='text-decoration: underline;'>|.....................| 1.158 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.05577</span> | 93.67 | 0.1597 | 0.01484 | 0.5275 | +#> |.....................| 1.954 | 0.7353 | 1.017 | 0.9079 | +#> <span style='text-decoration: underline;'>|.....................| 1.158 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 5</span>| 354.18966 | 0.9996 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8739 | -0.8996 | -0.8935 | -0.8959 | +#> <span style='text-decoration: underline;'>|.....................| -0.8906 |...........|...........|...........|</span> +#> | U| 354.18966 | 94.04 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7371 | 1.015 | 0.9086 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.18966</span> | 94.04 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7371 | 1.015 | 0.9086 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 6</span>| 354.21855 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8746 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.21855 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.21855</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 7</span>| 354.22159 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22159 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22159</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 8</span>| 354.22201 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22201 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22201</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 9</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 10</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 11</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 12</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 13</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 14</span>| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.22204</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 15</span>| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.222</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 16</span>| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.222</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 17</span>| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 | +#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 | +#> <span style='text-decoration: underline;'>|.....................| -0.8908 |...........|...........|...........|</span> +#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 354.222</span> | 94.08 | 0.1597 | 0.01483 | 0.5275 | +#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 | +#> <span style='text-decoration: underline;'>|.....................| 1.155 |...........|...........|...........|</span> +#> calculating covariance matrix +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate and covariance; see $scaleInfo</span></div><div class='input'> +<span class='va'>f_nlmixr_hs_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"HS"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> 1: 93.5894 -2.4029 -3.9815 2.0318 3.0448 0.8581 1.0844 0.3182 21.0327 +#> 2: 93.5363 -2.3652 -3.9374 1.9473 2.8925 0.8152 1.0302 0.3023 14.7642 +#> 3: 93.3061 -2.3950 -3.8630 1.9537 2.7479 0.7744 1.0729 0.2872 12.2332 +#> 4: 93.4757 -2.3967 -3.8509 1.9504 2.6105 0.7357 1.1580 0.2729 11.6140 +#> 5: 93.6045 -2.3957 -3.8593 1.9732 2.4800 0.6989 1.1001 0.2592 11.0776 +#> 6: 93.6138 -2.4089 -3.9577 1.9557 2.8119 0.6640 1.0451 0.2463 11.5001 +#> 7: 93.4125 -2.3879 -3.8924 1.9950 3.1015 0.6308 1.0649 0.2339 10.6133 +#> 8: 93.5798 -2.3850 -3.9314 1.9888 3.0019 0.5992 1.0116 0.2222 10.4278 +#> 9: 93.1493 -2.3918 -3.9011 2.0040 4.3802 0.5693 1.0723 0.2111 10.2172 +#> 10: 93.5411 -2.3906 -3.8778 1.9664 4.5606 0.5408 1.0616 0.2006 10.1244 +#> 11: 93.3749 -2.4011 -3.8586 1.9682 4.3326 0.5138 1.0696 0.1905 10.1145 +#> 12: 93.0136 -2.3943 -3.8530 1.9633 4.1160 0.4881 1.0606 0.1810 10.0091 +#> 13: 93.1809 -2.4059 -3.9088 1.9821 3.9102 0.5448 1.0076 0.1720 9.8058 +#> 14: 93.3891 -2.4107 -3.9285 1.9894 3.7147 0.5504 0.9810 0.1634 10.2784 +#> 15: 93.4041 -2.4114 -3.9711 2.0216 4.4250 0.6070 0.9495 0.1552 9.4036 +#> 16: 93.4244 -2.4191 -4.0366 2.0511 4.2037 0.6035 0.9020 0.1474 10.0835 +#> 17: 93.6295 -2.4103 -4.0143 2.0509 4.0926 0.5997 0.8599 0.1401 9.7686 +#> 18: 93.6653 -2.4165 -3.9724 2.0405 3.8880 0.5979 0.9046 0.1331 9.6299 +#> 19: 93.6510 -2.4088 -3.9969 2.0328 3.6936 0.5934 0.9181 0.1264 9.3236 +#> 20: 93.6048 -2.4117 -3.9552 2.0268 3.9084 0.5879 1.0078 0.1201 9.6618 +#> 21: 94.0961 -2.4193 -3.9812 2.0552 3.7456 0.5743 0.9574 0.1141 9.6510 +#> 22: 93.9157 -2.4202 -3.9102 2.0263 5.0447 0.6198 0.9742 0.1294 9.6463 +#> 23: 94.1580 -2.4286 -3.9223 2.0441 4.7925 0.5981 0.9312 0.1230 9.8346 +#> 24: 94.4405 -2.4141 -3.9564 2.0383 4.5529 0.5925 0.9173 0.1168 10.6161 +#> 25: 93.8846 -2.3958 -4.0122 2.0053 4.9956 0.5677 0.8715 0.1173 10.3823 +#> 26: 93.6815 -2.3835 -3.9801 1.9872 5.6625 0.5514 0.8368 0.1114 9.8283 +#> 27: 93.6463 -2.3779 -3.9731 1.9833 5.3794 0.5566 0.8650 0.1059 9.5439 +#> 28: 93.7974 -2.3980 -3.9583 1.9657 6.4804 0.5366 0.8756 0.1006 9.7998 +#> 29: 93.6921 -2.4221 -3.8982 1.9701 6.1564 0.6070 0.9713 0.0955 9.2988 +#> 30: 93.3112 -2.4200 -3.8916 1.9702 6.6968 0.6110 0.9538 0.0908 9.1812 +#> 31: 93.9900 -2.4282 -3.9448 2.0257 6.3620 0.6071 0.9061 0.0862 9.4865 +#> 32: 93.8014 -2.4241 -3.9364 2.0053 6.8497 0.6173 0.8608 0.0819 9.5589 +#> 33: 94.0330 -2.4215 -3.9888 2.0034 6.5072 0.6142 0.8178 0.0778 10.2023 +#> 34: 93.5811 -2.4215 -3.9917 2.0170 6.1819 0.5907 0.8314 0.0842 10.2204 +#> 35: 93.9308 -2.4210 -3.8798 2.0046 6.7593 0.5877 1.1132 0.0800 9.2384 +#> 36: 94.0000 -2.4325 -3.8970 2.0457 6.4213 0.5886 1.0731 0.0835 8.8987 +#> 37: 93.4010 -2.4325 -3.9306 2.0550 7.2268 0.5886 1.0220 0.0969 9.1261 +#> 38: 93.3896 -2.4291 -3.9250 2.0148 6.8655 0.5885 0.9709 0.1039 9.2989 +#> 39: 93.3821 -2.4349 -3.9148 2.0368 6.5222 0.6059 0.9647 0.1095 9.2864 +#> 40: 93.1382 -2.4685 -3.9384 2.1083 8.6249 0.6287 1.0265 0.1066 9.6411 +#> 41: 92.7963 -2.4643 -3.8992 2.0585 8.1937 0.6376 1.1117 0.1234 9.4738 +#> 42: 92.7160 -2.4545 -3.9652 2.0680 7.7840 0.6068 1.0561 0.1173 9.4776 +#> 43: 93.0070 -2.4360 -4.0223 2.0624 7.9556 0.5840 1.0033 0.1114 9.7197 +#> 44: 93.3836 -2.4207 -4.0739 2.0872 7.5578 0.5788 0.9531 0.1058 10.3515 +#> 45: 93.3240 -2.4382 -4.0210 2.1103 7.1799 0.6211 0.9055 0.1165 10.5050 +#> 46: 93.1921 -2.4438 -4.0330 2.0842 7.3884 0.6159 0.8602 0.1107 10.7251 +#> 47: 92.9710 -2.4351 -4.0155 2.1117 7.0189 0.5998 0.8519 0.1091 10.2972 +#> 48: 93.0129 -2.4395 -3.9677 2.0986 6.6680 0.5804 0.8775 0.1058 10.8515 +#> 49: 92.6562 -2.4474 -4.0295 2.0877 6.3346 0.6338 0.8723 0.1155 10.0641 +#> 50: 92.5101 -2.4612 -4.0295 2.0845 6.0179 0.6197 0.8742 0.1097 9.9048 +#> 51: 92.9446 -2.4615 -3.9927 2.1199 5.7170 0.6165 0.9311 0.1042 9.8383 +#> 52: 92.8362 -2.4525 -3.9682 2.0787 5.4311 0.6329 0.9647 0.0990 9.0726 +#> 53: 92.8579 -2.4598 -3.9324 2.0529 5.1596 0.6057 0.9192 0.0940 9.5677 +#> 54: 92.8667 -2.4858 -3.9104 2.0454 5.0661 0.6304 1.0025 0.0893 9.0977 +#> 55: 93.2327 -2.4650 -3.8323 2.0628 6.8188 0.6499 1.1366 0.0852 8.5677 +#> 56: 92.9319 -2.4794 -3.8376 2.0490 6.4778 0.6635 1.1141 0.1064 9.0723 +#> 57: 93.1126 -2.5128 -3.8223 2.0834 6.1539 0.6637 1.1361 0.1010 9.2678 +#> 58: 93.5085 -2.4894 -3.8723 2.0650 5.8462 0.6745 1.0793 0.0960 9.0367 +#> 59: 93.7882 -2.4614 -3.9241 2.0707 5.5539 0.6898 1.0254 0.0912 8.7466 +#> 60: 94.1492 -2.4386 -3.9415 2.0599 5.2762 0.6711 0.9741 0.0932 8.4466 +#> 61: 94.4215 -2.4272 -3.9647 2.0482 5.0124 0.6549 0.9254 0.0911 8.7870 +#> 62: 94.3607 -2.4053 -3.9633 1.9966 4.7618 0.6534 0.8878 0.1221 9.0404 +#> 63: 94.3958 -2.4179 -3.9386 2.0041 4.5237 0.6462 0.9360 0.1245 9.0491 +#> 64: 94.5204 -2.4175 -3.9411 2.0106 4.2975 0.6532 0.9657 0.1183 8.9115 +#> 65: 94.5674 -2.4117 -3.9701 2.0546 4.0826 0.6438 0.9238 0.1247 8.7293 +#> 66: 94.2199 -2.4337 -3.9298 2.0287 4.7686 0.6582 0.9262 0.1185 9.0519 +#> 67: 94.2756 -2.4305 -3.9706 2.0782 4.5301 0.6512 0.8799 0.1126 9.1397 +#> 68: 94.4195 -2.4193 -4.0049 2.0643 4.3036 0.6804 0.8359 0.1220 9.5306 +#> 69: 94.5255 -2.4183 -4.0119 2.0733 4.0884 0.6784 0.8577 0.1297 9.4535 +#> 70: 94.5668 -2.4117 -3.9662 2.0762 4.2149 0.6511 0.9325 0.1475 9.1637 +#> 71: 94.7464 -2.4147 -3.9937 2.0942 4.2418 0.6571 0.9524 0.1540 9.6576 +#> 72: 94.4869 -2.4160 -4.0050 2.1075 4.8520 0.6687 1.0119 0.1488 9.4234 +#> 73: 94.3747 -2.4423 -4.0072 2.1484 6.4364 0.6948 1.0011 0.1438 9.1490 +#> 74: 94.3997 -2.4464 -4.0147 2.1965 6.1146 0.7030 1.0566 0.1521 9.0697 +#> 75: 94.4187 -2.4566 -3.9611 2.1337 5.8089 0.6866 1.1666 0.1656 8.9436 +#> 76: 94.4381 -2.4502 -3.9816 2.1209 5.6488 0.7266 1.1449 0.1573 8.9289 +#> 77: 94.6421 -2.4446 -3.9603 2.1544 5.3663 0.6968 1.2087 0.1662 8.5186 +#> 78: 94.8397 -2.4420 -3.9690 2.1380 5.0980 0.6969 1.1833 0.1578 8.9071 +#> 79: 94.4296 -2.4547 -3.9576 2.1569 6.3095 0.6829 1.1850 0.1544 9.1345 +#> 80: 93.9628 -2.4530 -3.9312 2.0956 8.5844 0.6880 1.2548 0.1835 8.6936 +#> 81: 94.2900 -2.4687 -3.8570 2.0779 9.0596 0.6993 1.2012 0.1743 8.9092 +#> 82: 93.9652 -2.4742 -3.9261 2.0913 8.6066 0.6970 1.1667 0.1656 8.4359 +#> 83: 94.0828 -2.4739 -3.8603 2.0587 8.1763 0.7123 1.2575 0.1638 8.5431 +#> 84: 93.5926 -2.4645 -3.8993 2.0391 9.8721 0.7178 1.1947 0.1556 8.5623 +#> 85: 93.7052 -2.4692 -3.8411 2.0448 9.3785 0.7251 1.1349 0.1478 8.5558 +#> 86: 93.8043 -2.4726 -3.9028 2.0745 8.9096 0.7064 1.0782 0.1404 9.1308 +#> 87: 93.5704 -2.4836 -3.8694 2.0999 12.3224 0.7284 1.0922 0.1334 8.8645 +#> 88: 93.5715 -2.4827 -3.9202 2.0861 11.7063 0.7541 1.0376 0.1267 9.2433 +#> 89: 93.6894 -2.4720 -3.8964 2.1093 12.4610 0.7727 1.0218 0.1325 9.0321 +#> 90: 93.2881 -2.4787 -3.9464 2.1137 11.8380 0.7850 0.9707 0.1258 8.8265 +#> 91: 93.8454 -2.4626 -3.9566 2.1181 11.2461 0.7620 0.9579 0.1396 8.8279 +#> 92: 93.8268 -2.4639 -3.8951 2.0936 10.6838 0.7618 1.1083 0.1553 8.4609 +#> 93: 94.0622 -2.4853 -3.8531 2.0740 10.1496 0.7493 1.1237 0.1596 8.2057 +#> 94: 93.6190 -2.4843 -3.8857 2.0625 9.6421 0.7596 1.1104 0.1686 8.3522 +#> 95: 93.6352 -2.4725 -3.9243 2.0582 9.1600 0.7732 1.0549 0.1694 8.3993 +#> 96: 93.5291 -2.4707 -3.9318 2.0612 8.7020 0.7853 1.0639 0.1609 8.2908 +#> 97: 93.0626 -2.4639 -3.9255 2.0887 8.4092 0.7717 1.1477 0.1685 8.2710 +#> 98: 93.3712 -2.4677 -3.9642 2.1350 7.9888 0.7703 1.0903 0.1921 8.5468 +#> 99: 93.7108 -2.4848 -3.9775 2.1733 7.5893 0.7490 1.0367 0.1825 8.5629 +#> 100: 94.1114 -2.4867 -4.0111 2.1705 7.2099 0.7446 0.9849 0.1832 8.6964 +#> 101: 93.7547 -2.4897 -3.9793 2.1817 7.1755 0.7513 0.9899 0.1774 8.5077 +#> 102: 93.8818 -2.5029 -3.9929 2.2028 6.8167 0.7137 1.0045 0.1685 8.3706 +#> 103: 94.0026 -2.5094 -3.9680 2.2059 6.4759 0.7073 1.0498 0.1601 8.3087 +#> 104: 93.5946 -2.5260 -3.9640 2.2209 6.2674 0.7688 1.0548 0.1531 8.3444 +#> 105: 93.3863 -2.5431 -4.0087 2.2211 7.1040 0.7987 1.0020 0.1454 8.2210 +#> 106: 93.1536 -2.5365 -4.0243 2.2457 6.7488 0.7909 0.9519 0.1389 8.0950 +#> 107: 93.2220 -2.5446 -4.0016 2.2508 6.4114 0.8108 0.9483 0.1364 8.5629 +#> 108: 93.0778 -2.5470 -3.9678 2.2329 6.4774 0.8077 1.0081 0.1850 9.2740 +#> 109: 93.8925 -2.5453 -3.9560 2.2193 6.1535 0.8079 1.0608 0.2111 9.2651 +#> 110: 94.3171 -2.5179 -4.0040 2.2145 5.8458 0.7874 1.0520 0.2135 8.9788 +#> 111: 94.0655 -2.5069 -3.9752 2.2009 5.5536 0.8056 1.1206 0.2192 8.9410 +#> 112: 93.8552 -2.4994 -3.9791 2.1597 5.2759 0.8012 1.0646 0.2365 8.9570 +#> 113: 93.5190 -2.5053 -3.9760 2.1727 5.0121 0.8326 1.0114 0.2246 9.2154 +#> 114: 93.5531 -2.5083 -3.9569 2.1636 4.7615 0.8255 0.9879 0.2134 9.1197 +#> 115: 93.4780 -2.5217 -3.9467 2.1529 4.5234 0.8314 1.0392 0.2027 8.7850 +#> 116: 93.5707 -2.5216 -3.9098 2.1667 4.2972 0.8261 1.1213 0.1926 9.2991 +#> 117: 93.6610 -2.5445 -3.8775 2.1473 4.0824 0.8122 1.1232 0.1830 9.2054 +#> 118: 93.4315 -2.5251 -3.9166 2.1365 4.6012 0.7933 1.0690 0.1738 8.8061 +#> 119: 93.2491 -2.5265 -3.9236 2.1671 5.0672 0.8046 1.0711 0.1709 8.2293 +#> 120: 93.2605 -2.5327 -3.9714 2.1984 4.8138 0.8025 1.0176 0.1623 7.9088 +#> 121: 93.5831 -2.5448 -3.9669 2.2195 4.5731 0.8079 0.9921 0.1542 8.2211 +#> 122: 93.3408 -2.5460 -3.9710 2.2235 4.6838 0.8053 1.0377 0.1658 8.2934 +#> 123: 93.4581 -2.5395 -3.9487 2.2279 4.4496 0.8298 1.0338 0.1732 8.2859 +#> 124: 93.0562 -2.5565 -3.9587 2.2299 4.2272 0.8590 1.0531 0.1964 8.1244 +#> 125: 93.0576 -2.5660 -3.9434 2.2457 4.0158 0.8564 1.0768 0.1866 8.3730 +#> 126: 92.8366 -2.5571 -3.9463 2.2096 3.8150 0.8551 1.0476 0.1773 8.3820 +#> 127: 92.9607 -2.5595 -3.9773 2.2325 3.6243 0.8497 0.9952 0.1684 9.2276 +#> 128: 93.0655 -2.5463 -3.9731 2.1901 3.4430 0.8903 0.9454 0.1600 8.8096 +#> 129: 93.0669 -2.5467 -3.9713 2.2204 3.2709 0.8905 0.9234 0.1520 8.8686 +#> 130: 93.2036 -2.5524 -3.9702 2.2070 3.1073 0.8719 0.9514 0.1578 8.8433 +#> 131: 93.3565 -2.5544 -3.9809 2.1654 2.9520 0.8777 0.9117 0.1764 8.9770 +#> 132: 93.0371 -2.5364 -3.9250 2.1761 2.8044 0.8338 1.0518 0.1731 8.5405 +#> 133: 93.5727 -2.5388 -3.8759 2.1580 3.6769 0.8616 1.0981 0.1858 8.5303 +#> 134: 93.4962 -2.5341 -3.9006 2.1394 4.3695 0.8904 1.0432 0.1765 8.7067 +#> 135: 93.3219 -2.5413 -3.8922 2.1888 4.1510 0.8971 1.0435 0.1857 8.4977 +#> 136: 93.3582 -2.5477 -3.8412 2.1957 3.9435 0.8816 1.1954 0.2102 8.1330 +#> 137: 93.2791 -2.5313 -3.8936 2.1570 3.7463 0.8875 1.1356 0.1997 8.3094 +#> 138: 93.0890 -2.5428 -3.8910 2.1414 3.5590 0.8826 1.1008 0.2120 8.2653 +#> 139: 93.2404 -2.5407 -3.8926 2.1727 3.3810 0.8829 1.1068 0.2014 8.3739 +#> 140: 93.0870 -2.5514 -3.9131 2.2182 3.2120 0.8712 1.0870 0.1914 8.6179 +#> 141: 93.2715 -2.5499 -3.9460 2.2216 3.4383 0.8470 1.0662 0.1900 8.4034 +#> 142: 93.1915 -2.5583 -3.9990 2.2475 5.2653 0.8607 1.0129 0.2061 7.9891 +#> 143: 93.3709 -2.5650 -3.9422 2.2369 5.0020 0.8748 1.2043 0.2248 8.0084 +#> 144: 93.2092 -2.5706 -3.9016 2.1930 4.7519 0.8667 1.1977 0.2179 8.2733 +#> 145: 92.6640 -2.5733 -3.9225 2.1859 4.5143 0.8636 1.1695 0.2070 8.6212 +#> 146: 92.7581 -2.5695 -3.9055 2.1801 5.4209 0.8589 1.1678 0.1967 8.9378 +#> 147: 93.1089 -2.5707 -3.9825 2.2113 7.6640 0.8710 1.1094 0.1934 9.0543 +#> 148: 93.0803 -2.5672 -3.9461 2.2066 9.9043 0.8648 1.1043 0.1863 8.6209 +#> 149: 92.6332 -2.5468 -3.9425 2.1881 9.4091 0.8278 1.1313 0.1769 8.4652 +#> 150: 92.9068 -2.5440 -3.9531 2.2005 8.9386 0.8189 1.1104 0.1681 8.4196 +#> 151: 92.7324 -2.5497 -3.9648 2.2387 8.4917 0.8205 1.1421 0.1597 8.4228 +#> 152: 93.0394 -2.5282 -3.9916 2.2251 3.9029 0.8190 1.0320 0.1612 8.3453 +#> 153: 93.3137 -2.5268 -3.9993 2.2294 3.7951 0.8187 1.0311 0.1780 8.4258 +#> 154: 93.6677 -2.5264 -3.9756 2.2615 4.8704 0.8177 1.1355 0.1799 8.7204 +#> 155: 94.0822 -2.5409 -4.0456 2.2507 5.1202 0.8032 0.9930 0.1613 8.8844 +#> 156: 93.6289 -2.5388 -4.1150 2.2777 4.6367 0.8080 0.8336 0.1817 8.4370 +#> 157: 93.9171 -2.5327 -4.0218 2.2696 3.1121 0.8069 1.0394 0.1800 8.5006 +#> 158: 94.0010 -2.5357 -4.0036 2.2695 3.1485 0.8087 1.1132 0.2048 8.7160 +#> 159: 94.1277 -2.5541 -3.9717 2.2773 5.1432 0.8088 1.0732 0.1980 8.5378 +#> 160: 94.0075 -2.5436 -3.9550 2.2796 4.7826 0.8286 1.0820 0.1953 8.3885 +#> 161: 93.6793 -2.5471 -3.9675 2.2713 3.9366 0.8603 1.0682 0.1972 8.3026 +#> 162: 93.2649 -2.5429 -3.9564 2.2406 2.7349 0.8469 1.0889 0.1929 8.3765 +#> 163: 93.2072 -2.5519 -3.9786 2.2535 3.1500 0.8361 1.1240 0.1997 8.4527 +#> 164: 93.4059 -2.5471 -4.0398 2.2257 2.8708 0.8284 1.0541 0.2105 8.4984 +#> 165: 93.2579 -2.5407 -3.9665 2.2305 2.7397 0.8251 1.1355 0.2302 7.9794 +#> 166: 93.4900 -2.5465 -3.9565 2.2316 1.9775 0.8359 1.0939 0.2243 8.1279 +#> 167: 93.3825 -2.5567 -3.9784 2.2276 2.3737 0.8251 1.0894 0.2254 8.6657 +#> 168: 93.2568 -2.5681 -3.9993 2.2818 2.6721 0.8237 1.1398 0.2207 8.4894 +#> 169: 93.0484 -2.5468 -3.9693 2.2586 1.9105 0.8518 1.1911 0.1917 8.5627 +#> 170: 93.2703 -2.5730 -3.9059 2.2512 2.1481 0.8068 1.3267 0.2198 8.2260 +#> 171: 93.2041 -2.5720 -3.8992 2.2227 2.7790 0.8045 1.2387 0.2059 8.1401 +#> 172: 92.7596 -2.5722 -3.8802 2.2537 2.9977 0.8049 1.2807 0.1831 8.3375 +#> 173: 92.7734 -2.5716 -3.8811 2.1987 3.0176 0.8063 1.3070 0.2285 8.5061 +#> 174: 92.5561 -2.5700 -3.9236 2.2351 3.0286 0.8250 1.2000 0.2200 8.0725 +#> 175: 92.5072 -2.5724 -3.9968 2.2479 2.4287 0.8333 1.0169 0.2235 8.2600 +#> 176: 92.3531 -2.5787 -3.9977 2.2407 2.9999 0.8167 0.9813 0.2451 8.7505 +#> 177: 92.4672 -2.5746 -4.0095 2.2733 2.8040 0.8361 0.9794 0.2363 8.5176 +#> 178: 92.5747 -2.5981 -3.9921 2.2835 1.8203 0.8411 0.9795 0.2112 8.8034 +#> 179: 92.7101 -2.5766 -3.9697 2.2337 1.7808 0.8348 1.0402 0.2247 8.3952 +#> 180: 92.5348 -2.5714 -3.9595 2.2236 1.2661 0.8361 1.0107 0.2375 8.7156 +#> 181: 92.7241 -2.5730 -3.9205 2.2162 1.1047 0.8321 1.1192 0.2147 8.8821 +#> 182: 92.9177 -2.5864 -3.9351 2.2280 1.2069 0.8108 1.1022 0.2163 8.5703 +#> 183: 92.8646 -2.5704 -3.9755 2.2192 1.5680 0.8232 0.9400 0.1848 8.6586 +#> 184: 92.8081 -2.5759 -3.9981 2.2411 1.7739 0.8394 0.8711 0.1788 8.6327 +#> 185: 92.6830 -2.5700 -4.0110 2.2360 1.5375 0.8093 0.9114 0.1782 8.6703 +#> 186: 92.7691 -2.5764 -3.9671 2.2148 1.8813 0.8117 0.9794 0.1901 8.4813 +#> 187: 92.7540 -2.5659 -3.9695 2.2543 1.3755 0.8130 1.0332 0.1960 8.5371 +#> 188: 92.5722 -2.5650 -3.9527 2.2552 1.4000 0.8142 1.1013 0.1881 8.2025 +#> 189: 92.9404 -2.5644 -3.9446 2.2579 1.3589 0.8157 1.1262 0.1741 8.2347 +#> 190: 92.8142 -2.5628 -3.9397 2.2549 1.1871 0.8241 1.1571 0.1728 8.1590 +#> 191: 92.7352 -2.5682 -3.9476 2.2502 0.8302 0.7954 1.1448 0.1859 8.6148 +#> 192: 92.7380 -2.5574 -3.9273 2.2318 0.6692 0.8185 1.1124 0.1932 8.5279 +#> 193: 92.9199 -2.5652 -3.9586 2.2184 0.9877 0.8097 1.1689 0.1709 8.7071 +#> 194: 93.0042 -2.5651 -3.9699 2.2302 1.3311 0.8135 1.1202 0.1832 8.8051 +#> 195: 92.8090 -2.5890 -3.9799 2.2360 0.9251 0.8313 1.0192 0.1806 9.3110 +#> 196: 92.5114 -2.5894 -3.9883 2.2553 0.8504 0.8299 1.0665 0.1855 8.9668 +#> 197: 92.6704 -2.5845 -3.9577 2.2490 0.3567 0.8365 1.0893 0.1896 8.5856 +#> 198: 92.7249 -2.5753 -3.9775 2.2327 0.4282 0.8506 1.0736 0.2003 8.7110 +#> 199: 92.5538 -2.5696 -3.9550 2.2382 0.3177 0.8550 1.1060 0.2132 8.5431 +#> 200: 92.6352 -2.5716 -3.9921 2.2372 0.2500 0.8592 1.0083 0.2057 8.5811 +#> 201: 92.6440 -2.5663 -3.9931 2.2219 0.2611 0.8647 1.0130 0.1931 8.6428 +#> 202: 92.6090 -2.5633 -3.9837 2.2198 0.2389 0.8680 1.0373 0.1958 8.6818 +#> 203: 92.6180 -2.5627 -3.9823 2.2185 0.2315 0.8627 1.0398 0.1939 8.6310 +#> 204: 92.6140 -2.5628 -3.9783 2.2176 0.2289 0.8588 1.0462 0.1923 8.5391 +#> 205: 92.6337 -2.5619 -3.9802 2.2190 0.2227 0.8579 1.0407 0.1965 8.5514 +#> 206: 92.6373 -2.5615 -3.9835 2.2175 0.2313 0.8580 1.0330 0.2006 8.5635 +#> 207: 92.6403 -2.5594 -3.9836 2.2189 0.2365 0.8608 1.0282 0.2017 8.5721 +#> 208: 92.6415 -2.5587 -3.9862 2.2192 0.2480 0.8615 1.0221 0.2001 8.5738 +#> 209: 92.6303 -2.5586 -3.9872 2.2180 0.2544 0.8608 1.0127 0.1966 8.6159 +#> 210: 92.6278 -2.5584 -3.9829 2.2178 0.2577 0.8576 1.0149 0.1932 8.6336 +#> 211: 92.6320 -2.5580 -3.9844 2.2163 0.2614 0.8544 1.0057 0.1902 8.6594 +#> 212: 92.6266 -2.5576 -3.9802 2.2140 0.2554 0.8515 1.0125 0.1891 8.6549 +#> 213: 92.6226 -2.5570 -3.9771 2.2114 0.2491 0.8468 1.0201 0.1879 8.6612 +#> 214: 92.6217 -2.5570 -3.9759 2.2119 0.2430 0.8429 1.0289 0.1859 8.6700 +#> 215: 92.6212 -2.5573 -3.9743 2.2121 0.2354 0.8394 1.0383 0.1853 8.6796 +#> 216: 92.6151 -2.5566 -3.9736 2.2125 0.2329 0.8378 1.0446 0.1850 8.7036 +#> 217: 92.6073 -2.5558 -3.9759 2.2133 0.2311 0.8373 1.0459 0.1854 8.7185 +#> 218: 92.6090 -2.5556 -3.9771 2.2142 0.2312 0.8373 1.0499 0.1866 8.7181 +#> 219: 92.6166 -2.5553 -3.9764 2.2142 0.2358 0.8376 1.0624 0.1882 8.7228 +#> 220: 92.6268 -2.5549 -3.9770 2.2150 0.2404 0.8395 1.0671 0.1899 8.7325 +#> 221: 92.6337 -2.5548 -3.9765 2.2172 0.2460 0.8412 1.0713 0.1900 8.7409 +#> 222: 92.6383 -2.5563 -3.9796 2.2211 0.2499 0.8412 1.0667 0.1898 8.7456 +#> 223: 92.6399 -2.5575 -3.9806 2.2259 0.2494 0.8406 1.0665 0.1898 8.7564 +#> 224: 92.6424 -2.5589 -3.9840 2.2296 0.2451 0.8412 1.0624 0.1894 8.7571 +#> 225: 92.6431 -2.5599 -3.9883 2.2336 0.2427 0.8423 1.0555 0.1885 8.7754 +#> 226: 92.6393 -2.5612 -3.9919 2.2371 0.2384 0.8431 1.0488 0.1886 8.7904 +#> 227: 92.6354 -2.5630 -3.9918 2.2406 0.2361 0.8432 1.0501 0.1892 8.8070 +#> 228: 92.6328 -2.5650 -3.9926 2.2437 0.2336 0.8434 1.0524 0.1908 8.8133 +#> 229: 92.6328 -2.5672 -3.9913 2.2462 0.2318 0.8439 1.0578 0.1926 8.8314 +#> 230: 92.6322 -2.5684 -3.9911 2.2482 0.2269 0.8426 1.0621 0.1952 8.8464 +#> 231: 92.6263 -2.5698 -3.9910 2.2500 0.2240 0.8418 1.0628 0.1963 8.8734 +#> 232: 92.6228 -2.5710 -3.9908 2.2515 0.2218 0.8411 1.0644 0.1977 8.9056 +#> 233: 92.6235 -2.5721 -3.9919 2.2545 0.2192 0.8409 1.0649 0.1983 8.9192 +#> 234: 92.6232 -2.5727 -3.9927 2.2551 0.2171 0.8397 1.0649 0.1981 8.9294 +#> 235: 92.6219 -2.5733 -3.9924 2.2562 0.2155 0.8390 1.0646 0.1978 8.9242 +#> 236: 92.6212 -2.5737 -3.9924 2.2574 0.2145 0.8384 1.0639 0.1975 8.9292 +#> 237: 92.6211 -2.5738 -3.9938 2.2588 0.2142 0.8379 1.0607 0.1970 8.9400 +#> 238: 92.6194 -2.5735 -3.9931 2.2589 0.2155 0.8373 1.0630 0.1969 8.9371 +#> 239: 92.6175 -2.5734 -3.9928 2.2593 0.2155 0.8371 1.0648 0.1967 8.9315 +#> 240: 92.6175 -2.5729 -3.9923 2.2593 0.2143 0.8367 1.0673 0.1963 8.9180 +#> 241: 92.6155 -2.5728 -3.9917 2.2591 0.2133 0.8372 1.0695 0.1960 8.9139 +#> 242: 92.6135 -2.5726 -3.9923 2.2588 0.2136 0.8375 1.0681 0.1965 8.9191 +#> 243: 92.6115 -2.5726 -3.9930 2.2592 0.2127 0.8375 1.0683 0.1969 8.9117 +#> 244: 92.6106 -2.5726 -3.9925 2.2588 0.2123 0.8381 1.0704 0.1975 8.9124 +#> 245: 92.6065 -2.5730 -3.9930 2.2586 0.2127 0.8388 1.0691 0.1982 8.9140 +#> 246: 92.6046 -2.5734 -3.9931 2.2588 0.2109 0.8397 1.0701 0.1986 8.9132 +#> 247: 92.6048 -2.5737 -3.9938 2.2597 0.2081 0.8404 1.0708 0.1989 8.9224 +#> 248: 92.6029 -2.5739 -3.9932 2.2599 0.2056 0.8410 1.0718 0.1993 8.9198 +#> 249: 92.6006 -2.5743 -3.9934 2.2598 0.2052 0.8419 1.0705 0.1996 8.9244 +#> 250: 92.5984 -2.5740 -3.9930 2.2595 0.2037 0.8417 1.0709 0.1997 8.9208 +#> 251: 92.5967 -2.5739 -3.9932 2.2595 0.2018 0.8418 1.0700 0.1996 8.9143 +#> 252: 92.5943 -2.5737 -3.9920 2.2594 0.2009 0.8412 1.0734 0.1992 8.9090 +#> 253: 92.5944 -2.5736 -3.9904 2.2588 0.1997 0.8405 1.0769 0.1995 8.9035 +#> 254: 92.5941 -2.5732 -3.9896 2.2582 0.1987 0.8394 1.0788 0.1993 8.8940 +#> 255: 92.5916 -2.5728 -3.9892 2.2571 0.1983 0.8387 1.0794 0.1988 8.8894 +#> 256: 92.5889 -2.5724 -3.9880 2.2562 0.1988 0.8382 1.0813 0.1992 8.8834 +#> 257: 92.5889 -2.5719 -3.9872 2.2557 0.2003 0.8378 1.0831 0.1995 8.8806 +#> 258: 92.5889 -2.5717 -3.9866 2.2556 0.2021 0.8377 1.0858 0.1995 8.8792 +#> 259: 92.5898 -2.5715 -3.9867 2.2556 0.2033 0.8373 1.0884 0.1999 8.8785 +#> 260: 92.5924 -2.5709 -3.9868 2.2556 0.2033 0.8367 1.0891 0.2006 8.8743 +#> 261: 92.5956 -2.5703 -3.9866 2.2552 0.2045 0.8360 1.0908 0.2014 8.8635 +#> 262: 92.5985 -2.5698 -3.9859 2.2546 0.2054 0.8354 1.0940 0.2022 8.8551 +#> 263: 92.6014 -2.5694 -3.9857 2.2544 0.2067 0.8347 1.0964 0.2028 8.8479 +#> 264: 92.6041 -2.5690 -3.9858 2.2543 0.2069 0.8338 1.0977 0.2028 8.8421 +#> 265: 92.6063 -2.5687 -3.9861 2.2541 0.2079 0.8327 1.0976 0.2029 8.8394 +#> 266: 92.6087 -2.5684 -3.9867 2.2540 0.2107 0.8318 1.0968 0.2027 8.8351 +#> 267: 92.6108 -2.5682 -3.9863 2.2534 0.2118 0.8314 1.0970 0.2032 8.8283 +#> 268: 92.6130 -2.5680 -3.9860 2.2530 0.2131 0.8309 1.0970 0.2034 8.8263 +#> 269: 92.6139 -2.5678 -3.9851 2.2526 0.2155 0.8306 1.0979 0.2040 8.8240 +#> 270: 92.6144 -2.5676 -3.9851 2.2521 0.2176 0.8303 1.0972 0.2044 8.8283 +#> 271: 92.6153 -2.5675 -3.9855 2.2518 0.2190 0.8305 1.0961 0.2049 8.8310 +#> 272: 92.6163 -2.5674 -3.9859 2.2521 0.2196 0.8305 1.0965 0.2051 8.8378 +#> 273: 92.6178 -2.5672 -3.9862 2.2520 0.2198 0.8302 1.0959 0.2051 8.8421 +#> 274: 92.6193 -2.5670 -3.9870 2.2524 0.2195 0.8299 1.0955 0.2051 8.8441 +#> 275: 92.6197 -2.5669 -3.9874 2.2526 0.2194 0.8295 1.0947 0.2052 8.8477 +#> 276: 92.6215 -2.5665 -3.9875 2.2523 0.2206 0.8288 1.0956 0.2058 8.8462 +#> 277: 92.6225 -2.5660 -3.9878 2.2522 0.2231 0.8282 1.0974 0.2064 8.8450 +#> 278: 92.6237 -2.5655 -3.9883 2.2522 0.2240 0.8277 1.0988 0.2074 8.8501 +#> 279: 92.6249 -2.5651 -3.9888 2.2524 0.2244 0.8274 1.0994 0.2083 8.8504 +#> 280: 92.6259 -2.5647 -3.9891 2.2523 0.2235 0.8270 1.0992 0.2087 8.8514 +#> 281: 92.6264 -2.5643 -3.9889 2.2522 0.2225 0.8262 1.1001 0.2090 8.8559 +#> 282: 92.6270 -2.5639 -3.9889 2.2516 0.2223 0.8255 1.0997 0.2090 8.8593 +#> 283: 92.6280 -2.5633 -3.9885 2.2503 0.2214 0.8248 1.0999 0.2101 8.8586 +#> 284: 92.6281 -2.5627 -3.9883 2.2491 0.2212 0.8241 1.0993 0.2110 8.8580 +#> 285: 92.6283 -2.5621 -3.9881 2.2481 0.2213 0.8235 1.0986 0.2118 8.8590 +#> 286: 92.6288 -2.5615 -3.9886 2.2475 0.2219 0.8231 1.0973 0.2123 8.8602 +#> 287: 92.6291 -2.5611 -3.9890 2.2470 0.2217 0.8230 1.0961 0.2133 8.8577 +#> 288: 92.6292 -2.5607 -3.9893 2.2468 0.2202 0.8229 1.0960 0.2142 8.8570 +#> 289: 92.6275 -2.5602 -3.9895 2.2464 0.2192 0.8226 1.0964 0.2151 8.8554 +#> 290: 92.6262 -2.5598 -3.9892 2.2457 0.2189 0.8223 1.0977 0.2161 8.8578 +#> 291: 92.6246 -2.5596 -3.9890 2.2454 0.2183 0.8218 1.0999 0.2165 8.8596 +#> 292: 92.6223 -2.5593 -3.9892 2.2451 0.2183 0.8213 1.1003 0.2173 8.8575 +#> 293: 92.6201 -2.5590 -3.9896 2.2447 0.2193 0.8209 1.1003 0.2175 8.8569 +#> 294: 92.6169 -2.5587 -3.9902 2.2445 0.2202 0.8204 1.0998 0.2176 8.8568 +#> 295: 92.6144 -2.5584 -3.9906 2.2442 0.2217 0.8197 1.0994 0.2176 8.8565 +#> 296: 92.6126 -2.5581 -3.9913 2.2441 0.2223 0.8188 1.0983 0.2175 8.8585 +#> 297: 92.6112 -2.5576 -3.9920 2.2439 0.2235 0.8182 1.0969 0.2175 8.8600 +#> 298: 92.6108 -2.5572 -3.9921 2.2433 0.2250 0.8174 1.0964 0.2177 8.8612 +#> 299: 92.6101 -2.5567 -3.9919 2.2425 0.2254 0.8169 1.0960 0.2178 8.8626 +#> 300: 92.6097 -2.5562 -3.9913 2.2415 0.2257 0.8163 1.0974 0.2182 8.8632 +#> 301: 92.6102 -2.5556 -3.9913 2.2407 0.2255 0.8156 1.0972 0.2183 8.8600 +#> 302: 92.6102 -2.5551 -3.9916 2.2400 0.2252 0.8156 1.0966 0.2186 8.8586 +#> 303: 92.6099 -2.5546 -3.9915 2.2391 0.2250 0.8152 1.0978 0.2189 8.8589 +#> 304: 92.6096 -2.5541 -3.9913 2.2387 0.2242 0.8149 1.0987 0.2194 8.8570 +#> 305: 92.6100 -2.5538 -3.9914 2.2383 0.2247 0.8144 1.0995 0.2202 8.8553 +#> 306: 92.6109 -2.5533 -3.9915 2.2378 0.2255 0.8144 1.1001 0.2212 8.8531 +#> 307: 92.6119 -2.5529 -3.9913 2.2371 0.2252 0.8143 1.1007 0.2217 8.8498 +#> 308: 92.6128 -2.5525 -3.9912 2.2366 0.2249 0.8142 1.1012 0.2219 8.8490 +#> 309: 92.6143 -2.5519 -3.9905 2.2357 0.2251 0.8138 1.1018 0.2224 8.8449 +#> 310: 92.6160 -2.5513 -3.9900 2.2346 0.2255 0.8136 1.1020 0.2230 8.8403 +#> 311: 92.6177 -2.5506 -3.9891 2.2333 0.2258 0.8132 1.1031 0.2236 8.8392 +#> 312: 92.6190 -2.5499 -3.9881 2.2319 0.2267 0.8130 1.1047 0.2242 8.8382 +#> 313: 92.6192 -2.5493 -3.9872 2.2305 0.2273 0.8127 1.1057 0.2249 8.8350 +#> 314: 92.6196 -2.5490 -3.9864 2.2300 0.2279 0.8129 1.1067 0.2257 8.8315 +#> 315: 92.6197 -2.5488 -3.9858 2.2295 0.2277 0.8132 1.1072 0.2266 8.8285 +#> 316: 92.6192 -2.5485 -3.9850 2.2284 0.2276 0.8133 1.1087 0.2275 8.8278 +#> 317: 92.6190 -2.5482 -3.9840 2.2275 0.2278 0.8135 1.1105 0.2282 8.8296 +#> 318: 92.6193 -2.5480 -3.9833 2.2266 0.2274 0.8133 1.1120 0.2289 8.8313 +#> 319: 92.6200 -2.5476 -3.9827 2.2257 0.2265 0.8129 1.1133 0.2297 8.8326 +#> 320: 92.6211 -2.5472 -3.9820 2.2250 0.2260 0.8124 1.1150 0.2302 8.8359 +#> 321: 92.6226 -2.5468 -3.9816 2.2246 0.2254 0.8118 1.1158 0.2308 8.8396 +#> 322: 92.6238 -2.5464 -3.9808 2.2238 0.2249 0.8114 1.1169 0.2316 8.8424 +#> 323: 92.6248 -2.5461 -3.9805 2.2231 0.2241 0.8109 1.1173 0.2320 8.8458 +#> 324: 92.6252 -2.5458 -3.9801 2.2224 0.2233 0.8103 1.1182 0.2324 8.8474 +#> 325: 92.6248 -2.5455 -3.9799 2.2216 0.2225 0.8096 1.1192 0.2328 8.8507 +#> 326: 92.6247 -2.5451 -3.9802 2.2209 0.2216 0.8091 1.1186 0.2331 8.8519 +#> 327: 92.6248 -2.5446 -3.9806 2.2203 0.2203 0.8088 1.1179 0.2335 8.8535 +#> 328: 92.6242 -2.5442 -3.9808 2.2198 0.2196 0.8084 1.1175 0.2339 8.8533 +#> 329: 92.6234 -2.5437 -3.9809 2.2192 0.2188 0.8081 1.1176 0.2342 8.8550 +#> 330: 92.6229 -2.5433 -3.9806 2.2187 0.2182 0.8078 1.1187 0.2346 8.8574 +#> 331: 92.6220 -2.5429 -3.9801 2.2181 0.2183 0.8075 1.1210 0.2352 8.8599 +#> 332: 92.6214 -2.5425 -3.9796 2.2175 0.2185 0.8072 1.1235 0.2360 8.8612 +#> 333: 92.6215 -2.5421 -3.9794 2.2170 0.2184 0.8068 1.1248 0.2365 8.8660 +#> 334: 92.6218 -2.5417 -3.9795 2.2168 0.2180 0.8065 1.1257 0.2369 8.8675 +#> 335: 92.6220 -2.5413 -3.9793 2.2164 0.2177 0.8062 1.1269 0.2374 8.8683 +#> 336: 92.6228 -2.5410 -3.9792 2.2159 0.2173 0.8059 1.1275 0.2378 8.8707 +#> 337: 92.6244 -2.5405 -3.9792 2.2153 0.2175 0.8057 1.1278 0.2387 8.8734 +#> 338: 92.6266 -2.5401 -3.9792 2.2146 0.2184 0.8057 1.1283 0.2396 8.8757 +#> 339: 92.6290 -2.5398 -3.9790 2.2144 0.2191 0.8060 1.1294 0.2403 8.8770 +#> 340: 92.6309 -2.5396 -3.9790 2.2142 0.2200 0.8061 1.1295 0.2405 8.8766 +#> 341: 92.6328 -2.5394 -3.9788 2.2142 0.2211 0.8061 1.1300 0.2406 8.8752 +#> 342: 92.6347 -2.5392 -3.9788 2.2140 0.2223 0.8062 1.1291 0.2405 8.8744 +#> 343: 92.6365 -2.5390 -3.9787 2.2139 0.2233 0.8063 1.1288 0.2405 8.8732 +#> 344: 92.6383 -2.5388 -3.9785 2.2136 0.2242 0.8060 1.1295 0.2404 8.8730 +#> 345: 92.6392 -2.5386 -3.9781 2.2133 0.2248 0.8055 1.1303 0.2401 8.8737 +#> 346: 92.6401 -2.5384 -3.9780 2.2129 0.2249 0.8051 1.1302 0.2399 8.8739 +#> 347: 92.6411 -2.5381 -3.9777 2.2124 0.2248 0.8049 1.1302 0.2399 8.8794 +#> 348: 92.6427 -2.5380 -3.9777 2.2122 0.2251 0.8047 1.1306 0.2398 8.8814 +#> 349: 92.6444 -2.5378 -3.9777 2.2119 0.2252 0.8047 1.1304 0.2397 8.8834 +#> 350: 92.6462 -2.5376 -3.9776 2.2115 0.2260 0.8043 1.1300 0.2395 8.8859 +#> 351: 92.6470 -2.5375 -3.9772 2.2110 0.2265 0.8041 1.1303 0.2392 8.8883 +#> 352: 92.6478 -2.5373 -3.9772 2.2106 0.2266 0.8037 1.1293 0.2386 8.8926 +#> 353: 92.6493 -2.5373 -3.9772 2.2103 0.2268 0.8032 1.1285 0.2381 8.8928 +#> 354: 92.6504 -2.5372 -3.9772 2.2100 0.2264 0.8028 1.1274 0.2376 8.8946 +#> 355: 92.6512 -2.5370 -3.9771 2.2096 0.2267 0.8023 1.1273 0.2373 8.8951 +#> 356: 92.6522 -2.5367 -3.9767 2.2089 0.2275 0.8018 1.1272 0.2370 8.8947 +#> 357: 92.6534 -2.5364 -3.9765 2.2080 0.2290 0.8015 1.1268 0.2369 8.8932 +#> 358: 92.6545 -2.5362 -3.9761 2.2072 0.2301 0.8011 1.1270 0.2368 8.8919 +#> 359: 92.6566 -2.5360 -3.9757 2.2064 0.2310 0.8008 1.1269 0.2369 8.8928 +#> 360: 92.6584 -2.5358 -3.9751 2.2059 0.2311 0.8005 1.1272 0.2368 8.8924 +#> 361: 92.6611 -2.5356 -3.9744 2.2051 0.2317 0.8004 1.1280 0.2369 8.8932 +#> 362: 92.6639 -2.5353 -3.9740 2.2043 0.2321 0.8003 1.1284 0.2370 8.8914 +#> 363: 92.6662 -2.5349 -3.9733 2.2033 0.2328 0.8001 1.1289 0.2371 8.8902 +#> 364: 92.6679 -2.5345 -3.9729 2.2025 0.2325 0.7998 1.1292 0.2372 8.8883 +#> 365: 92.6695 -2.5341 -3.9725 2.2019 0.2321 0.7994 1.1297 0.2373 8.8865 +#> 366: 92.6709 -2.5337 -3.9722 2.2011 0.2321 0.7990 1.1297 0.2373 8.8860 +#> 367: 92.6724 -2.5334 -3.9720 2.2005 0.2317 0.7987 1.1295 0.2372 8.8848 +#> 368: 92.6736 -2.5330 -3.9719 2.1999 0.2314 0.7985 1.1288 0.2371 8.8844 +#> 369: 92.6745 -2.5326 -3.9717 2.1994 0.2310 0.7982 1.1283 0.2371 8.8840 +#> 370: 92.6758 -2.5323 -3.9714 2.1990 0.2312 0.7980 1.1283 0.2370 8.8854 +#> 371: 92.6776 -2.5321 -3.9708 2.1984 0.2313 0.7977 1.1286 0.2369 8.8852 +#> 372: 92.6791 -2.5317 -3.9704 2.1978 0.2311 0.7973 1.1282 0.2367 8.8865 +#> 373: 92.6804 -2.5312 -3.9701 2.1969 0.2308 0.7969 1.1280 0.2366 8.8884 +#> 374: 92.6814 -2.5308 -3.9699 2.1962 0.2305 0.7965 1.1279 0.2364 8.8898 +#> 375: 92.6827 -2.5304 -3.9698 2.1954 0.2305 0.7961 1.1271 0.2360 8.8938 +#> 376: 92.6832 -2.5301 -3.9695 2.1947 0.2301 0.7957 1.1268 0.2359 8.8930 +#> 377: 92.6835 -2.5298 -3.9692 2.1941 0.2300 0.7953 1.1269 0.2357 8.8933 +#> 378: 92.6831 -2.5295 -3.9693 2.1935 0.2303 0.7950 1.1266 0.2357 8.8990 +#> 379: 92.6827 -2.5293 -3.9694 2.1933 0.2307 0.7948 1.1265 0.2356 8.9027 +#> 380: 92.6826 -2.5291 -3.9695 2.1931 0.2307 0.7947 1.1262 0.2356 8.9045 +#> 381: 92.6822 -2.5290 -3.9695 2.1929 0.2307 0.7945 1.1259 0.2355 8.9040 +#> 382: 92.6817 -2.5289 -3.9694 2.1925 0.2305 0.7943 1.1258 0.2357 8.9033 +#> 383: 92.6812 -2.5288 -3.9695 2.1922 0.2305 0.7942 1.1255 0.2358 8.9045 +#> 384: 92.6810 -2.5288 -3.9695 2.1920 0.2302 0.7940 1.1253 0.2360 8.9058 +#> 385: 92.6806 -2.5287 -3.9694 2.1918 0.2301 0.7938 1.1254 0.2361 8.9052 +#> 386: 92.6801 -2.5286 -3.9692 2.1914 0.2298 0.7936 1.1256 0.2362 8.9039 +#> 387: 92.6800 -2.5285 -3.9687 2.1914 0.2294 0.7934 1.1261 0.2361 8.9032 +#> 388: 92.6801 -2.5284 -3.9683 2.1913 0.2293 0.7931 1.1267 0.2360 8.9027 +#> 389: 92.6802 -2.5283 -3.9684 2.1912 0.2288 0.7928 1.1261 0.2360 8.9028 +#> 390: 92.6805 -2.5281 -3.9684 2.1910 0.2283 0.7925 1.1258 0.2360 8.9044 +#> 391: 92.6806 -2.5280 -3.9685 2.1908 0.2285 0.7921 1.1254 0.2360 8.9047 +#> 392: 92.6810 -2.5278 -3.9682 2.1907 0.2288 0.7918 1.1257 0.2360 8.9057 +#> 393: 92.6810 -2.5275 -3.9681 2.1906 0.2290 0.7916 1.1257 0.2360 8.9049 +#> 394: 92.6811 -2.5272 -3.9682 2.1904 0.2292 0.7913 1.1253 0.2360 8.9056 +#> 395: 92.6812 -2.5269 -3.9682 2.1900 0.2295 0.7911 1.1251 0.2362 8.9044 +#> 396: 92.6817 -2.5269 -3.9683 2.1901 0.2292 0.7911 1.1251 0.2361 8.9031 +#> 397: 92.6824 -2.5269 -3.9686 2.1903 0.2292 0.7911 1.1250 0.2361 8.9043 +#> 398: 92.6828 -2.5270 -3.9688 2.1907 0.2291 0.7913 1.1248 0.2359 8.9035 +#> 399: 92.6829 -2.5271 -3.9689 2.1909 0.2292 0.7916 1.1248 0.2358 8.9043 +#> 400: 92.6829 -2.5273 -3.9688 2.1909 0.2295 0.7919 1.1250 0.2356 8.9037 +#> 401: 92.6827 -2.5274 -3.9687 2.1910 0.2299 0.7922 1.1249 0.2356 8.9035 +#> 402: 92.6822 -2.5276 -3.9687 2.1911 0.2303 0.7926 1.1248 0.2355 8.9033 +#> 403: 92.6821 -2.5277 -3.9686 2.1913 0.2307 0.7929 1.1250 0.2354 8.9009 +#> 404: 92.6817 -2.5279 -3.9684 2.1914 0.2314 0.7930 1.1249 0.2352 8.9012 +#> 405: 92.6813 -2.5281 -3.9683 2.1915 0.2318 0.7930 1.1252 0.2349 8.9015 +#> 406: 92.6811 -2.5283 -3.9680 2.1916 0.2321 0.7930 1.1255 0.2345 8.9019 +#> 407: 92.6817 -2.5285 -3.9677 2.1918 0.2329 0.7930 1.1255 0.2343 8.9014 +#> 408: 92.6824 -2.5287 -3.9675 2.1919 0.2330 0.7930 1.1253 0.2341 8.9019 +#> 409: 92.6833 -2.5289 -3.9674 2.1922 0.2331 0.7931 1.1249 0.2338 8.9031 +#> 410: 92.6840 -2.5291 -3.9673 2.1924 0.2331 0.7930 1.1245 0.2335 8.9054 +#> 411: 92.6848 -2.5292 -3.9672 2.1926 0.2333 0.7929 1.1243 0.2333 8.9083 +#> 412: 92.6852 -2.5293 -3.9671 2.1928 0.2333 0.7931 1.1243 0.2333 8.9107 +#> 413: 92.6858 -2.5293 -3.9671 2.1929 0.2332 0.7932 1.1246 0.2332 8.9119 +#> 414: 92.6863 -2.5293 -3.9671 2.1928 0.2332 0.7934 1.1252 0.2333 8.9112 +#> 415: 92.6868 -2.5293 -3.9671 2.1928 0.2330 0.7935 1.1253 0.2332 8.9109 +#> 416: 92.6872 -2.5293 -3.9672 2.1928 0.2327 0.7935 1.1247 0.2330 8.9101 +#> 417: 92.6875 -2.5293 -3.9674 2.1929 0.2324 0.7934 1.1241 0.2330 8.9126 +#> 418: 92.6881 -2.5294 -3.9675 2.1929 0.2322 0.7935 1.1238 0.2332 8.9148 +#> 419: 92.6885 -2.5295 -3.9674 2.1929 0.2322 0.7936 1.1236 0.2331 8.9179 +#> 420: 92.6890 -2.5297 -3.9674 2.1929 0.2322 0.7936 1.1235 0.2331 8.9194 +#> 421: 92.6891 -2.5299 -3.9672 2.1930 0.2318 0.7937 1.1236 0.2330 8.9192 +#> 422: 92.6894 -2.5301 -3.9670 2.1930 0.2318 0.7937 1.1239 0.2329 8.9183 +#> 423: 92.6898 -2.5302 -3.9667 2.1931 0.2318 0.7937 1.1242 0.2327 8.9190 +#> 424: 92.6905 -2.5304 -3.9667 2.1931 0.2316 0.7937 1.1243 0.2326 8.9190 +#> 425: 92.6910 -2.5305 -3.9667 2.1932 0.2316 0.7936 1.1240 0.2327 8.9203 +#> 426: 92.6917 -2.5306 -3.9668 2.1935 0.2318 0.7937 1.1237 0.2326 8.9200 +#> 427: 92.6918 -2.5308 -3.9671 2.1939 0.2322 0.7938 1.1227 0.2326 8.9224 +#> 428: 92.6912 -2.5310 -3.9670 2.1941 0.2319 0.7939 1.1225 0.2325 8.9268 +#> 429: 92.6912 -2.5312 -3.9670 2.1944 0.2316 0.7939 1.1225 0.2324 8.9301 +#> 430: 92.6910 -2.5314 -3.9674 2.1948 0.2314 0.7940 1.1217 0.2322 8.9314 +#> 431: 92.6911 -2.5315 -3.9675 2.1950 0.2314 0.7942 1.1210 0.2320 8.9320 +#> 432: 92.6911 -2.5316 -3.9677 2.1953 0.2312 0.7944 1.1204 0.2320 8.9327 +#> 433: 92.6910 -2.5317 -3.9681 2.1955 0.2309 0.7946 1.1196 0.2320 8.9336 +#> 434: 92.6910 -2.5318 -3.9683 2.1957 0.2306 0.7949 1.1188 0.2320 8.9337 +#> 435: 92.6912 -2.5319 -3.9687 2.1960 0.2302 0.7951 1.1178 0.2319 8.9343 +#> 436: 92.6914 -2.5320 -3.9688 2.1961 0.2300 0.7953 1.1173 0.2319 8.9345 +#> 437: 92.6919 -2.5321 -3.9688 2.1962 0.2299 0.7955 1.1168 0.2318 8.9335 +#> 438: 92.6920 -2.5323 -3.9688 2.1964 0.2296 0.7957 1.1164 0.2318 8.9334 +#> 439: 92.6917 -2.5324 -3.9689 2.1965 0.2292 0.7959 1.1165 0.2317 8.9322 +#> 440: 92.6910 -2.5326 -3.9688 2.1969 0.2289 0.7960 1.1170 0.2316 8.9319 +#> 441: 92.6907 -2.5328 -3.9688 2.1973 0.2283 0.7961 1.1175 0.2316 8.9317 +#> 442: 92.6909 -2.5330 -3.9689 2.1976 0.2280 0.7962 1.1174 0.2315 8.9326 +#> 443: 92.6911 -2.5332 -3.9689 2.1980 0.2277 0.7963 1.1180 0.2315 8.9338 +#> 444: 92.6906 -2.5332 -3.9690 2.1981 0.2275 0.7963 1.1181 0.2315 8.9354 +#> 445: 92.6897 -2.5333 -3.9691 2.1982 0.2276 0.7962 1.1181 0.2315 8.9364 +#> 446: 92.6896 -2.5333 -3.9692 2.1982 0.2272 0.7962 1.1176 0.2314 8.9363 +#> 447: 92.6893 -2.5334 -3.9693 2.1982 0.2272 0.7961 1.1173 0.2313 8.9365 +#> 448: 92.6890 -2.5334 -3.9693 2.1982 0.2271 0.7961 1.1173 0.2313 8.9364 +#> 449: 92.6888 -2.5335 -3.9693 2.1982 0.2267 0.7961 1.1170 0.2313 8.9372 +#> 450: 92.6884 -2.5335 -3.9693 2.1982 0.2262 0.7959 1.1166 0.2312 8.9364 +#> 451: 92.6885 -2.5335 -3.9691 2.1981 0.2261 0.7958 1.1167 0.2312 8.9350 +#> 452: 92.6887 -2.5335 -3.9691 2.1980 0.2260 0.7957 1.1164 0.2311 8.9349 +#> 453: 92.6888 -2.5335 -3.9691 2.1979 0.2258 0.7957 1.1163 0.2310 8.9375 +#> 454: 92.6890 -2.5335 -3.9689 2.1977 0.2258 0.7957 1.1160 0.2308 8.9385 +#> 455: 92.6894 -2.5334 -3.9687 2.1975 0.2259 0.7956 1.1158 0.2307 8.9382 +#> 456: 92.6898 -2.5334 -3.9685 2.1974 0.2261 0.7957 1.1154 0.2306 8.9380 +#> 457: 92.6904 -2.5334 -3.9685 2.1975 0.2265 0.7956 1.1146 0.2304 8.9391 +#> 458: 92.6908 -2.5334 -3.9687 2.1975 0.2266 0.7956 1.1137 0.2303 8.9418 +#> 459: 92.6911 -2.5335 -3.9689 2.1975 0.2270 0.7956 1.1129 0.2303 8.9442 +#> 460: 92.6912 -2.5335 -3.9687 2.1976 0.2274 0.7957 1.1126 0.2301 8.9461 +#> 461: 92.6913 -2.5336 -3.9687 2.1975 0.2276 0.7958 1.1125 0.2300 8.9463 +#> 462: 92.6914 -2.5336 -3.9686 2.1974 0.2280 0.7959 1.1126 0.2299 8.9456 +#> 463: 92.6917 -2.5336 -3.9684 2.1973 0.2280 0.7960 1.1127 0.2297 8.9452 +#> 464: 92.6918 -2.5336 -3.9683 2.1970 0.2280 0.7961 1.1127 0.2295 8.9444 +#> 465: 92.6921 -2.5336 -3.9682 2.1967 0.2277 0.7962 1.1127 0.2294 8.9447 +#> 466: 92.6924 -2.5336 -3.9679 2.1967 0.2275 0.7964 1.1127 0.2291 8.9454 +#> 467: 92.6930 -2.5336 -3.9677 2.1966 0.2273 0.7967 1.1128 0.2290 8.9453 +#> 468: 92.6935 -2.5337 -3.9675 2.1966 0.2275 0.7970 1.1128 0.2289 8.9458 +#> 469: 92.6937 -2.5338 -3.9676 2.1967 0.2278 0.7972 1.1123 0.2287 8.9455 +#> 470: 92.6938 -2.5338 -3.9677 2.1967 0.2283 0.7974 1.1122 0.2285 8.9451 +#> 471: 92.6940 -2.5339 -3.9676 2.1969 0.2290 0.7976 1.1124 0.2283 8.9448 +#> 472: 92.6938 -2.5339 -3.9676 2.1972 0.2293 0.7977 1.1125 0.2281 8.9460 +#> 473: 92.6937 -2.5340 -3.9676 2.1972 0.2298 0.7978 1.1121 0.2278 8.9461 +#> 474: 92.6934 -2.5341 -3.9677 2.1974 0.2308 0.7978 1.1118 0.2276 8.9470 +#> 475: 92.6936 -2.5342 -3.9677 2.1978 0.2316 0.7979 1.1113 0.2273 8.9486 +#> 476: 92.6940 -2.5345 -3.9679 2.1983 0.2324 0.7981 1.1106 0.2271 8.9491 +#> 477: 92.6945 -2.5347 -3.9681 2.1989 0.2332 0.7983 1.1099 0.2269 8.9502 +#> 478: 92.6951 -2.5349 -3.9682 2.1992 0.2344 0.7986 1.1093 0.2267 8.9502 +#> 479: 92.6958 -2.5352 -3.9683 2.1995 0.2357 0.7987 1.1088 0.2266 8.9521 +#> 480: 92.6967 -2.5354 -3.9684 2.1998 0.2370 0.7988 1.1083 0.2265 8.9524 +#> 481: 92.6977 -2.5355 -3.9685 2.2001 0.2383 0.7990 1.1079 0.2263 8.9521 +#> 482: 92.6985 -2.5357 -3.9687 2.2004 0.2395 0.7992 1.1073 0.2262 8.9518 +#> 483: 92.6992 -2.5359 -3.9690 2.2008 0.2403 0.7995 1.1066 0.2262 8.9524 +#> 484: 92.7000 -2.5361 -3.9691 2.2010 0.2406 0.7998 1.1061 0.2260 8.9516 +#> 485: 92.7009 -2.5362 -3.9693 2.2015 0.2410 0.8001 1.1057 0.2261 8.9508 +#> 486: 92.7010 -2.5363 -3.9695 2.2019 0.2412 0.8004 1.1051 0.2261 8.9502 +#> 487: 92.7008 -2.5365 -3.9698 2.2023 0.2413 0.8009 1.1048 0.2260 8.9502 +#> 488: 92.7006 -2.5366 -3.9700 2.2026 0.2411 0.8012 1.1044 0.2260 8.9501 +#> 489: 92.7006 -2.5367 -3.9701 2.2029 0.2410 0.8015 1.1041 0.2261 8.9504 +#> 490: 92.7006 -2.5368 -3.9702 2.2031 0.2407 0.8015 1.1043 0.2260 8.9498 +#> 491: 92.7007 -2.5369 -3.9701 2.2034 0.2405 0.8016 1.1047 0.2261 8.9484 +#> 492: 92.7008 -2.5370 -3.9702 2.2035 0.2406 0.8017 1.1046 0.2261 8.9473 +#> 493: 92.7010 -2.5370 -3.9704 2.2037 0.2406 0.8018 1.1044 0.2261 8.9469 +#> 494: 92.7015 -2.5371 -3.9707 2.2038 0.2408 0.8019 1.1040 0.2261 8.9453 +#> 495: 92.7017 -2.5371 -3.9708 2.2039 0.2407 0.8021 1.1042 0.2262 8.9447 +#> 496: 92.7016 -2.5371 -3.9708 2.2039 0.2407 0.8022 1.1042 0.2262 8.9433 +#> 497: 92.7015 -2.5371 -3.9709 2.2039 0.2408 0.8023 1.1044 0.2262 8.9431 +#> 498: 92.7013 -2.5371 -3.9709 2.2040 0.2409 0.8024 1.1047 0.2262 8.9452 +#> 499: 92.7011 -2.5371 -3.9710 2.2039 0.2409 0.8023 1.1049 0.2261 8.9481 +#> 500: 92.7010 -2.5371 -3.9712 2.2040 0.2412 0.8022 1.1049 0.2260 8.9498</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='input'><span class='va'>f_nlmixr_hs_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"HS"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | parent_0 | log_k1 | log_k2 | log_tb | +#> |.....................| sigma | o1 | o2 | o3 | +#> <span style='text-decoration: underline;'>|.....................| o4 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 1</span>| 360.27275 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 360.27275 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 360.27275</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | G| Gill Diff. | 106.2 | 0.7918 | 0.06750 | 10.50 | +#> |.....................| -26.04 | 2.358 | -5.196 | -2.491 | +#> <span style='text-decoration: underline;'>|.....................| -12.13 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 2</span>| 7055.7467 | 0.04059 | -0.9733 | -1.001 | -0.9739 | +#> |.....................| -0.6317 | -0.9263 | -0.8528 | -0.8784 | +#> <span style='text-decoration: underline;'>|.....................| -0.7843 |...........|...........|...........|</span> +#> | U| 7055.7467 | 3.818 | -2.236 | -3.887 | 1.944 | +#> |.....................| 2.941 | 0.7466 | 1.074 | 0.9892 | +#> <span style='text-decoration: underline;'>|.....................| 1.458 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 7055.7467</span> | 3.818 | 0.1069 | 0.02050 | 6.988 | +#> |.....................| 2.941 | 0.7466 | 1.074 | 0.9892 | +#> <span style='text-decoration: underline;'>|.....................| 1.458 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 3</span>| 499.76989 | 0.9041 | -0.9669 | -1.000 | -0.8885 | +#> |.....................| -0.8434 | -0.9072 | -0.8950 | -0.8986 | +#> <span style='text-decoration: underline;'>|.....................| -0.8828 |...........|...........|...........|</span> +#> | U| 499.76989 | 85.03 | -2.229 | -3.887 | 2.030 | +#> |.....................| 2.663 | 0.7612 | 1.031 | 0.9696 | +#> <span style='text-decoration: underline;'>|.....................| 1.329 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 499.76989</span> | 85.03 | 0.1076 | 0.02051 | 7.611 | +#> |.....................| 2.663 | 0.7612 | 1.031 | 0.9696 | +#> <span style='text-decoration: underline;'>|.....................| 1.329 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 4</span>| 360.48011 | 0.9904 | -0.9662 | -1.000 | -0.8799 | +#> |.....................| -0.8645 | -0.9053 | -0.8992 | -0.9007 | +#> <span style='text-decoration: underline;'>|.....................| -0.8927 |...........|...........|...........|</span> +#> | U| 360.48011 | 93.15 | -2.229 | -3.887 | 2.038 | +#> |.....................| 2.635 | 0.7627 | 1.026 | 0.9677 | +#> <span style='text-decoration: underline;'>|.....................| 1.316 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 360.48011</span> | 93.15 | 0.1077 | 0.02051 | 7.676 | +#> |.....................| 2.635 | 0.7627 | 1.026 | 0.9677 | +#> <span style='text-decoration: underline;'>|.....................| 1.316 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 5</span>| 360.80998 | 0.9960 | -0.9662 | -1.000 | -0.8794 | +#> |.....................| -0.8659 | -0.9051 | -0.8995 | -0.9008 | +#> <span style='text-decoration: underline;'>|.....................| -0.8933 |...........|...........|...........|</span> +#> | U| 360.80998 | 93.68 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.633 | 0.7628 | 1.026 | 0.9676 | +#> <span style='text-decoration: underline;'>|.....................| 1.315 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 360.80998</span> | 93.68 | 0.1077 | 0.02051 | 7.680 | +#> |.....................| 2.633 | 0.7628 | 1.026 | 0.9676 | +#> <span style='text-decoration: underline;'>|.....................| 1.315 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 6</span>| 361.20154 | 0.9991 | -0.9661 | -1.000 | -0.8791 | +#> |.....................| -0.8667 | -0.9051 | -0.8996 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8937 |...........|...........|...........|</span> +#> | U| 361.20154 | 93.97 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.315 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.20154</span> | 93.97 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.315 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 7</span>| 361.33469 | 0.9999 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.33469 | 94.05 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.33469</span> | 94.05 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 8</span>| 361.34878 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.34878 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.34878</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 9</span>| 361.35091 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35091 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35091</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 10</span>| 361.35004 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35004 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35004</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 11</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 12</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 13</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 14</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 15</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 16</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 17</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> |<span style='font-weight: bold;'> 18</span>| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 | +#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 | +#> <span style='text-decoration: underline;'>|.....................| -0.8938 |...........|...........|...........|</span> +#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> | X|<span style='font-weight: bold;'> 361.35006</span> | 94.06 | 0.1077 | 0.02051 | 7.683 | +#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 | +#> <span style='text-decoration: underline;'>|.....................| 1.314 |...........|...........|...........|</span> +#> calculating covariance matrix +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate and covariance; see $scaleInfo</span></div><div class='input'> +<span class='va'>f_nlmixr_fomc_saem_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> 1: 92.2167 0.0936 1.9256 3.3974 0.7958 0.7197 11.8539 0.0004 +#> 2: 92.5446 0.0892 2.4952 3.3516 0.8528 0.6837 4.5197 0.0001 +#> 3: 9.2720e+01 1.3849e-01 2.5917e+00 3.9204e+00 9.5883e-01 6.4953e-01 4.0268e+00 5.9554e-05 +#> 4: 92.6098 0.1052 2.5494 5.0533 1.0968 0.6171 3.2396 0.0200 +#> 5: 92.6795 0.0406 2.4151 5.6729 1.0420 0.5862 3.1558 0.0183 +#> 6: 92.6580 0.0258 2.3640 5.7014 0.9899 0.5569 3.0212 0.0140 +#> 7: 93.0532 -0.0754 2.2262 7.3582 0.9404 0.5291 2.5591 0.0180 +#> 8: 92.8372 -0.0760 2.2080 6.9903 0.8934 0.5026 2.5653 0.0187 +#> 9: 93.0757 -0.1322 2.1663 6.6408 0.8487 0.4775 2.4943 0.0182 +#> 10: 93.0704 -0.1520 2.1410 6.3087 0.8063 0.4536 2.4004 0.0225 +#> 11: 93.1611 -0.1366 2.1740 5.9933 0.7659 0.4309 2.4242 0.0199 +#> 12: 92.7195 -0.0787 2.2947 5.6936 0.7277 0.4094 2.4532 0.0205 +#> 13: 92.6573 -0.1543 2.1929 5.4089 0.6913 0.3889 2.3750 0.0244 +#> 14: 93.1138 -0.1547 2.1924 5.1385 0.6567 0.3695 2.3590 0.0187 +#> 15: 93.5083 -0.1625 2.1831 4.8816 0.6239 0.3510 2.4420 0.0125 +#> 16: 93.2086 -0.1667 2.1516 4.6375 0.5927 0.3334 2.4527 0.0004 +#> 17: 93.3988 -0.1766 2.1521 4.4056 0.5630 0.3168 2.4527 0.0004 +#> 18: 93.4526 -0.1748 2.1461 4.1853 0.5349 0.3009 2.3775 0.0116 +#> 19: 93.5953 -0.1963 2.1167 3.9761 0.5081 0.2859 2.4693 0.0031 +#> 20: 9.3404e+01 -2.4408e-01 2.0453e+00 3.7773e+00 4.8274e-01 2.7158e-01 2.4789e+00 2.0760e-05 +#> 21: 9.3624e+01 -2.4691e-01 2.0524e+00 3.5884e+00 4.5860e-01 2.5800e-01 2.4789e+00 2.0760e-05 +#> 22: 9.3821e+01 -2.5932e-01 2.0021e+00 3.4090e+00 4.3567e-01 2.8670e-01 2.4182e+00 9.3297e-06 +#> 23: 9.3572e+01 -2.3703e-01 2.0725e+00 3.2385e+00 4.4889e-01 2.7237e-01 2.4525e+00 1.5592e-06 +#> 24: 9.3496e+01 -2.2704e-01 2.0746e+00 3.0766e+00 4.3674e-01 2.5875e-01 2.4569e+00 6.1365e-05 +#> 25: 9.3772e+01 -2.2211e-01 2.0762e+00 2.9228e+00 4.4843e-01 2.6194e-01 2.4015e+00 8.3288e-05 +#> 26: 9.3266e+01 -1.9408e-01 2.1345e+00 2.7766e+00 4.6952e-01 2.4885e-01 2.3827e+00 2.9029e-05 +#> 27: 9.3472e+01 -1.9793e-01 2.1141e+00 3.5922e+00 4.7687e-01 2.3640e-01 2.3827e+00 2.9029e-05 +#> 28: 9.3411e+01 -1.7721e-01 2.1334e+00 3.4125e+00 4.8209e-01 2.2458e-01 2.3864e+00 6.5503e-06 +#> 29: 93.6868 -0.1863 2.1258 4.5379 0.4744 0.2134 2.3001 0.0045 +#> 30: 9.4054e+01 -1.8122e-01 2.1287e+00 4.9729e+00 4.7945e-01 2.0269e-01 2.2979e+00 5.8327e-05 +#> 31: 9.3955e+01 -1.9131e-01 2.1202e+00 5.6375e+00 4.7965e-01 1.9255e-01 2.2671e+00 1.6931e-05 +#> 32: 9.4376e+01 -1.6810e-01 2.1287e+00 5.3556e+00 4.7567e-01 1.8972e-01 2.2483e+00 1.1778e-05 +#> 33: 9.4067e+01 -1.5819e-01 2.1656e+00 5.0878e+00 4.5710e-01 1.9389e-01 2.2696e+00 2.4282e-05 +#> 34: 9.4526e+01 -1.6367e-01 2.1473e+00 4.8334e+00 4.7085e-01 1.8419e-01 2.2919e+00 8.8644e-06 +#> 35: 9.4972e+01 -1.6784e-01 2.1353e+00 4.5917e+00 4.7510e-01 1.7498e-01 2.3129e+00 2.2851e-05 +#> 36: 9.4744e+01 -1.5973e-01 2.1281e+00 5.2356e+00 4.5695e-01 1.8499e-01 2.2896e+00 6.8824e-05 +#> 37: 9.4721e+01 -1.6756e-01 2.1168e+00 5.1111e+00 4.6804e-01 1.8407e-01 2.3035e+00 1.5534e-06 +#> 38: 9.4613e+01 -1.5952e-01 2.1385e+00 4.8555e+00 4.6107e-01 1.7720e-01 2.2650e+00 1.2489e-05 +#> 39: 9.4787e+01 -1.6113e-01 2.1458e+00 4.6128e+00 4.6317e-01 1.8378e-01 2.2831e+00 1.3668e-05 +#> 40: 94.5315 -0.1765 2.1186 4.3821 0.4428 0.1902 2.3132 0.0001 +#> 41: 9.4336e+01 -1.8333e-01 2.1285e+00 4.1630e+00 4.4521e-01 1.9913e-01 2.3092e+00 1.3482e-05 +#> 42: 94.0780 -0.2031 2.0724 3.9549 0.4405 0.1892 2.2704 0.0056 +#> 43: 93.9276 -0.1896 2.1191 3.7571 0.4590 0.1797 2.2396 0.0080 +#> 44: 94.2491 -0.1896 2.1006 3.8473 0.4590 0.1764 2.2774 0.0083 +#> 45: 94.4073 -0.1811 2.1156 3.6550 0.4519 0.1676 2.2682 0.0078 +#> 46: 93.9736 -0.1882 2.1196 3.4722 0.4545 0.1633 2.2775 0.0035 +#> 47: 94.1930 -0.1965 2.1102 3.2986 0.4599 0.1664 2.3243 0.0005 +#> 48: 9.4147e+01 -1.9494e-01 2.1118e+00 3.3188e+00 4.7005e-01 1.7181e-01 2.3345e+00 1.1669e-05 +#> 49: 9.4139e+01 -1.7920e-01 2.1199e+00 3.1528e+00 4.7417e-01 1.6322e-01 2.2794e+00 3.5582e-05 +#> 50: 9.4031e+01 -1.9074e-01 2.1098e+00 2.9952e+00 4.7498e-01 1.6695e-01 2.2574e+00 2.7302e-06 +#> 51: 9.3982e+01 -1.9369e-01 2.1058e+00 2.8848e+00 4.8158e-01 1.8408e-01 2.2447e+00 1.8188e-05 +#> 52: 9.3924e+01 -2.0726e-01 2.0809e+00 3.6064e+00 4.7008e-01 2.0029e-01 2.2319e+00 6.8301e-06 +#> 53: 9.4094e+01 -1.9609e-01 2.0780e+00 4.4341e+00 4.7556e-01 1.9742e-01 2.2701e+00 2.1343e-06 +#> 54: 9.4351e+01 -1.9839e-01 2.0746e+00 4.2124e+00 4.7456e-01 1.8866e-01 2.2778e+00 4.8058e-06 +#> 55: 93.9450 -0.1876 2.1059 4.0017 0.4892 0.1792 2.2720 0.0001 +#> 56: 9.3741e+01 -1.8208e-01 2.1172e+00 3.8017e+00 4.7696e-01 1.7027e-01 2.2332e+00 2.1237e-05 +#> 57: 9.3668e+01 -1.8580e-01 2.1181e+00 3.9224e+00 4.7704e-01 1.7425e-01 2.2512e+00 2.2766e-05 +#> 58: 9.3811e+01 -1.8324e-01 2.1178e+00 3.7263e+00 4.7945e-01 1.7939e-01 2.2512e+00 2.2766e-05 +#> 59: 9.3800e+01 -1.6691e-01 2.1250e+00 3.8213e+00 4.9353e-01 1.8464e-01 2.2763e+00 4.6129e-06 +#> 60: 9.3997e+01 -1.5920e-01 2.1489e+00 3.6303e+00 5.0788e-01 1.7541e-01 2.2466e+00 4.1975e-06 +#> 61: 9.4215e+01 -1.6445e-01 2.1482e+00 3.9303e+00 5.1966e-01 1.6664e-01 2.3053e+00 5.8982e-07 +#> 62: 9.3936e+01 -1.6721e-01 2.1376e+00 4.0316e+00 5.3719e-01 1.7228e-01 2.2841e+00 7.8603e-05 +#> 63: 9.3832e+01 -1.6209e-01 2.1334e+00 3.8698e+00 5.4370e-01 1.7064e-01 2.3046e+00 6.4415e-07 +#> 64: 93.9042 -0.1617 2.1563 5.5384 0.5430 0.1622 2.2988 0.0002 +#> 65: 93.8613 -0.1723 2.1239 6.2143 0.5304 0.1541 2.2949 0.0001 +#> 66: 9.4113e+01 -1.9168e-01 2.1019e+00 7.3588e+00 5.1287e-01 1.4641e-01 2.3164e+00 1.2580e-05 +#> 67: 9.3954e+01 -1.8141e-01 2.1199e+00 6.9909e+00 5.0278e-01 1.4993e-01 2.2676e+00 1.1126e-05 +#> 68: 93.8741 -0.1852 2.1343 6.6414 0.4997 0.1493 2.2706 0.0001 +#> 69: 9.3657e+01 -1.8345e-01 2.1375e+00 6.3093e+00 5.0292e-01 1.6326e-01 2.2809e+00 1.7299e-07 +#> 70: 9.3762e+01 -1.7493e-01 2.1512e+00 5.9938e+00 5.1042e-01 1.5509e-01 2.2837e+00 4.5745e-05 +#> 71: 9.4060e+01 -1.6516e-01 2.1440e+00 5.6941e+00 5.1615e-01 1.4734e-01 2.3001e+00 3.9993e-07 +#> 72: 9.3927e+01 -1.7365e-01 2.1347e+00 5.4094e+00 5.2582e-01 1.3997e-01 2.3075e+00 6.3748e-06 +#> 73: 9.4049e+01 -1.8080e-01 2.1254e+00 5.1390e+00 5.1154e-01 1.3297e-01 2.3042e+00 9.5858e-06 +#> 74: 9.3917e+01 -1.9083e-01 2.1051e+00 4.8820e+00 5.0104e-01 1.4605e-01 2.2733e+00 7.4923e-05 +#> 75: 9.4271e+01 -1.8281e-01 2.1059e+00 5.0872e+00 5.0773e-01 1.5322e-01 2.2387e+00 1.4240e-05 +#> 76: 9.4205e+01 -1.8352e-01 2.1160e+00 4.8328e+00 5.0684e-01 1.5669e-01 2.2708e+00 3.6346e-05 +#> 77: 9.4480e+01 -1.8352e-01 2.0942e+00 4.9009e+00 5.0684e-01 1.4885e-01 2.3098e+00 1.8186e-06 +#> 78: 9.4699e+01 -1.9686e-01 2.0671e+00 4.6559e+00 4.9182e-01 1.4503e-01 2.2806e+00 7.9443e-08 +#> 79: 9.4785e+01 -2.0649e-01 2.0500e+00 6.0608e+00 4.6723e-01 1.6185e-01 2.2607e+00 2.1557e-07 +#> 80: 9.4782e+01 -2.0045e-01 2.0680e+00 5.7578e+00 4.5759e-01 1.5747e-01 2.2926e+00 8.6381e-06 +#> 81: 9.4339e+01 -2.0435e-01 2.0885e+00 6.9051e+00 4.5054e-01 1.7410e-01 2.2796e+00 1.5517e-05 +#> 82: 9.4805e+01 -2.1032e-01 2.0658e+00 7.1580e+00 4.7091e-01 1.6539e-01 2.3013e+00 1.3893e-05 +#> 83: 9.4650e+01 -2.0507e-01 2.0485e+00 6.8001e+00 4.7624e-01 1.5938e-01 2.3104e+00 6.6569e-06 +#> 84: 9.4766e+01 -1.9959e-01 2.0667e+00 6.4601e+00 4.7322e-01 1.5619e-01 2.3359e+00 1.8890e-09 +#> 85: 9.4714e+01 -1.9959e-01 2.0756e+00 6.1371e+00 4.7322e-01 1.6894e-01 2.2738e+00 4.9578e-06 +#> 86: 9.4466e+01 -2.0544e-01 2.0626e+00 5.8302e+00 4.6340e-01 1.6050e-01 2.2773e+00 3.6221e-07 +#> 87: 9.4786e+01 -1.9292e-01 2.0703e+00 5.5387e+00 4.6881e-01 1.5641e-01 2.2746e+00 2.3326e-05 +#> 88: 9.4573e+01 -1.9488e-01 2.0597e+00 5.2618e+00 4.6538e-01 1.5079e-01 2.3225e+00 4.7054e-05 +#> 89: 94.8466 -0.2040 2.0603 4.9987 0.4620 0.1456 2.2807 0.0002 +#> 90: 9.4839e+01 -2.0359e-01 2.0673e+00 4.7488e+00 4.5379e-01 1.4729e-01 2.3099e+00 2.7922e-05 +#> 91: 9.4897e+01 -2.0635e-01 2.0496e+00 4.5113e+00 4.4018e-01 1.3993e-01 2.2924e+00 1.7074e-05 +#> 92: 9.4740e+01 -2.0567e-01 2.0518e+00 4.2858e+00 4.6190e-01 1.3293e-01 2.3396e+00 9.0471e-05 +#> 93: 94.9558 -0.2033 2.0824 4.0715 0.4877 0.1263 2.3785 0.0082 +#> 94: 95.1673 -0.1801 2.0900 3.8679 0.5150 0.1200 2.4128 0.0106 +#> 95: 95.3129 -0.1686 2.1057 3.6745 0.4892 0.1140 2.4135 0.0147 +#> 96: 9.5235e+01 -1.6834e-01 2.1069e+00 3.4908e+00 4.9584e-01 1.0827e-01 2.4408e+00 2.5829e-06 +#> 97: 9.4892e+01 -1.5911e-01 2.1277e+00 3.3162e+00 4.7518e-01 1.0286e-01 2.4658e+00 1.8589e-05 +#> 98: 9.4749e+01 -1.6133e-01 2.1204e+00 4.5926e+00 4.6435e-01 1.0192e-01 2.4716e+00 5.8808e-09 +#> 99: 9.4546e+01 -1.5627e-01 2.1358e+00 5.5648e+00 4.8843e-01 1.0047e-01 2.5033e+00 2.5865e-05 +#> 100: 9.4544e+01 -1.6341e-01 2.1317e+00 5.2974e+00 4.7076e-01 1.1065e-01 2.4711e+00 4.4438e-05 +#> 101: 94.2461 -0.1640 2.1458 5.0325 0.4750 0.1107 2.5297 0.0002 +#> 102: 9.4039e+01 -1.6946e-01 2.1490e+00 4.9929e+00 4.7265e-01 1.2109e-01 2.3907e+00 2.3093e-05 +#> 103: 9.4132e+01 -1.6840e-01 2.1250e+00 5.3879e+00 4.7062e-01 1.2389e-01 2.3401e+00 5.4840e-07 +#> 104: 9.4376e+01 -1.6842e-01 2.1239e+00 7.9826e+00 4.7053e-01 1.1769e-01 2.3663e+00 1.9617e-05 +#> 105: 9.4370e+01 -1.7024e-01 2.1187e+00 7.5834e+00 4.6738e-01 1.1683e-01 2.3471e+00 1.4035e-05 +#> 106: 9.4462e+01 -1.6562e-01 2.1406e+00 7.5466e+00 4.6364e-01 1.2640e-01 2.3140e+00 4.7933e-05 +#> 107: 9.4541e+01 -1.6582e-01 2.1308e+00 7.1692e+00 4.6457e-01 1.2964e-01 2.3395e+00 1.8489e-05 +#> 108: 9.4709e+01 -1.6157e-01 2.1484e+00 6.8108e+00 4.5925e-01 1.3393e-01 2.3340e+00 1.5230e-06 +#> 109: 9.4450e+01 -1.8900e-01 2.0799e+00 6.4702e+00 4.4801e-01 1.4728e-01 2.3847e+00 3.2613e-05 +#> 110: 9.4180e+01 -1.9104e-01 2.1172e+00 6.1467e+00 4.5389e-01 1.4273e-01 2.3775e+00 6.0285e-05 +#> 111: 9.4366e+01 -1.8908e-01 2.1031e+00 5.8394e+00 4.4875e-01 1.4983e-01 2.3898e+00 7.2653e-05 +#> 112: 9.4008e+01 -1.8144e-01 2.1008e+00 5.5474e+00 4.6433e-01 1.4234e-01 2.3705e+00 9.9395e-06 +#> 113: 9.4372e+01 -1.8885e-01 2.1154e+00 5.2700e+00 4.7983e-01 1.3522e-01 2.3641e+00 1.8643e-05 +#> 114: 94.1292 -0.1872 2.1134 5.0065 0.4824 0.1285 2.3163 0.0001 +#> 115: 9.4510e+01 -1.7805e-01 2.1185e+00 4.7562e+00 4.8451e-01 1.2204e-01 2.3568e+00 1.6277e-07 +#> 116: 9.4234e+01 -1.8613e-01 2.1214e+00 4.5184e+00 4.7967e-01 1.2275e-01 2.3388e+00 3.4361e-05 +#> 117: 9.4438e+01 -1.7276e-01 2.1218e+00 4.2925e+00 4.6200e-01 1.1662e-01 2.3686e+00 5.6594e-06 +#> 118: 9.4498e+01 -1.7628e-01 2.1143e+00 6.2395e+00 4.5445e-01 1.2378e-01 2.3303e+00 6.5645e-05 +#> 119: 9.4303e+01 -1.8107e-01 2.1120e+00 7.5774e+00 4.6102e-01 1.2829e-01 2.3595e+00 9.4057e-06 +#> 120: 9.4022e+01 -1.7626e-01 2.1258e+00 9.9044e+00 4.6505e-01 1.5188e-01 2.3582e+00 3.6907e-05 +#> 121: 9.4103e+01 -1.5976e-01 2.1354e+00 9.4091e+00 4.7792e-01 1.5429e-01 2.3729e+00 4.6749e-05 +#> 122: 9.4727e+01 -1.9092e-01 2.0956e+00 8.9387e+00 4.5402e-01 1.6371e-01 2.3118e+00 6.8573e-06 +#> 123: 9.4447e+01 -1.9139e-01 2.0898e+00 8.4918e+00 4.3317e-01 1.7569e-01 2.3083e+00 4.4068e-05 +#> 124: 9.4422e+01 -1.9130e-01 2.0920e+00 8.0672e+00 4.3952e-01 1.7160e-01 2.3003e+00 1.7162e-05 +#> 125: 9.4608e+01 -1.7777e-01 2.1007e+00 7.6638e+00 4.8253e-01 1.6302e-01 2.3244e+00 1.9896e-05 +#> 126: 9.4512e+01 -1.6596e-01 2.1139e+00 7.2806e+00 4.7648e-01 1.7588e-01 2.2913e+00 4.9747e-05 +#> 127: 9.4983e+01 -1.6562e-01 2.1290e+00 6.9166e+00 4.7028e-01 1.6709e-01 2.3141e+00 3.3357e-05 +#> 128: 94.3910 -0.1728 2.1159 6.5708 0.4914 0.1850 2.3173 0.0001 +#> 129: 9.4578e+01 -1.7211e-01 2.1177e+00 6.2422e+00 4.8295e-01 1.7709e-01 2.2815e+00 4.8158e-05 +#> 130: 9.4646e+01 -1.6785e-01 2.1333e+00 5.9301e+00 4.6360e-01 1.6823e-01 2.3140e+00 2.1204e-05 +#> 131: 9.4670e+01 -1.4897e-01 2.1480e+00 5.6336e+00 4.8826e-01 1.5982e-01 2.3436e+00 1.3221e-05 +#> 132: 9.4625e+01 -1.6160e-01 2.1599e+00 5.3519e+00 4.6385e-01 1.6125e-01 2.2830e+00 9.6815e-06 +#> 133: 9.3985e+01 -1.7636e-01 2.1299e+00 5.8178e+00 4.4885e-01 1.5389e-01 2.2810e+00 6.7789e-06 +#> 134: 9.4105e+01 -1.7389e-01 2.1199e+00 5.5269e+00 4.5848e-01 1.4628e-01 2.2992e+00 7.6542e-06 +#> 135: 9.4387e+01 -1.5936e-01 2.1418e+00 5.2506e+00 4.5002e-01 1.6349e-01 2.3403e+00 7.6250e-05 +#> 136: 94.3595 -0.1696 2.1493 4.9880 0.4407 0.1722 2.3121 0.0001 +#> 137: 9.4056e+01 -1.6030e-01 2.1720e+00 5.5600e+00 4.4954e-01 1.8233e-01 2.3099e+00 2.1195e-05 +#> 138: 9.4043e+01 -1.4848e-01 2.1876e+00 5.2820e+00 4.5696e-01 1.8542e-01 2.2876e+00 8.7271e-06 +#> 139: 94.3020 -0.1374 2.1965 5.6428 0.4668 0.1927 2.3341 0.0001 +#> 140: 9.4260e+01 -1.3603e-01 2.2014e+00 5.7727e+00 4.6823e-01 1.8302e-01 2.3248e+00 1.4731e-06 +#> 141: 9.4302e+01 -1.2134e-01 2.1992e+00 5.4841e+00 4.8967e-01 1.7947e-01 2.3212e+00 1.6339e-05 +#> 142: 94.0970 -0.1143 2.2570 5.4173 0.4766 0.1726 2.3581 0.0077 +#> 143: 94.2078 -0.1162 2.2460 5.1464 0.4745 0.1874 2.3551 0.0152 +#> 144: 94.2085 -0.0953 2.2685 4.8891 0.5010 0.1780 2.3881 0.0095 +#> 145: 94.1483 -0.0906 2.2751 5.0705 0.4959 0.1770 2.3103 0.0143 +#> 146: 94.4257 -0.0859 2.2735 5.0201 0.5331 0.2050 2.3104 0.0160 +#> 147: 93.8072 -0.0887 2.2766 4.7691 0.5253 0.2200 2.2903 0.0180 +#> 148: 94.4354 -0.0901 2.2770 4.5306 0.5237 0.2147 2.3108 0.0150 +#> 149: 94.1171 -0.1126 2.2342 4.3041 0.5412 0.2300 2.3454 0.0126 +#> 150: 94.0704 -0.1267 2.2071 4.0889 0.5324 0.2185 2.3673 0.0097 +#> 151: 93.9860 -0.1480 2.1852 3.8844 0.5101 0.2529 2.3280 0.0056 +#> 152: 93.9500 -0.1419 2.1940 4.4687 0.5066 0.2371 2.3617 0.0002 +#> 153: 93.8058 -0.1368 2.1917 4.2493 0.5068 0.2057 2.3481 0.0002 +#> 154: 9.4043e+01 -1.3331e-01 2.1972e+00 4.3921e+00 4.7605e-01 1.9689e-01 2.3952e+00 9.5657e-05 +#> 155: 94.2500 -0.1223 2.2260 5.7786 0.4848 0.1829 2.3361 0.0075 +#> 156: 94.5035 -0.1223 2.2091 6.1344 0.4848 0.1558 2.3951 0.0048 +#> 157: 9.4448e+01 -1.3268e-01 2.1797e+00 6.4746e+00 4.6934e-01 1.6035e-01 2.3496e+00 5.2771e-05 +#> 158: 94.7438 -0.1401 2.1904 6.0162 0.4589 0.1692 2.3444 0.0001 +#> 159: 94.2681 -0.1430 2.1852 4.6165 0.4774 0.1617 2.3601 0.0001 +#> 160: 9.3911e+01 -1.1659e-01 2.2267e+00 4.9756e+00 4.9349e-01 1.7150e-01 2.3500e+00 9.0374e-06 +#> 161: 9.3914e+01 -1.1938e-01 2.2233e+00 4.8238e+00 4.9674e-01 1.8358e-01 2.3536e+00 1.1877e-06 +#> 162: 93.9974 -0.1188 2.2349 5.1092 0.4967 0.1714 2.3237 0.0041 +#> 163: 9.3939e+01 -1.2170e-01 2.2147e+00 4.8315e+00 5.0622e-01 1.8195e-01 2.3823e+00 2.4030e-05 +#> 164: 93.8015 -0.1362 2.2166 3.9112 0.4958 0.1684 2.3488 0.0072 +#> 165: 93.4082 -0.1398 2.2132 3.2992 0.5087 0.1734 2.2861 0.0125 +#> 166: 93.4680 -0.1421 2.2077 3.3232 0.5075 0.1643 2.2792 0.0149 +#> 167: 93.5455 -0.1443 2.2080 3.7465 0.4972 0.1685 2.2194 0.0191 +#> 168: 93.5603 -0.1711 2.1421 3.2407 0.5201 0.1940 2.3029 0.0198 +#> 169: 93.7281 -0.1578 2.1553 2.5110 0.4988 0.1836 2.3343 0.0134 +#> 170: 93.9675 -0.1564 2.1532 2.2507 0.5049 0.1753 2.3089 0.0110 +#> 171: 93.8255 -0.1543 2.1647 2.7302 0.5114 0.1691 2.2959 0.0113 +#> 172: 93.8071 -0.1536 2.1689 2.5849 0.5069 0.1751 2.3047 0.0099 +#> 173: 93.7137 -0.1403 2.2096 1.5160 0.5204 0.1622 2.3452 0.0155 +#> 174: 93.7182 -0.1376 2.1975 1.3366 0.5222 0.1700 2.3311 0.0149 +#> 175: 93.5957 -0.1587 2.1613 1.3539 0.5321 0.1470 2.3893 0.0156 +#> 176: 93.6058 -0.1587 2.1602 1.4588 0.5321 0.1412 2.4323 0.0116 +#> 177: 93.4496 -0.1858 2.1323 1.2423 0.4987 0.1460 2.3491 0.0167 +#> 178: 93.5894 -0.1935 2.1217 1.7812 0.4776 0.1643 2.3046 0.0168 +#> 179: 93.6386 -0.1887 2.1445 2.8813 0.4808 0.1585 2.2689 0.0192 +#> 180: 93.9288 -0.1950 2.1015 2.0905 0.4681 0.1557 2.2783 0.0170 +#> 181: 93.8165 -0.1950 2.0840 2.6302 0.4681 0.1592 2.3643 0.0173 +#> 182: 94.2132 -0.1936 2.0866 3.0185 0.5131 0.1712 2.3164 0.0147 +#> 183: 94.0929 -0.1896 2.0782 3.0716 0.5288 0.1644 2.5169 0.0066 +#> 184: 93.8694 -0.1968 2.0946 2.4734 0.5121 0.1709 2.3795 0.0071 +#> 185: 93.8138 -0.1970 2.0987 2.9707 0.4957 0.1500 2.3995 0.0034 +#> 186: 9.4047e+01 -2.1045e-01 2.0791e+00 3.6686e+00 4.8764e-01 1.4347e-01 2.3654e+00 3.8127e-05 +#> 187: 9.4498e+01 -1.9649e-01 2.0949e+00 2.0912e+00 4.7479e-01 1.6122e-01 2.3873e+00 4.7739e-06 +#> 188: 9.4650e+01 -1.8508e-01 2.1132e+00 2.1529e+00 4.6244e-01 1.4403e-01 2.3367e+00 3.5345e-06 +#> 189: 9.4301e+01 -1.8137e-01 2.1132e+00 2.6433e+00 4.4894e-01 1.3537e-01 2.3145e+00 9.6836e-06 +#> 190: 9.4501e+01 -1.8209e-01 2.0962e+00 3.1460e+00 4.4908e-01 1.2006e-01 2.3563e+00 3.3387e-05 +#> 191: 9.4156e+01 -2.0214e-01 2.0803e+00 3.2334e+00 4.7635e-01 1.1917e-01 2.3782e+00 6.6641e-06 +#> 192: 9.3981e+01 -2.1562e-01 2.0492e+00 3.0526e+00 5.0505e-01 1.3669e-01 2.3412e+00 7.3871e-05 +#> 193: 9.4085e+01 -2.2693e-01 2.0318e+00 2.9855e+00 4.9563e-01 1.4371e-01 2.3727e+00 8.6443e-05 +#> 194: 9.3922e+01 -2.3089e-01 2.0323e+00 2.9709e+00 4.9151e-01 1.4470e-01 2.3667e+00 3.5941e-05 +#> 195: 9.4180e+01 -2.2865e-01 2.0284e+00 2.2426e+00 4.8793e-01 1.5283e-01 2.3442e+00 1.8882e-05 +#> 196: 9.4259e+01 -2.0053e-01 2.0541e+00 1.5155e+00 5.1571e-01 1.5596e-01 2.3638e+00 2.9015e-05 +#> 197: 9.4225e+01 -2.0144e-01 2.0551e+00 1.6032e+00 5.0920e-01 1.6454e-01 2.3564e+00 2.7823e-05 +#> 198: 9.4166e+01 -1.9411e-01 2.0602e+00 1.8793e+00 5.5190e-01 1.8338e-01 2.3611e+00 1.6669e-05 +#> 199: 9.4230e+01 -1.9621e-01 2.0737e+00 1.8847e+00 5.4082e-01 1.7340e-01 2.3488e+00 5.8282e-07 +#> 200: 9.4215e+01 -1.9629e-01 2.0888e+00 1.9185e+00 5.4293e-01 1.7502e-01 2.3563e+00 5.7303e-06 +#> 201: 94.0654 -0.1931 2.0901 1.8074 0.5373 0.1886 2.3869 0.0025 +#> 202: 93.9801 -0.1898 2.0990 1.6823 0.5318 0.1841 2.4043 0.0016 +#> 203: 94.0246 -0.1893 2.1004 1.6503 0.5286 0.1855 2.3971 0.0012 +#> 204: 93.9893 -0.1870 2.1014 1.6166 0.5276 0.1846 2.3900 0.0010 +#> 205: 94.0154 -0.1854 2.1006 1.5294 0.5286 0.1828 2.3939 0.0009 +#> 206: 94.0468 -0.1833 2.1024 1.5102 0.5295 0.1807 2.3967 0.0007 +#> 207: 94.0641 -0.1810 2.1049 1.5136 0.5289 0.1798 2.4037 0.0008 +#> 208: 94.0794 -0.1790 2.1062 1.5078 0.5286 0.1790 2.4139 0.0007 +#> 209: 94.0892 -0.1799 2.1049 1.4549 0.5261 0.1793 2.4144 0.0006 +#> 210: 94.0911 -0.1817 2.1042 1.4537 0.5217 0.1810 2.4069 0.0012 +#> 211: 94.1011 -0.1828 2.1016 1.4582 0.5235 0.1825 2.4049 0.0011 +#> 212: 94.1081 -0.1839 2.0989 1.4657 0.5255 0.1838 2.4031 0.0010 +#> 213: 94.1264 -0.1842 2.0973 1.4527 0.5263 0.1851 2.4026 0.0010 +#> 214: 94.1287 -0.1844 2.0974 1.4405 0.5270 0.1869 2.4006 0.0009 +#> 215: 94.1440 -0.1850 2.0973 1.4556 0.5269 0.1876 2.3985 0.0009 +#> 216: 94.1352 -0.1863 2.0970 1.4698 0.5258 0.1885 2.3977 0.0008 +#> 217: 94.1261 -0.1868 2.0962 1.4850 0.5244 0.1897 2.3946 0.0008 +#> 218: 94.1100 -0.1858 2.0987 1.4673 0.5230 0.1934 2.3924 0.0007 +#> 219: 94.1073 -0.1845 2.1013 1.4630 0.5218 0.1993 2.3890 0.0011 +#> 220: 94.1026 -0.1836 2.1030 1.4705 0.5205 0.2028 2.3904 0.0010 +#> 221: 94.0972 -0.1824 2.1046 1.4732 0.5198 0.2065 2.3907 0.0010 +#> 222: 94.0898 -0.1824 2.1052 1.4952 0.5180 0.2083 2.3892 0.0010 +#> 223: 94.0975 -0.1830 2.1050 1.5035 0.5161 0.2107 2.3888 0.0011 +#> 224: 94.1027 -0.1831 2.1050 1.5196 0.5148 0.2124 2.3878 0.0011 +#> 225: 94.0977 -0.1828 2.1065 1.5153 0.5142 0.2141 2.3856 0.0013 +#> 226: 94.0907 -0.1831 2.1066 1.5287 0.5130 0.2151 2.3828 0.0014 +#> 227: 94.0831 -0.1833 2.1065 1.5535 0.5119 0.2159 2.3814 0.0014 +#> 228: 94.0834 -0.1832 2.1072 1.5713 0.5114 0.2174 2.3813 0.0014 +#> 229: 94.0793 -0.1832 2.1076 1.6041 0.5111 0.2184 2.3811 0.0015 +#> 230: 94.0701 -0.1843 2.1064 1.6177 0.5096 0.2181 2.3803 0.0017 +#> 231: 94.0598 -0.1853 2.1052 1.6254 0.5085 0.2180 2.3818 0.0016 +#> 232: 94.0539 -0.1862 2.1045 1.6254 0.5074 0.2175 2.3824 0.0017 +#> 233: 94.0498 -0.1869 2.1034 1.6380 0.5065 0.2169 2.3826 0.0017 +#> 234: 94.0514 -0.1872 2.1035 1.6300 0.5050 0.2160 2.3829 0.0017 +#> 235: 94.0521 -0.1876 2.1026 1.6263 0.5041 0.2148 2.3825 0.0018 +#> 236: 94.0587 -0.1876 2.1024 1.6277 0.5023 0.2134 2.3834 0.0020 +#> 237: 94.0741 -0.1873 2.1025 1.6349 0.5013 0.2120 2.3828 0.0019 +#> 238: 94.0898 -0.1876 2.1022 1.6509 0.4997 0.2107 2.3837 0.0019 +#> 239: 94.1055 -0.1880 2.1016 1.6596 0.4979 0.2098 2.3836 0.0018 +#> 240: 94.1209 -0.1885 2.1007 1.6627 0.4958 0.2092 2.3831 0.0018 +#> 241: 94.1322 -0.1893 2.0992 1.6563 0.4945 0.2085 2.3825 0.0017 +#> 242: 94.1404 -0.1904 2.0976 1.6574 0.4930 0.2082 2.3814 0.0017 +#> 243: 94.1428 -0.1914 2.0961 1.6412 0.4918 0.2078 2.3800 0.0017 +#> 244: 94.1477 -0.1923 2.0945 1.6287 0.4907 0.2071 2.3795 0.0016 +#> 245: 94.1525 -0.1931 2.0933 1.6225 0.4897 0.2064 2.3791 0.0016 +#> 246: 94.1557 -0.1938 2.0927 1.6243 0.4890 0.2048 2.3780 0.0016 +#> 247: 94.1576 -0.1943 2.0919 1.6333 0.4881 0.2034 2.3777 0.0015 +#> 248: 94.1603 -0.1951 2.0909 1.6328 0.4863 0.2026 2.3775 0.0015 +#> 249: 94.1648 -0.1957 2.0898 1.6427 0.4847 0.2018 2.3774 0.0015 +#> 250: 94.1766 -0.1963 2.0889 1.6482 0.4829 0.2012 2.3770 0.0015 +#> 251: 94.1854 -0.1971 2.0875 1.6536 0.4806 0.2011 2.3769 0.0016 +#> 252: 94.1906 -0.1980 2.0861 1.6527 0.4785 0.2013 2.3763 0.0017 +#> 253: 94.1913 -0.1982 2.0857 1.6459 0.4772 0.2014 2.3751 0.0019 +#> 254: 94.1945 -0.1985 2.0852 1.6413 0.4759 0.2019 2.3755 0.0019 +#> 255: 94.1972 -0.1989 2.0837 1.6451 0.4754 0.2027 2.3753 0.0018 +#> 256: 94.1994 -0.1989 2.0833 1.6548 0.4758 0.2024 2.3752 0.0018 +#> 257: 94.2014 -0.1987 2.0833 1.6708 0.4765 0.2024 2.3752 0.0018 +#> 258: 94.2081 -0.1984 2.0836 1.6903 0.4768 0.2023 2.3749 0.0017 +#> 259: 94.2151 -0.1982 2.0839 1.7169 0.4767 0.2023 2.3737 0.0017 +#> 260: 94.2212 -0.1980 2.0838 1.7426 0.4766 0.2031 2.3725 0.0017 +#> 261: 94.2229 -0.1981 2.0835 1.7696 0.4764 0.2038 2.3714 0.0017 +#> 262: 94.2213 -0.1983 2.0832 1.7977 0.4762 0.2045 2.3704 0.0016 +#> 263: 94.2220 -0.1984 2.0830 1.8277 0.4764 0.2051 2.3700 0.0016 +#> 264: 94.2230 -0.1983 2.0830 1.8430 0.4766 0.2057 2.3690 0.0016 +#> 265: 94.2235 -0.1983 2.0832 1.8679 0.4768 0.2060 2.3674 0.0016 +#> 266: 94.2242 -0.1982 2.0833 1.8705 0.4769 0.2064 2.3658 0.0015 +#> 267: 94.2267 -0.1982 2.0832 1.8715 0.4769 0.2070 2.3643 0.0015 +#> 268: 94.2312 -0.1980 2.0834 1.8824 0.4769 0.2074 2.3631 0.0015 +#> 269: 94.2329 -0.1981 2.0829 1.8843 0.4766 0.2084 2.3628 0.0015 +#> 270: 94.2321 -0.1982 2.0825 1.8904 0.4770 0.2093 2.3629 0.0015 +#> 271: 94.2349 -0.1985 2.0820 1.8942 0.4769 0.2101 2.3633 0.0016 +#> 272: 94.2388 -0.1989 2.0818 1.9099 0.4767 0.2110 2.3634 0.0018 +#> 273: 94.2420 -0.1992 2.0816 1.9259 0.4765 0.2118 2.3632 0.0018 +#> 274: 94.2454 -0.1994 2.0813 1.9330 0.4763 0.2128 2.3629 0.0017 +#> 275: 94.2456 -0.1997 2.0810 1.9316 0.4761 0.2138 2.3624 0.0018 +#> 276: 94.2472 -0.1999 2.0807 1.9306 0.4758 0.2146 2.3624 0.0019 +#> 277: 94.2492 -0.2001 2.0808 1.9326 0.4756 0.2153 2.3623 0.0020 +#> 278: 94.2493 -0.2003 2.0807 1.9225 0.4752 0.2163 2.3628 0.0020 +#> 279: 94.2481 -0.2002 2.0808 1.9206 0.4750 0.2168 2.3628 0.0019 +#> 280: 94.2433 -0.2002 2.0810 1.9257 0.4749 0.2173 2.3626 0.0019 +#> 281: 94.2358 -0.2004 2.0809 1.9217 0.4748 0.2173 2.3620 0.0019 +#> 282: 94.2307 -0.2005 2.0807 1.9209 0.4748 0.2172 2.3617 0.0019 +#> 283: 94.2302 -0.2008 2.0803 1.9131 0.4748 0.2172 2.3615 0.0019 +#> 284: 94.2309 -0.2009 2.0802 1.9085 0.4749 0.2171 2.3610 0.0018 +#> 285: 94.2344 -0.2010 2.0799 1.9135 0.4749 0.2170 2.3603 0.0018 +#> 286: 94.2381 -0.2013 2.0794 1.9099 0.4749 0.2167 2.3596 0.0018 +#> 287: 94.2420 -0.2016 2.0786 1.9105 0.4749 0.2164 2.3596 0.0018 +#> 288: 94.2425 -0.2020 2.0778 1.9081 0.4749 0.2161 2.3590 0.0019 +#> 289: 94.2386 -0.2023 2.0773 1.9136 0.4749 0.2158 2.3586 0.0019 +#> 290: 94.2357 -0.2026 2.0768 1.9171 0.4750 0.2154 2.3581 0.0019 +#> 291: 94.2326 -0.2026 2.0765 1.9162 0.4750 0.2150 2.3577 0.0019 +#> 292: 94.2305 -0.2026 2.0766 1.9178 0.4753 0.2144 2.3577 0.0020 +#> 293: 94.2268 -0.2023 2.0771 1.9257 0.4754 0.2138 2.3574 0.0022 +#> 294: 94.2216 -0.2023 2.0773 1.9326 0.4754 0.2132 2.3565 0.0023 +#> 295: 94.2193 -0.2024 2.0769 1.9378 0.4762 0.2125 2.3565 0.0024 +#> 296: 94.2160 -0.2025 2.0765 1.9463 0.4771 0.2117 2.3565 0.0025 +#> 297: 94.2106 -0.2026 2.0761 1.9523 0.4779 0.2109 2.3569 0.0026 +#> 298: 94.2089 -0.2028 2.0756 1.9622 0.4787 0.2099 2.3578 0.0025 +#> 299: 94.2077 -0.2029 2.0753 1.9721 0.4794 0.2090 2.3586 0.0026 +#> 300: 94.2064 -0.2030 2.0749 1.9838 0.4802 0.2080 2.3589 0.0026 +#> 301: 94.2086 -0.2029 2.0747 1.9942 0.4806 0.2071 2.3587 0.0025 +#> 302: 94.2111 -0.2031 2.0744 1.9938 0.4810 0.2063 2.3593 0.0025 +#> 303: 94.2133 -0.2031 2.0743 1.9923 0.4811 0.2056 2.3593 0.0025 +#> 304: 94.2151 -0.2032 2.0739 1.9885 0.4811 0.2049 2.3595 0.0025 +#> 305: 94.2159 -0.2035 2.0735 1.9872 0.4813 0.2044 2.3594 0.0024 +#> 306: 94.2192 -0.2038 2.0729 1.9806 0.4813 0.2041 2.3592 0.0024 +#> 307: 94.2226 -0.2040 2.0724 1.9796 0.4814 0.2038 2.3588 0.0024 +#> 308: 94.2224 -0.2042 2.0723 1.9828 0.4814 0.2036 2.3589 0.0024 +#> 309: 94.2200 -0.2043 2.0723 1.9859 0.4812 0.2034 2.3587 0.0024 +#> 310: 94.2183 -0.2044 2.0723 1.9892 0.4810 0.2034 2.3583 0.0023 +#> 311: 94.2175 -0.2044 2.0724 1.9895 0.4805 0.2033 2.3580 0.0023 +#> 312: 94.2171 -0.2044 2.0725 1.9977 0.4800 0.2032 2.3581 0.0023 +#> 313: 94.2108 -0.2044 2.0728 1.9995 0.4795 0.2030 2.3578 0.0023 +#> 314: 94.2068 -0.2045 2.0730 1.9929 0.4790 0.2029 2.3576 0.0024 +#> 315: 94.2031 -0.2047 2.0730 1.9884 0.4784 0.2028 2.3579 0.0024 +#> 316: 94.2018 -0.2048 2.0731 1.9860 0.4779 0.2026 2.3582 0.0024 +#> 317: 94.2015 -0.2050 2.0729 1.9836 0.4773 0.2025 2.3582 0.0024 +#> 318: 94.2025 -0.2052 2.0728 1.9814 0.4768 0.2024 2.3580 0.0023 +#> 319: 94.2066 -0.2053 2.0726 1.9867 0.4764 0.2024 2.3577 0.0023 +#> 320: 94.2074 -0.2055 2.0727 1.9896 0.4760 0.2024 2.3575 0.0023 +#> 321: 94.2097 -0.2055 2.0728 1.9985 0.4758 0.2026 2.3573 0.0023 +#> 322: 94.2080 -0.2054 2.0731 2.0108 0.4759 0.2028 2.3570 0.0023 +#> 323: 94.2042 -0.2054 2.0732 2.0253 0.4762 0.2030 2.3566 0.0023 +#> 324: 94.2005 -0.2054 2.0733 2.0514 0.4765 0.2032 2.3566 0.0023 +#> 325: 94.2000 -0.2053 2.0735 2.0719 0.4767 0.2034 2.3570 0.0023 +#> 326: 94.2002 -0.2052 2.0738 2.0907 0.4769 0.2034 2.3573 0.0023 +#> 327: 94.1997 -0.2051 2.0741 2.1140 0.4770 0.2035 2.3571 0.0023 +#> 328: 94.1976 -0.2050 2.0743 2.1379 0.4770 0.2035 2.3569 0.0023 +#> 329: 94.1969 -0.2051 2.0741 2.1485 0.4769 0.2038 2.3566 0.0022 +#> 330: 94.1959 -0.2053 2.0738 2.1533 0.4767 0.2042 2.3561 0.0022 +#> 331: 94.1962 -0.2055 2.0733 2.1588 0.4763 0.2046 2.3555 0.0022 +#> 332: 94.1967 -0.2059 2.0727 2.1626 0.4760 0.2051 2.3551 0.0022 +#> 333: 94.1964 -0.2062 2.0721 2.1666 0.4757 0.2056 2.3547 0.0022 +#> 334: 94.1978 -0.2064 2.0718 2.1703 0.4756 0.2063 2.3543 0.0022 +#> 335: 94.1985 -0.2066 2.0715 2.1698 0.4755 0.2068 2.3538 0.0021 +#> 336: 94.1999 -0.2068 2.0711 2.1705 0.4757 0.2075 2.3534 0.0021 +#> 337: 94.1990 -0.2069 2.0708 2.1690 0.4759 0.2080 2.3530 0.0021 +#> 338: 94.1965 -0.2071 2.0706 2.1708 0.4760 0.2085 2.3525 0.0021 +#> 339: 94.1934 -0.2071 2.0704 2.1769 0.4761 0.2088 2.3518 0.0021 +#> 340: 94.1908 -0.2072 2.0704 2.1794 0.4763 0.2091 2.3515 0.0021 +#> 341: 94.1875 -0.2072 2.0706 2.1859 0.4762 0.2092 2.3512 0.0021 +#> 342: 94.1840 -0.2071 2.0707 2.1903 0.4762 0.2093 2.3513 0.0021 +#> 343: 94.1816 -0.2072 2.0706 2.1909 0.4761 0.2093 2.3512 0.0020 +#> 344: 94.1815 -0.2070 2.0708 2.1877 0.4758 0.2091 2.3514 0.0021 +#> 345: 94.1839 -0.2070 2.0710 2.1844 0.4757 0.2090 2.3517 0.0021 +#> 346: 94.1868 -0.2068 2.0713 2.1787 0.4756 0.2088 2.3520 0.0020 +#> 347: 94.1871 -0.2066 2.0717 2.1762 0.4756 0.2086 2.3519 0.0020 +#> 348: 94.1868 -0.2064 2.0722 2.1724 0.4756 0.2084 2.3521 0.0020 +#> 349: 94.1892 -0.2062 2.0725 2.1673 0.4755 0.2080 2.3524 0.0020 +#> 350: 94.1921 -0.2060 2.0726 2.1632 0.4754 0.2076 2.3527 0.0020 +#> 351: 94.1947 -0.2060 2.0726 2.1613 0.4752 0.2073 2.3530 0.0020 +#> 352: 94.1988 -0.2060 2.0725 2.1647 0.4751 0.2069 2.3530 0.0020 +#> 353: 94.2036 -0.2061 2.0721 2.1684 0.4749 0.2067 2.3530 0.0020 +#> 354: 94.2082 -0.2061 2.0719 2.1670 0.4747 0.2063 2.3529 0.0020 +#> 355: 94.2111 -0.2061 2.0718 2.1645 0.4747 0.2062 2.3526 0.0020 +#> 356: 94.2123 -0.2061 2.0717 2.1628 0.4747 0.2063 2.3525 0.0020 +#> 357: 94.2146 -0.2062 2.0716 2.1610 0.4746 0.2064 2.3523 0.0020 +#> 358: 94.2161 -0.2062 2.0715 2.1656 0.4744 0.2065 2.3520 0.0020 +#> 359: 94.2178 -0.2063 2.0714 2.1684 0.4743 0.2065 2.3516 0.0020 +#> 360: 94.2194 -0.2063 2.0713 2.1687 0.4742 0.2065 2.3512 0.0019 +#> 361: 94.2191 -0.2064 2.0713 2.1738 0.4741 0.2065 2.3508 0.0019 +#> 362: 94.2186 -0.2064 2.0713 2.1762 0.4740 0.2065 2.3502 0.0019 +#> 363: 94.2179 -0.2064 2.0714 2.1754 0.4740 0.2065 2.3495 0.0019 +#> 364: 94.2165 -0.2063 2.0715 2.1740 0.4741 0.2064 2.3495 0.0019 +#> 365: 94.2149 -0.2063 2.0716 2.1736 0.4741 0.2062 2.3495 0.0020 +#> 366: 94.2141 -0.2062 2.0717 2.1813 0.4740 0.2064 2.3490 0.0020 +#> 367: 94.2158 -0.2062 2.0717 2.1905 0.4739 0.2063 2.3491 0.0019 +#> 368: 94.2173 -0.2062 2.0718 2.1963 0.4737 0.2063 2.3485 0.0019 +#> 369: 94.2183 -0.2062 2.0717 2.2005 0.4736 0.2064 2.3481 0.0019 +#> 370: 94.2194 -0.2062 2.0716 2.2016 0.4735 0.2063 2.3477 0.0019 +#> 371: 94.2192 -0.2063 2.0715 2.1997 0.4733 0.2064 2.3476 0.0019 +#> 372: 94.2202 -0.2062 2.0716 2.1957 0.4733 0.2065 2.3479 0.0019 +#> 373: 94.2208 -0.2061 2.0717 2.1913 0.4733 0.2065 2.3480 0.0019 +#> 374: 94.2209 -0.2061 2.0719 2.1870 0.4731 0.2065 2.3479 0.0019 +#> 375: 94.2219 -0.2061 2.0719 2.1864 0.4729 0.2064 2.3477 0.0019 +#> 376: 94.2231 -0.2061 2.0720 2.1849 0.4726 0.2063 2.3473 0.0019 +#> 377: 94.2251 -0.2061 2.0720 2.1835 0.4724 0.2063 2.3471 0.0019 +#> 378: 94.2238 -0.2062 2.0719 2.1777 0.4721 0.2062 2.3472 0.0018 +#> 379: 94.2226 -0.2064 2.0717 2.1741 0.4717 0.2063 2.3471 0.0018 +#> 380: 94.2216 -0.2066 2.0714 2.1759 0.4714 0.2063 2.3468 0.0018 +#> 381: 94.2206 -0.2068 2.0711 2.1784 0.4711 0.2063 2.3465 0.0018 +#> 382: 94.2200 -0.2071 2.0707 2.1753 0.4707 0.2062 2.3462 0.0018 +#> 383: 94.2205 -0.2073 2.0704 2.1757 0.4703 0.2061 2.3461 0.0018 +#> 384: 94.2201 -0.2076 2.0702 2.1802 0.4698 0.2060 2.3458 0.0018 +#> 385: 94.2210 -0.2078 2.0701 2.1795 0.4693 0.2061 2.3457 0.0018 +#> 386: 94.2199 -0.2079 2.0700 2.1788 0.4688 0.2061 2.3455 0.0018 +#> 387: 94.2181 -0.2081 2.0699 2.1801 0.4683 0.2061 2.3454 0.0018 +#> 388: 94.2169 -0.2082 2.0699 2.1850 0.4679 0.2061 2.3452 0.0017 +#> 389: 94.2158 -0.2083 2.0699 2.1881 0.4674 0.2063 2.3449 0.0017 +#> 390: 94.2162 -0.2084 2.0696 2.1928 0.4671 0.2064 2.3447 0.0017 +#> 391: 94.2172 -0.2085 2.0696 2.1921 0.4669 0.2063 2.3444 0.0017 +#> 392: 94.2175 -0.2085 2.0695 2.1933 0.4667 0.2063 2.3442 0.0017 +#> 393: 94.2174 -0.2086 2.0695 2.1972 0.4666 0.2062 2.3440 0.0017 +#> 394: 94.2179 -0.2087 2.0694 2.1972 0.4664 0.2061 2.3439 0.0017 +#> 395: 94.2200 -0.2087 2.0694 2.2009 0.4663 0.2059 2.3438 0.0017 +#> 396: 94.2189 -0.2086 2.0695 2.2062 0.4662 0.2058 2.3434 0.0017 +#> 397: 94.2183 -0.2085 2.0696 2.2151 0.4663 0.2056 2.3431 0.0017 +#> 398: 94.2186 -0.2085 2.0696 2.2200 0.4664 0.2056 2.3430 0.0017 +#> 399: 94.2183 -0.2084 2.0698 2.2204 0.4664 0.2056 2.3428 0.0017 +#> 400: 94.2184 -0.2082 2.0703 2.2252 0.4665 0.2054 2.3428 0.0016 +#> 401: 94.2176 -0.2080 2.0707 2.2323 0.4666 0.2052 2.3427 0.0016 +#> 402: 94.2167 -0.2078 2.0712 2.2397 0.4668 0.2050 2.3426 0.0016 +#> 403: 94.2157 -0.2075 2.0716 2.2464 0.4669 0.2049 2.3426 0.0016 +#> 404: 94.2152 -0.2074 2.0719 2.2508 0.4670 0.2047 2.3427 0.0016 +#> 405: 94.2152 -0.2072 2.0723 2.2537 0.4671 0.2046 2.3427 0.0016 +#> 406: 94.2151 -0.2070 2.0726 2.2565 0.4672 0.2044 2.3427 0.0016 +#> 407: 94.2132 -0.2067 2.0731 2.2568 0.4673 0.2044 2.3426 0.0016 +#> 408: 94.2142 -0.2065 2.0734 2.2579 0.4674 0.2046 2.3424 0.0016 +#> 409: 94.2136 -0.2063 2.0738 2.2630 0.4674 0.2046 2.3420 0.0016 +#> 410: 94.2125 -0.2062 2.0739 2.2635 0.4674 0.2047 2.3417 0.0016 +#> 411: 94.2131 -0.2061 2.0741 2.2634 0.4674 0.2048 2.3413 0.0016 +#> 412: 94.2132 -0.2060 2.0742 2.2662 0.4674 0.2048 2.3409 0.0016 +#> 413: 94.2143 -0.2059 2.0743 2.2666 0.4673 0.2048 2.3407 0.0016 +#> 414: 94.2156 -0.2058 2.0743 2.2710 0.4672 0.2048 2.3404 0.0015 +#> 415: 94.2174 -0.2057 2.0745 2.2751 0.4671 0.2049 2.3400 0.0015 +#> 416: 94.2185 -0.2057 2.0746 2.2762 0.4669 0.2049 2.3399 0.0015 +#> 417: 94.2208 -0.2056 2.0748 2.2759 0.4667 0.2049 2.3397 0.0015 +#> 418: 94.2231 -0.2054 2.0751 2.2772 0.4664 0.2050 2.3398 0.0015 +#> 419: 94.2249 -0.2053 2.0754 2.2783 0.4663 0.2050 2.3396 0.0015 +#> 420: 94.2255 -0.2052 2.0757 2.2798 0.4660 0.2050 2.3395 0.0015 +#> 421: 94.2265 -0.2051 2.0759 2.2848 0.4659 0.2050 2.3392 0.0016 +#> 422: 94.2288 -0.2049 2.0761 2.2929 0.4659 0.2050 2.3390 0.0016 +#> 423: 94.2307 -0.2048 2.0762 2.2988 0.4657 0.2051 2.3390 0.0016 +#> 424: 94.2313 -0.2047 2.0764 2.3017 0.4656 0.2051 2.3391 0.0016 +#> 425: 94.2322 -0.2046 2.0765 2.3028 0.4655 0.2050 2.3388 0.0016 +#> 426: 94.2327 -0.2046 2.0765 2.3049 0.4654 0.2050 2.3386 0.0016 +#> 427: 94.2323 -0.2045 2.0768 2.3053 0.4655 0.2049 2.3386 0.0016 +#> 428: 94.2324 -0.2044 2.0770 2.3016 0.4655 0.2048 2.3387 0.0017 +#> 429: 94.2322 -0.2043 2.0772 2.2984 0.4656 0.2047 2.3386 0.0017 +#> 430: 94.2306 -0.2042 2.0774 2.2971 0.4656 0.2046 2.3384 0.0017 +#> 431: 94.2295 -0.2042 2.0775 2.2931 0.4657 0.2044 2.3384 0.0017 +#> 432: 94.2298 -0.2040 2.0778 2.2896 0.4656 0.2044 2.3383 0.0018 +#> 433: 94.2311 -0.2039 2.0780 2.2885 0.4656 0.2044 2.3383 0.0018 +#> 434: 94.2311 -0.2037 2.0783 2.2854 0.4655 0.2044 2.3381 0.0018 +#> 435: 94.2314 -0.2036 2.0786 2.2838 0.4654 0.2044 2.3378 0.0018 +#> 436: 94.2315 -0.2035 2.0788 2.2817 0.4653 0.2044 2.3377 0.0018 +#> 437: 94.2326 -0.2034 2.0790 2.2801 0.4652 0.2044 2.3378 0.0018 +#> 438: 94.2338 -0.2034 2.0791 2.2802 0.4650 0.2046 2.3380 0.0018 +#> 439: 94.2340 -0.2033 2.0791 2.2810 0.4649 0.2046 2.3377 0.0018 +#> 440: 94.2330 -0.2034 2.0791 2.2822 0.4646 0.2046 2.3376 0.0018 +#> 441: 94.2323 -0.2035 2.0790 2.2818 0.4644 0.2046 2.3375 0.0018 +#> 442: 94.2321 -0.2034 2.0792 2.2804 0.4642 0.2043 2.3375 0.0018 +#> 443: 94.2313 -0.2033 2.0794 2.2812 0.4641 0.2041 2.3372 0.0018 +#> 444: 94.2301 -0.2032 2.0796 2.2820 0.4640 0.2040 2.3369 0.0018 +#> 445: 94.2279 -0.2031 2.0799 2.2872 0.4639 0.2039 2.3366 0.0018 +#> 446: 94.2272 -0.2030 2.0801 2.2874 0.4639 0.2037 2.3363 0.0018 +#> 447: 94.2262 -0.2029 2.0803 2.2881 0.4639 0.2036 2.3359 0.0018 +#> 448: 94.2248 -0.2028 2.0806 2.2905 0.4639 0.2036 2.3358 0.0018 +#> 449: 94.2245 -0.2027 2.0808 2.2914 0.4638 0.2035 2.3356 0.0018 +#> 450: 94.2237 -0.2027 2.0809 2.2928 0.4638 0.2035 2.3356 0.0018 +#> 451: 94.2233 -0.2025 2.0813 2.2917 0.4639 0.2033 2.3355 0.0018 +#> 452: 94.2232 -0.2023 2.0816 2.2898 0.4640 0.2031 2.3356 0.0018 +#> 453: 94.2230 -0.2021 2.0819 2.2890 0.4641 0.2030 2.3356 0.0018 +#> 454: 94.2222 -0.2020 2.0822 2.2851 0.4641 0.2029 2.3357 0.0018 +#> 455: 94.2214 -0.2018 2.0824 2.2820 0.4640 0.2028 2.3357 0.0017 +#> 456: 94.2212 -0.2017 2.0827 2.2797 0.4640 0.2026 2.3357 0.0017 +#> 457: 94.2216 -0.2016 2.0829 2.2771 0.4640 0.2024 2.3358 0.0017 +#> 458: 94.2220 -0.2015 2.0831 2.2740 0.4639 0.2022 2.3358 0.0017 +#> 459: 94.2229 -0.2013 2.0834 2.2765 0.4638 0.2021 2.3358 0.0017 +#> 460: 94.2226 -0.2012 2.0837 2.2810 0.4637 0.2020 2.3359 0.0017 +#> 461: 94.2227 -0.2009 2.0841 2.2893 0.4637 0.2018 2.3358 0.0017 +#> 462: 94.2235 -0.2007 2.0844 2.2942 0.4637 0.2016 2.3357 0.0017 +#> 463: 94.2241 -0.2005 2.0848 2.2971 0.4637 0.2014 2.3358 0.0017 +#> 464: 94.2236 -0.2002 2.0853 2.2953 0.4637 0.2012 2.3360 0.0017 +#> 465: 94.2230 -0.2000 2.0858 2.2946 0.4638 0.2010 2.3360 0.0017 +#> 466: 94.2215 -0.1997 2.0863 2.2995 0.4638 0.2009 2.3363 0.0017 +#> 467: 94.2193 -0.1995 2.0868 2.3051 0.4637 0.2008 2.3363 0.0017 +#> 468: 94.2174 -0.1992 2.0874 2.3086 0.4636 0.2006 2.3363 0.0018 +#> 469: 94.2160 -0.1989 2.0881 2.3072 0.4636 0.2006 2.3361 0.0018 +#> 470: 94.2152 -0.1985 2.0887 2.3075 0.4637 0.2005 2.3363 0.0018 +#> 471: 94.2139 -0.1982 2.0891 2.3126 0.4638 0.2004 2.3361 0.0018 +#> 472: 94.2134 -0.1980 2.0895 2.3151 0.4640 0.2002 2.3360 0.0018 +#> 473: 94.2141 -0.1979 2.0897 2.3149 0.4640 0.2001 2.3360 0.0018 +#> 474: 94.2144 -0.1978 2.0900 2.3140 0.4640 0.2001 2.3358 0.0018 +#> 475: 94.2151 -0.1977 2.0901 2.3151 0.4640 0.2000 2.3358 0.0018 +#> 476: 94.2154 -0.1975 2.0903 2.3195 0.4641 0.2001 2.3357 0.0018 +#> 477: 94.2167 -0.1974 2.0905 2.3253 0.4642 0.2002 2.3358 0.0018 +#> 478: 94.2163 -0.1972 2.0909 2.3324 0.4641 0.2004 2.3357 0.0017 +#> 479: 94.2156 -0.1970 2.0912 2.3364 0.4640 0.2006 2.3355 0.0017 +#> 480: 94.2149 -0.1969 2.0915 2.3395 0.4638 0.2007 2.3353 0.0017 +#> 481: 94.2140 -0.1968 2.0918 2.3431 0.4637 0.2008 2.3350 0.0017 +#> 482: 94.2137 -0.1967 2.0919 2.3440 0.4635 0.2010 2.3349 0.0017 +#> 483: 94.2139 -0.1966 2.0920 2.3468 0.4634 0.2011 2.3348 0.0017 +#> 484: 94.2149 -0.1966 2.0921 2.3488 0.4633 0.2012 2.3346 0.0017 +#> 485: 94.2153 -0.1966 2.0921 2.3486 0.4632 0.2012 2.3345 0.0017 +#> 486: 94.2148 -0.1965 2.0923 2.3483 0.4631 0.2015 2.3345 0.0017 +#> 487: 94.2140 -0.1965 2.0923 2.3492 0.4628 0.2018 2.3345 0.0017 +#> 488: 94.2121 -0.1965 2.0923 2.3489 0.4625 0.2020 2.3347 0.0017 +#> 489: 94.2119 -0.1966 2.0923 2.3497 0.4622 0.2023 2.3346 0.0017 +#> 490: 94.2120 -0.1966 2.0923 2.3476 0.4618 0.2025 2.3346 0.0017 +#> 491: 94.2124 -0.1966 2.0923 2.3462 0.4615 0.2028 2.3346 0.0017 +#> 492: 94.2118 -0.1966 2.0923 2.3453 0.4613 0.2029 2.3346 0.0017 +#> 493: 94.2113 -0.1967 2.0923 2.3452 0.4610 0.2030 2.3347 0.0017 +#> 494: 94.2118 -0.1968 2.0922 2.3488 0.4608 0.2030 2.3347 0.0017 +#> 495: 94.2122 -0.1969 2.0920 2.3530 0.4605 0.2029 2.3347 0.0017 +#> 496: 94.2138 -0.1969 2.0919 2.3540 0.4603 0.2028 2.3350 0.0017 +#> 497: 94.2148 -0.1970 2.0917 2.3554 0.4601 0.2029 2.3352 0.0017 +#> 498: 94.2152 -0.1971 2.0916 2.3534 0.4600 0.2029 2.3356 0.0017 +#> 499: 94.2157 -0.1972 2.0914 2.3519 0.4598 0.2029 2.3357 0.0016 +#> 500: 94.2162 -0.1973 2.0912 2.3498 0.4596 0.2030 2.3358 0.0016</div><div class='output co'>#> <span class='message'>Calculating covariance matrix</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='input'><span class='va'>f_nlmixr_fomc_focei_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span style='font-weight: bold;'>Key:</span> U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation +#> F: Forward difference gradient approximation +#> C: Central difference gradient approximation +#> M: Mixed forward and central difference gradient approximation +#> Unscaled parameters for Omegas=chol(solve(omega)); +#> Diagonals are transformed, as specified by foceiControl(diagXform=) +#> |-----+---------------+-----------+-----------+-----------+-----------| +#> | #| Objective Fun | parent_0 | log_alpha | log_beta | sigma_low | +#> |.....................| rsd_high | o1 | o2 | o3 | +#> |<span style='font-weight: bold;'> 1</span>| 356.08238 | 1.000 | -1.000 | -0.9495 | -0.9739 | +#> |.....................| -0.9969 | -0.9818 | -0.9750 | -0.9744 | +#> | U| 356.08238 | 93.10 | -0.1209 | 2.232 | 1.095 | +#> |.....................| 0.02509 | 0.7272 | 1.045 | 1.072 | +#> | X|<span style='font-weight: bold;'> 356.08238</span> | 93.10 | 0.8861 | 9.321 | 1.095 | +#> |.....................| 0.02509 | 0.7272 | 1.045 | 1.072 | +#> | G| Gill Diff. | -85.81 | 0.5929 | 0.9043 | -97.79 | +#> |.....................| -28.71 | -0.07427 | -8.550 | -12.99 | +#> |<span style='font-weight: bold;'> 2</span>| 1940.7752 | 1.640 | -1.004 | -0.9563 | -0.2449 | +#> |.....................| -0.7829 | -0.9813 | -0.9112 | -0.8775 | +#> | U| 1940.7752 | 152.7 | -0.1253 | 2.226 | 1.495 | +#> |.....................| 0.02778 | 0.7276 | 1.112 | 1.176 | +#> | X|<span style='font-weight: bold;'> 1940.7752</span> | 152.7 | 0.8822 | 9.258 | 1.495 | +#> |.....................| 0.02778 | 0.7276 | 1.112 | 1.176 | +#> |<span style='font-weight: bold;'> 3</span>| 370.78508 | 1.064 | -1.000 | -0.9502 | -0.9010 | +#> |.....................| -0.9755 | -0.9817 | -0.9686 | -0.9647 | +#> | U| 370.78508 | 99.05 | -0.1213 | 2.232 | 1.135 | +#> |.....................| 0.02536 | 0.7272 | 1.052 | 1.082 | +#> | X|<span style='font-weight: bold;'> 370.78508</span> | 99.05 | 0.8857 | 9.315 | 1.135 | +#> |.....................| 0.02536 | 0.7272 | 1.052 | 1.082 | +#> |<span style='font-weight: bold;'> 4</span>| 354.52588 | 1.015 | -1.000 | -0.9497 | -0.9565 | +#> |.....................| -0.9918 | -0.9818 | -0.9735 | -0.9721 | +#> | U| 354.52588 | 94.52 | -0.1210 | 2.232 | 1.105 | +#> |.....................| 0.02516 | 0.7272 | 1.047 | 1.074 | +#> | X|<span style='font-weight: bold;'> 354.52588</span> | 94.52 | 0.8860 | 9.319 | 1.105 | +#> |.....................| 0.02516 | 0.7272 | 1.047 | 1.074 | +#> | F| Forward Diff. | 126.3 | 0.7329 | 1.391 | -95.71 | +#> |.....................| -26.58 | 0.4812 | -8.528 | -12.76 | +#> |<span style='font-weight: bold;'> 5</span>| 352.43362 | 0.9998 | -1.000 | -0.9499 | -0.9392 | +#> |.....................| -0.9869 | -0.9819 | -0.9719 | -0.9698 | +#> | U| 352.43362 | 93.08 | -0.1211 | 2.232 | 1.114 | +#> |.....................| 0.02522 | 0.7271 | 1.048 | 1.077 | +#> | X|<span style='font-weight: bold;'> 352.43362</span> | 93.08 | 0.8859 | 9.317 | 1.114 | +#> |.....................| 0.02522 | 0.7271 | 1.048 | 1.077 | +#> | F| Forward Diff. | -88.58 | 0.5971 | 0.9141 | -92.65 | +#> |.....................| -26.61 | -0.01862 | -8.458 | -12.78 | +#> |<span style='font-weight: bold;'> 6</span>| 350.82994 | 1.015 | -1.000 | -0.9501 | -0.9214 | +#> |.....................| -0.9818 | -0.9819 | -0.9703 | -0.9673 | +#> | U| 350.82994 | 94.46 | -0.1213 | 2.232 | 1.124 | +#> |.....................| 0.02528 | 0.7271 | 1.050 | 1.079 | +#> | X|<span style='font-weight: bold;'> 350.82994</span> | 94.46 | 0.8858 | 9.315 | 1.124 | +#> |.....................| 0.02528 | 0.7271 | 1.050 | 1.079 | +#> | F| Forward Diff. | 115.7 | 0.7442 | 1.407 | -90.51 | +#> |.....................| -24.67 | 0.2416 | -8.378 | -12.59 | +#> |<span style='font-weight: bold;'> 7</span>| 348.85697 | 1.000 | -1.000 | -0.9503 | -0.9035 | +#> |.....................| -0.9769 | -0.9819 | -0.9686 | -0.9649 | +#> | U| 348.85697 | 93.10 | -0.1214 | 2.231 | 1.134 | +#> |.....................| 0.02534 | 0.7271 | 1.052 | 1.082 | +#> | X|<span style='font-weight: bold;'> 348.85697</span> | 93.10 | 0.8857 | 9.313 | 1.134 | +#> |.....................| 0.02534 | 0.7271 | 1.052 | 1.082 | +#> | F| Forward Diff. | -86.89 | 0.6078 | 0.9395 | -87.49 | +#> |.....................| -24.70 | -0.2033 | -8.301 | -12.59 | +#> |<span style='font-weight: bold;'> 8</span>| 347.23757 | 1.014 | -1.001 | -0.9506 | -0.8852 | +#> |.....................| -0.9717 | -0.9819 | -0.9669 | -0.9622 | +#> | U| 347.23757 | 94.41 | -0.1215 | 2.231 | 1.144 | +#> |.....................| 0.02541 | 0.7271 | 1.054 | 1.085 | +#> | X|<span style='font-weight: bold;'> 347.23757</span> | 94.41 | 0.8856 | 9.311 | 1.144 | +#> |.....................| 0.02541 | 0.7271 | 1.054 | 1.085 | +#> | F| Forward Diff. | 106.0 | 0.7499 | 1.419 | -85.67 | +#> |.....................| -22.89 | -0.09812 | -8.213 | -12.39 | +#> |<span style='font-weight: bold;'> 9</span>| 345.37317 | 1.000 | -1.001 | -0.9508 | -0.8667 | +#> |.....................| -0.9667 | -0.9818 | -0.9651 | -0.9596 | +#> | U| 345.37317 | 93.12 | -0.1217 | 2.231 | 1.154 | +#> |.....................| 0.02547 | 0.7272 | 1.056 | 1.088 | +#> | X|<span style='font-weight: bold;'> 345.37317</span> | 93.12 | 0.8854 | 9.308 | 1.154 | +#> |.....................| 0.02547 | 0.7272 | 1.056 | 1.088 | +#> | F| Forward Diff. | -84.47 | 0.6193 | 0.9668 | -82.72 | +#> |.....................| -22.87 | -0.2860 | -8.128 | -12.38 | +#> |<span style='font-weight: bold;'> 10</span>| 343.77522 | 1.014 | -1.001 | -0.9511 | -0.8479 | +#> |.....................| -0.9616 | -0.9818 | -0.9633 | -0.9568 | +#> | U| 343.77522 | 94.37 | -0.1218 | 2.231 | 1.164 | +#> |.....................| 0.02554 | 0.7272 | 1.057 | 1.091 | +#> | X|<span style='font-weight: bold;'> 343.77522</span> | 94.37 | 0.8853 | 9.306 | 1.164 | +#> |.....................| 0.02554 | 0.7272 | 1.057 | 1.091 | +#> | F| Forward Diff. | 98.54 | 0.7582 | 1.440 | -80.80 | +#> |.....................| -21.11 | -0.2480 | -8.037 | -12.18 | +#> |<span style='font-weight: bold;'> 11</span>| 342.01002 | 1.000 | -1.001 | -0.9514 | -0.8290 | +#> |.....................| -0.9566 | -0.9817 | -0.9614 | -0.9539 | +#> | U| 342.01002 | 93.14 | -0.1220 | 2.230 | 1.175 | +#> |.....................| 0.02560 | 0.7273 | 1.059 | 1.094 | +#> | X|<span style='font-weight: bold;'> 342.01002</span> | 93.14 | 0.8852 | 9.303 | 1.175 | +#> |.....................| 0.02560 | 0.7273 | 1.059 | 1.094 | +#> | F| Forward Diff. | -81.78 | 0.6281 | 0.9934 | -78.17 | +#> |.....................| -21.11 | -0.4903 | -7.943 | -12.16 | +#> |<span style='font-weight: bold;'> 12</span>| 340.43696 | 1.013 | -1.001 | -0.9517 | -0.8098 | +#> |.....................| -0.9515 | -0.9816 | -0.9595 | -0.9509 | +#> | U| 340.43696 | 94.32 | -0.1222 | 2.230 | 1.185 | +#> |.....................| 0.02566 | 0.7274 | 1.062 | 1.097 | +#> | X|<span style='font-weight: bold;'> 340.43696</span> | 94.32 | 0.8850 | 9.301 | 1.185 | +#> |.....................| 0.02566 | 0.7274 | 1.062 | 1.097 | +#> | F| Forward Diff. | 90.87 | 0.7671 | 1.462 | -75.86 | +#> |.....................| -19.30 | -0.2119 | -7.851 | -11.96 | +#> |<span style='font-weight: bold;'> 13</span>| 338.78414 | 1.001 | -1.001 | -0.9520 | -0.7906 | +#> |.....................| -0.9465 | -0.9815 | -0.9574 | -0.9478 | +#> | U| 338.78414 | 93.15 | -0.1223 | 2.230 | 1.196 | +#> |.....................| 0.02572 | 0.7274 | 1.064 | 1.100 | +#> | X|<span style='font-weight: bold;'> 338.78414</span> | 93.15 | 0.8848 | 9.298 | 1.196 | +#> |.....................| 0.02572 | 0.7274 | 1.064 | 1.100 | +#> | F| Forward Diff. | -80.47 | 0.6431 | 1.023 | -73.28 | +#> |.....................| -19.27 | -0.2791 | -7.739 | -11.92 | +#> |<span style='font-weight: bold;'> 14</span>| 337.22825 | 1.013 | -1.002 | -0.9523 | -0.7710 | +#> |.....................| -0.9415 | -0.9814 | -0.9553 | -0.9445 | +#> | U| 337.22825 | 94.28 | -0.1225 | 2.229 | 1.206 | +#> |.....................| 0.02579 | 0.7275 | 1.066 | 1.104 | +#> | X|<span style='font-weight: bold;'> 337.22825</span> | 94.28 | 0.8847 | 9.295 | 1.206 | +#> |.....................| 0.02579 | 0.7275 | 1.066 | 1.104 | +#> | F| Forward Diff. | 82.17 | 0.7754 | 1.480 | -71.69 | +#> |.....................| -17.81 | -0.5846 | -7.635 | -11.71 | +#> |<span style='font-weight: bold;'> 15</span>| 335.66851 | 1.001 | -1.002 | -0.9527 | -0.7512 | +#> |.....................| -0.9367 | -0.9812 | -0.9531 | -0.9411 | +#> | U| 335.66851 | 93.18 | -0.1228 | 2.229 | 1.217 | +#> |.....................| 0.02585 | 0.7276 | 1.068 | 1.108 | +#> | X|<span style='font-weight: bold;'> 335.66851</span> | 93.18 | 0.8845 | 9.291 | 1.217 | +#> |.....................| 0.02585 | 0.7276 | 1.068 | 1.108 | +#> | F| Forward Diff. | -77.03 | 0.6546 | 1.055 | -69.28 | +#> |.....................| -17.76 | -0.6126 | -7.531 | -11.66 | +#> |<span style='font-weight: bold;'> 16</span>| 334.17549 | 1.012 | -1.002 | -0.9531 | -0.7314 | +#> |.....................| -0.9319 | -0.9810 | -0.9509 | -0.9376 | +#> | U| 334.17549 | 94.25 | -0.1230 | 2.229 | 1.228 | +#> |.....................| 0.02591 | 0.7278 | 1.070 | 1.111 | +#> | X|<span style='font-weight: bold;'> 334.17549</span> | 94.25 | 0.8843 | 9.287 | 1.228 | +#> |.....................| 0.02591 | 0.7278 | 1.070 | 1.111 | +#> | F| Forward Diff. | 77.34 | 0.7869 | 1.511 | -67.40 | +#> |.....................| -16.23 | -0.6338 | -7.414 | -11.45 | +#> |<span style='font-weight: bold;'> 17</span>| 332.70253 | 1.001 | -1.002 | -0.9536 | -0.7113 | +#> |.....................| -0.9273 | -0.9807 | -0.9485 | -0.9339 | +#> | U| 332.70253 | 93.20 | -0.1232 | 2.228 | 1.239 | +#> |.....................| 0.02597 | 0.7280 | 1.073 | 1.115 | +#> | X|<span style='font-weight: bold;'> 332.70253</span> | 93.20 | 0.8841 | 9.283 | 1.239 | +#> |.....................| 0.02597 | 0.7280 | 1.073 | 1.115 | +#> | F| Forward Diff. | -74.42 | 0.6680 | 1.089 | -65.07 | +#> |.....................| -16.20 | -0.6067 | -7.288 | -11.39 | +#> |<span style='font-weight: bold;'> 18</span>| 331.26057 | 1.012 | -1.003 | -0.9540 | -0.6912 | +#> |.....................| -0.9227 | -0.9804 | -0.9461 | -0.9301 | +#> | U| 331.26057 | 94.22 | -0.1235 | 2.228 | 1.250 | +#> |.....................| 0.02602 | 0.7282 | 1.076 | 1.119 | +#> | X|<span style='font-weight: bold;'> 331.26057</span> | 94.22 | 0.8838 | 9.279 | 1.250 | +#> |.....................| 0.02602 | 0.7282 | 1.076 | 1.119 | +#> | F| Forward Diff. | 71.33 | 0.7962 | 1.537 | -63.45 | +#> |.....................| -14.84 | -0.8466 | -7.169 | -11.16 | +#> |<span style='font-weight: bold;'> 19</span>| 329.86877 | 1.001 | -1.003 | -0.9546 | -0.6708 | +#> |.....................| -0.9184 | -0.9799 | -0.9435 | -0.9260 | +#> | U| 329.86877 | 93.23 | -0.1238 | 2.227 | 1.261 | +#> |.....................| 0.02608 | 0.7285 | 1.078 | 1.124 | +#> | X|<span style='font-weight: bold;'> 329.86877</span> | 93.23 | 0.8836 | 9.273 | 1.261 | +#> |.....................| 0.02608 | 0.7285 | 1.078 | 1.124 | +#> | F| Forward Diff. | -70.96 | 0.6825 | 1.126 | -60.92 | +#> |.....................| -14.66 | -0.5289 | -7.027 | -11.08 | +#> |<span style='font-weight: bold;'> 20</span>| 328.50031 | 1.012 | -1.003 | -0.9552 | -0.6504 | +#> |.....................| -0.9143 | -0.9795 | -0.9408 | -0.9217 | +#> | U| 328.50031 | 94.20 | -0.1241 | 2.227 | 1.272 | +#> |.....................| 0.02613 | 0.7288 | 1.081 | 1.128 | +#> | X|<span style='font-weight: bold;'> 328.50031</span> | 94.20 | 0.8833 | 9.268 | 1.272 | +#> |.....................| 0.02613 | 0.7288 | 1.081 | 1.128 | +#> | F| Forward Diff. | 67.86 | 0.8082 | 1.577 | -59.49 | +#> |.....................| -13.42 | -0.7986 | -6.899 | -10.84 | +#> |<span style='font-weight: bold;'> 21</span>| 327.16645 | 1.002 | -1.004 | -0.9559 | -0.6298 | +#> |.....................| -0.9105 | -0.9791 | -0.9380 | -0.9171 | +#> | U| 327.16645 | 93.27 | -0.1245 | 2.226 | 1.284 | +#> |.....................| 0.02618 | 0.7291 | 1.084 | 1.133 | +#> | X|<span style='font-weight: bold;'> 327.16645</span> | 93.27 | 0.8829 | 9.261 | 1.284 | +#> |.....................| 0.02618 | 0.7291 | 1.084 | 1.133 | +#> | F| Forward Diff. | -65.39 | 0.6978 | 1.172 | -57.48 | +#> |.....................| -13.36 | -0.7754 | -6.743 | -10.73 | +#> |<span style='font-weight: bold;'> 22</span>| 325.87373 | 1.012 | -1.004 | -0.9567 | -0.6091 | +#> |.....................| -0.9070 | -0.9785 | -0.9351 | -0.9123 | +#> | U| 325.87373 | 94.19 | -0.1249 | 2.225 | 1.295 | +#> |.....................| 0.02622 | 0.7296 | 1.087 | 1.138 | +#> | X|<span style='font-weight: bold;'> 325.87373</span> | 94.19 | 0.8826 | 9.255 | 1.295 | +#> |.....................| 0.02622 | 0.7296 | 1.087 | 1.138 | +#> | F| Forward Diff. | 64.00 | 0.8187 | 1.613 | -55.46 | +#> |.....................| -12.01 | -0.6347 | -6.615 | -10.48 | +#> |<span style='font-weight: bold;'> 23</span>| 324.62990 | 1.002 | -1.004 | -0.9576 | -0.5884 | +#> |.....................| -0.9040 | -0.9780 | -0.9320 | -0.9071 | +#> | U| 324.6299 | 93.29 | -0.1254 | 2.224 | 1.306 | +#> |.....................| 0.02626 | 0.7300 | 1.090 | 1.144 | +#> | X|<span style='font-weight: bold;'> 324.6299</span> | 93.29 | 0.8822 | 9.246 | 1.306 | +#> |.....................| 0.02626 | 0.7300 | 1.090 | 1.144 | +#> | F| Forward Diff. | -64.25 | 0.7091 | 1.205 | -53.86 | +#> |.....................| -12.06 | -0.7132 | -6.446 | -10.35 | +#> |<span style='font-weight: bold;'> 24</span>| 323.37595 | 1.011 | -1.005 | -0.9586 | -0.5676 | +#> |.....................| -0.9015 | -0.9774 | -0.9287 | -0.9014 | +#> | U| 323.37595 | 94.14 | -0.1259 | 2.223 | 1.318 | +#> |.....................| 0.02629 | 0.7304 | 1.094 | 1.150 | +#> | X|<span style='font-weight: bold;'> 323.37595</span> | 94.14 | 0.8817 | 9.236 | 1.318 | +#> |.....................| 0.02629 | 0.7304 | 1.094 | 1.150 | +#> | F| Forward Diff. | 56.04 | 0.8254 | 1.637 | -52.44 | +#> |.....................| -10.96 | -0.9420 | -6.280 | -10.07 | +#> |<span style='font-weight: bold;'> 25</span>| 322.22752 | 1.002 | -1.006 | -0.9598 | -0.5467 | +#> |.....................| -0.8995 | -0.9764 | -0.9254 | -0.8957 | +#> | U| 322.22752 | 93.30 | -0.1265 | 2.222 | 1.329 | +#> |.....................| 0.02631 | 0.7311 | 1.097 | 1.156 | +#> | X|<span style='font-weight: bold;'> 322.22752</span> | 93.30 | 0.8812 | 9.225 | 1.329 | +#> |.....................| 0.02631 | 0.7311 | 1.097 | 1.156 | +#> | F| Forward Diff. | -62.58 | 0.7198 | 1.238 | -50.46 | +#> |.....................| -10.85 | -0.6563 | -6.111 | -9.931 | +#> |<span style='font-weight: bold;'> 26</span>| 321.05050 | 1.011 | -1.006 | -0.9612 | -0.5258 | +#> |.....................| -0.8983 | -0.9755 | -0.9219 | -0.8894 | +#> | U| 321.0505 | 94.13 | -0.1272 | 2.221 | 1.341 | +#> |.....................| 0.02633 | 0.7318 | 1.101 | 1.163 | +#> | X|<span style='font-weight: bold;'> 321.0505</span> | 94.13 | 0.8805 | 9.213 | 1.341 | +#> |.....................| 0.02633 | 0.7318 | 1.101 | 1.163 | +#> | F| Forward Diff. | 53.55 | 0.8319 | 1.674 | -49.18 | +#> |.....................| -9.827 | -0.8926 | -5.944 | -9.631 | +#> |<span style='font-weight: bold;'> 27</span>| 319.96320 | 1.003 | -1.007 | -0.9629 | -0.5048 | +#> |.....................| -0.8978 | -0.9744 | -0.9184 | -0.8829 | +#> | U| 319.9632 | 93.35 | -0.1280 | 2.219 | 1.352 | +#> |.....................| 0.02633 | 0.7325 | 1.104 | 1.170 | +#> | X|<span style='font-weight: bold;'> 319.9632</span> | 93.35 | 0.8798 | 9.197 | 1.352 | +#> |.....................| 0.02633 | 0.7325 | 1.104 | 1.170 | +#> | F| Forward Diff. | -57.14 | 0.7318 | 1.284 | -47.52 | +#> |.....................| -9.778 | -0.7040 | -5.744 | -9.448 | +#> |<span style='font-weight: bold;'> 28</span>| 318.87595 | 1.011 | -1.008 | -0.9647 | -0.4840 | +#> |.....................| -0.8984 | -0.9733 | -0.9148 | -0.8761 | +#> | U| 318.87595 | 94.12 | -0.1289 | 2.217 | 1.364 | +#> |.....................| 0.02633 | 0.7334 | 1.108 | 1.177 | +#> | X|<span style='font-weight: bold;'> 318.87595</span> | 94.12 | 0.8790 | 9.180 | 1.364 | +#> |.....................| 0.02633 | 0.7334 | 1.108 | 1.177 | +#> | F| Forward Diff. | 50.84 | 0.8352 | 1.706 | -46.29 | +#> |.....................| -8.837 | -0.9158 | -5.564 | -9.134 | +#> |<span style='font-weight: bold;'> 29</span>| 317.86528 | 1.003 | -1.009 | -0.9669 | -0.4631 | +#> |.....................| -0.9000 | -0.9719 | -0.9113 | -0.8691 | +#> | U| 317.86528 | 93.39 | -0.1300 | 2.215 | 1.375 | +#> |.....................| 0.02631 | 0.7344 | 1.112 | 1.185 | +#> | X|<span style='font-weight: bold;'> 317.86528</span> | 93.39 | 0.8781 | 9.160 | 1.375 | +#> |.....................| 0.02631 | 0.7344 | 1.112 | 1.185 | +#> | F| Forward Diff. | -53.64 | 0.7337 | 1.307 | -44.73 | +#> |.....................| -8.788 | -0.7242 | -5.380 | -8.940 | +#> |<span style='font-weight: bold;'> 30</span>| 316.86653 | 1.011 | -1.010 | -0.9694 | -0.4424 | +#> |.....................| -0.9029 | -0.9703 | -0.9078 | -0.8619 | +#> | U| 316.86653 | 94.11 | -0.1312 | 2.212 | 1.386 | +#> |.....................| 0.02627 | 0.7355 | 1.115 | 1.192 | +#> | X|<span style='font-weight: bold;'> 316.86653</span> | 94.11 | 0.8771 | 9.137 | 1.386 | +#> |.....................| 0.02627 | 0.7355 | 1.115 | 1.192 | +#> | F| Forward Diff. | 47.91 | 0.8298 | 1.717 | -43.37 | +#> |.....................| -7.860 | -0.7095 | -5.221 | -8.628 | +#> |<span style='font-weight: bold;'> 31</span>| 315.94581 | 1.003 | -1.012 | -0.9723 | -0.4219 | +#> |.....................| -0.9070 | -0.9693 | -0.9044 | -0.8547 | +#> | U| 315.94581 | 93.42 | -0.1325 | 2.209 | 1.398 | +#> |.....................| 0.02622 | 0.7363 | 1.119 | 1.200 | +#> | X|<span style='font-weight: bold;'> 315.94581</span> | 93.42 | 0.8759 | 9.111 | 1.398 | +#> |.....................| 0.02622 | 0.7363 | 1.119 | 1.200 | +#> | F| Forward Diff. | -50.84 | 0.7268 | 1.307 | -41.97 | +#> |.....................| -7.840 | -0.5502 | -5.032 | -8.421 | +#> |<span style='font-weight: bold;'> 32</span>| 315.03994 | 1.011 | -1.013 | -0.9754 | -0.4018 | +#> |.....................| -0.9129 | -0.9687 | -0.9011 | -0.8473 | +#> | U| 315.03994 | 94.09 | -0.1340 | 2.206 | 1.409 | +#> |.....................| 0.02615 | 0.7367 | 1.122 | 1.208 | +#> | X|<span style='font-weight: bold;'> 315.03994</span> | 94.09 | 0.8746 | 9.082 | 1.409 | +#> |.....................| 0.02615 | 0.7367 | 1.122 | 1.208 | +#> | F| Forward Diff. | 43.50 | 0.8139 | 1.698 | -41.38 | +#> |.....................| -7.196 | -0.9249 | -4.882 | -8.108 | +#> |<span style='font-weight: bold;'> 33</span>| 314.20198 | 1.004 | -1.015 | -0.9788 | -0.3816 | +#> |.....................| -0.9197 | -0.9671 | -0.8983 | -0.8406 | +#> | U| 314.20198 | 93.47 | -0.1355 | 2.203 | 1.420 | +#> |.....................| 0.02606 | 0.7379 | 1.125 | 1.215 | +#> | X|<span style='font-weight: bold;'> 314.20198</span> | 93.47 | 0.8733 | 9.052 | 1.420 | +#> |.....................| 0.02606 | 0.7379 | 1.125 | 1.215 | +#> | F| Forward Diff. | -46.04 | 0.7133 | 1.286 | -40.35 | +#> |.....................| -7.243 | -0.8268 | -4.724 | -7.917 | +#> |<span style='font-weight: bold;'> 34</span>| 313.39087 | 1.011 | -1.016 | -0.9822 | -0.3616 | +#> |.....................| -0.9277 | -0.9641 | -0.8960 | -0.8348 | +#> | U| 313.39087 | 94.10 | -0.1371 | 2.200 | 1.431 | +#> |.....................| 0.02596 | 0.7401 | 1.128 | 1.221 | +#> | X|<span style='font-weight: bold;'> 313.39087</span> | 94.10 | 0.8719 | 9.021 | 1.431 | +#> |.....................| 0.02596 | 0.7401 | 1.128 | 1.221 | +#> | F| Forward Diff. | 42.44 | 0.7936 | 1.657 | -38.93 | +#> |.....................| -6.417 | -0.6060 | -4.631 | -7.687 | +#> |<span style='font-weight: bold;'> 35</span>| 312.65204 | 1.004 | -1.018 | -0.9857 | -0.3421 | +#> |.....................| -0.9371 | -0.9626 | -0.8936 | -0.8290 | +#> | U| 312.65204 | 93.49 | -0.1387 | 2.196 | 1.441 | +#> |.....................| 0.02584 | 0.7411 | 1.130 | 1.228 | +#> | X|<span style='font-weight: bold;'> 312.65204</span> | 93.49 | 0.8705 | 8.989 | 1.441 | +#> |.....................| 0.02584 | 0.7411 | 1.130 | 1.228 | +#> | F| Forward Diff. | -46.74 | 0.6875 | 1.233 | -38.07 | +#> |.....................| -6.520 | -0.5247 | -4.495 | -7.518 | +#> |<span style='font-weight: bold;'> 36</span>| 311.92333 | 1.010 | -1.020 | -0.9894 | -0.3235 | +#> |.....................| -0.9483 | -0.9627 | -0.8910 | -0.8230 | +#> | U| 311.92333 | 94.07 | -0.1404 | 2.192 | 1.452 | +#> |.....................| 0.02570 | 0.7411 | 1.133 | 1.234 | +#> | X|<span style='font-weight: bold;'> 311.92333</span> | 94.07 | 0.8690 | 8.957 | 1.452 | +#> |.....................| 0.02570 | 0.7411 | 1.133 | 1.234 | +#> | F| Forward Diff. | 35.63 | 0.7624 | 1.583 | -37.23 | +#> |.....................| -5.893 | -0.6222 | -4.382 | -7.287 | +#> |<span style='font-weight: bold;'> 37</span>| 311.27355 | 1.004 | -1.021 | -0.9929 | -0.3046 | +#> |.....................| -0.9595 | -0.9623 | -0.8888 | -0.8177 | +#> | U| 311.27355 | 93.51 | -0.1420 | 2.189 | 1.462 | +#> |.....................| 0.02556 | 0.7413 | 1.135 | 1.240 | +#> | X|<span style='font-weight: bold;'> 311.27355</span> | 93.51 | 0.8676 | 8.925 | 1.462 | +#> |.....................| 0.02556 | 0.7413 | 1.135 | 1.240 | +#> | F| Forward Diff. | -45.98 | 0.6631 | 1.170 | -36.31 | +#> |.....................| -5.950 | -0.4376 | -4.255 | -7.133 | +#> |<span style='font-weight: bold;'> 38</span>| 310.62439 | 1.010 | -1.023 | -0.9963 | -0.2868 | +#> |.....................| -0.9728 | -0.9625 | -0.8869 | -0.8128 | +#> | U| 310.62439 | 94.07 | -0.1437 | 2.185 | 1.472 | +#> |.....................| 0.02539 | 0.7412 | 1.137 | 1.245 | +#> | X|<span style='font-weight: bold;'> 310.62439</span> | 94.07 | 0.8661 | 8.895 | 1.472 | +#> |.....................| 0.02539 | 0.7412 | 1.137 | 1.245 | +#> | F| Forward Diff. | 33.19 | 0.7369 | 1.513 | -35.63 | +#> |.....................| -5.399 | -0.5527 | -4.174 | -6.950 | +#> |<span style='font-weight: bold;'> 39</span>| 310.04420 | 1.005 | -1.024 | -0.9995 | -0.2687 | +#> |.....................| -0.9859 | -0.9628 | -0.8850 | -0.8081 | +#> | U| 310.0442 | 93.55 | -0.1453 | 2.182 | 1.482 | +#> |.....................| 0.02523 | 0.7410 | 1.139 | 1.250 | +#> | X|<span style='font-weight: bold;'> 310.0442</span> | 93.55 | 0.8648 | 8.866 | 1.482 | +#> |.....................| 0.02523 | 0.7410 | 1.139 | 1.250 | +#> | F| Forward Diff. | -43.63 | 0.6390 | 1.117 | -34.92 | +#> |.....................| -5.491 | -0.4082 | -4.072 | -6.814 | +#> |<span style='font-weight: bold;'> 40</span>| 309.46411 | 1.010 | -1.026 | -1.003 | -0.2518 | +#> |.....................| -1.001 | -0.9632 | -0.8835 | -0.8040 | +#> | U| 309.46411 | 94.07 | -0.1468 | 2.179 | 1.491 | +#> |.....................| 0.02504 | 0.7407 | 1.141 | 1.254 | +#> | X|<span style='font-weight: bold;'> 309.46411</span> | 94.07 | 0.8634 | 8.839 | 1.491 | +#> |.....................| 0.02504 | 0.7407 | 1.141 | 1.254 | +#> | F| Forward Diff. | 30.94 | 0.7075 | 1.451 | -34.14 | +#> |.....................| -4.970 | -0.4915 | -4.021 | -6.668 | +#> |<span style='font-weight: bold;'> 41</span>| 308.94397 | 1.005 | -1.027 | -1.005 | -0.2344 | +#> |.....................| -1.015 | -0.9639 | -0.8817 | -0.7999 | +#> | U| 308.94397 | 93.57 | -0.1483 | 2.176 | 1.500 | +#> |.....................| 0.02486 | 0.7402 | 1.143 | 1.259 | +#> | X|<span style='font-weight: bold;'> 308.94397</span> | 93.57 | 0.8622 | 8.814 | 1.500 | +#> |.....................| 0.02486 | 0.7402 | 1.143 | 1.259 | +#> | F| Forward Diff. | -43.40 | 0.6150 | 1.062 | -33.15 | +#> |.....................| -4.981 | -0.1275 | -3.914 | -6.542 | +#> |<span style='font-weight: bold;'> 42</span>| 308.42636 | 1.010 | -1.029 | -1.008 | -0.2188 | +#> |.....................| -1.031 | -0.9663 | -0.8797 | -0.7956 | +#> | U| 308.42636 | 94.07 | -0.1498 | 2.174 | 1.509 | +#> |.....................| 0.02466 | 0.7384 | 1.145 | 1.264 | +#> | X|<span style='font-weight: bold;'> 308.42636</span> | 94.07 | 0.8609 | 8.789 | 1.509 | +#> |.....................| 0.02466 | 0.7384 | 1.145 | 1.264 | +#> | F| Forward Diff. | 28.94 | 0.6832 | 1.395 | -33.36 | +#> |.....................| -4.720 | -0.6585 | -3.841 | -6.387 | +#> |<span style='font-weight: bold;'> 43</span>| 307.94294 | 1.006 | -1.030 | -1.011 | -0.2019 | +#> |.....................| -1.047 | -0.9672 | -0.8783 | -0.7922 | +#> | U| 307.94294 | 93.62 | -0.1511 | 2.171 | 1.518 | +#> |.....................| 0.02447 | 0.7378 | 1.146 | 1.267 | +#> | X|<span style='font-weight: bold;'> 307.94294</span> | 93.62 | 0.8597 | 8.766 | 1.518 | +#> |.....................| 0.02447 | 0.7378 | 1.146 | 1.267 | +#> | F| Forward Diff. | -38.44 | 0.5985 | 1.037 | -32.41 | +#> |.....................| -4.734 | -0.3663 | -3.762 | -6.284 | +#> |<span style='font-weight: bold;'> 44</span>| 307.46797 | 1.011 | -1.032 | -1.013 | -0.1861 | +#> |.....................| -1.063 | -0.9666 | -0.8774 | -0.7896 | +#> | U| 307.46797 | 94.11 | -0.1524 | 2.169 | 1.527 | +#> |.....................| 0.02426 | 0.7383 | 1.147 | 1.270 | +#> | X|<span style='font-weight: bold;'> 307.46797</span> | 94.11 | 0.8586 | 8.746 | 1.527 | +#> |.....................| 0.02426 | 0.7383 | 1.147 | 1.270 | +#> | F| Forward Diff. | 31.70 | 0.6652 | 1.367 | -32.07 | +#> |.....................| -4.364 | -0.4841 | -3.739 | -6.200 | +#> |<span style='font-weight: bold;'> 45</span>| 307.02197 | 1.006 | -1.033 | -1.016 | -0.1702 | +#> |.....................| -1.080 | -0.9671 | -0.8762 | -0.7866 | +#> | U| 307.02197 | 93.66 | -0.1537 | 2.166 | 1.536 | +#> |.....................| 0.02405 | 0.7379 | 1.149 | 1.273 | +#> | X|<span style='font-weight: bold;'> 307.02197</span> | 93.66 | 0.8575 | 8.725 | 1.536 | +#> |.....................| 0.02405 | 0.7379 | 1.149 | 1.273 | +#> | F| Forward Diff. | -34.81 | 0.5817 | 1.015 | -31.25 | +#> |.....................| -4.413 | -0.2597 | -3.670 | -6.117 | +#> |<span style='font-weight: bold;'> 46</span>| 306.58875 | 1.011 | -1.034 | -1.018 | -0.1551 | +#> |.....................| -1.097 | -0.9684 | -0.8747 | -0.7833 | +#> | U| 306.58875 | 94.13 | -0.1549 | 2.164 | 1.544 | +#> |.....................| 0.02384 | 0.7369 | 1.150 | 1.277 | +#> | X|<span style='font-weight: bold;'> 306.58875</span> | 94.13 | 0.8565 | 8.705 | 1.544 | +#> |.....................| 0.02384 | 0.7369 | 1.150 | 1.277 | +#> | F| Forward Diff. | 31.47 | 0.6484 | 1.332 | -31.08 | +#> |.....................| -4.101 | -0.4354 | -3.617 | -5.999 | +#> |<span style='font-weight: bold;'> 47</span>| 306.17343 | 1.006 | -1.035 | -1.020 | -0.1399 | +#> |.....................| -1.114 | -0.9699 | -0.8732 | -0.7802 | +#> | U| 306.17343 | 93.70 | -0.1561 | 2.162 | 1.552 | +#> |.....................| 0.02362 | 0.7358 | 1.152 | 1.280 | +#> | X|<span style='font-weight: bold;'> 306.17343</span> | 93.70 | 0.8554 | 8.686 | 1.552 | +#> |.....................| 0.02362 | 0.7358 | 1.152 | 1.280 | +#> | F| Forward Diff. | -31.81 | 0.5683 | 0.9956 | -30.69 | +#> |.....................| -4.225 | -0.4059 | -3.540 | -5.903 | +#> |<span style='font-weight: bold;'> 48</span>| 305.76609 | 1.011 | -1.036 | -1.022 | -0.1248 | +#> |.....................| -1.132 | -0.9702 | -0.8722 | -0.7778 | +#> | U| 305.76609 | 94.14 | -0.1573 | 2.160 | 1.560 | +#> |.....................| 0.02340 | 0.7356 | 1.153 | 1.283 | +#> | X|<span style='font-weight: bold;'> 305.76609</span> | 94.14 | 0.8545 | 8.668 | 1.560 | +#> |.....................| 0.02340 | 0.7356 | 1.153 | 1.283 | +#> | F| Forward Diff. | 30.78 | 0.6301 | 1.297 | -30.24 | +#> |.....................| -3.891 | -0.4278 | -3.502 | -5.825 | +#> |<span style='font-weight: bold;'> 49</span>| 305.37620 | 1.007 | -1.037 | -1.024 | -0.1098 | +#> |.....................| -1.149 | -0.9705 | -0.8714 | -0.7755 | +#> | U| 305.3762 | 93.72 | -0.1584 | 2.158 | 1.569 | +#> |.....................| 0.02318 | 0.7354 | 1.154 | 1.285 | +#> | X|<span style='font-weight: bold;'> 305.3762</span> | 93.72 | 0.8535 | 8.651 | 1.569 | +#> |.....................| 0.02318 | 0.7354 | 1.154 | 1.285 | +#> | F| Forward Diff. | -32.45 | 0.5512 | 0.9611 | -29.28 | +#> |.....................| -3.904 | -0.09870 | -3.459 | -5.767 | +#> |<span style='font-weight: bold;'> 50</span>| 304.99974 | 1.011 | -1.039 | -1.026 | -0.09561 | +#> |.....................| -1.167 | -0.9731 | -0.8699 | -0.7723 | +#> | U| 304.99974 | 94.15 | -0.1595 | 2.156 | 1.576 | +#> |.....................| 0.02295 | 0.7335 | 1.155 | 1.288 | +#> | X|<span style='font-weight: bold;'> 304.99974</span> | 94.15 | 0.8526 | 8.633 | 1.576 | +#> |.....................| 0.02295 | 0.7335 | 1.155 | 1.288 | +#> | F| Forward Diff. | 30.20 | 0.6130 | 1.265 | -28.57 | +#> |.....................| -3.511 | -0.04200 | -3.403 | -5.652 | +#> |<span style='font-weight: bold;'> 51</span>| 304.64794 | 1.007 | -1.040 | -1.028 | -0.08217 | +#> |.....................| -1.185 | -0.9783 | -0.8678 | -0.7682 | +#> | U| 304.64794 | 93.75 | -0.1607 | 2.153 | 1.584 | +#> |.....................| 0.02273 | 0.7297 | 1.157 | 1.293 | +#> | X|<span style='font-weight: bold;'> 304.64794</span> | 93.75 | 0.8516 | 8.614 | 1.584 | +#> |.....................| 0.02273 | 0.7297 | 1.157 | 1.293 | +#> | F| Forward Diff. | -30.08 | 0.5385 | 0.9408 | -28.96 | +#> |.....................| -3.779 | -0.3908 | -3.281 | -5.515 | +#> |<span style='font-weight: bold;'> 52</span>| 304.28931 | 1.011 | -1.041 | -1.030 | -0.06828 | +#> |.....................| -1.203 | -0.9811 | -0.8668 | -0.7655 | +#> | U| 304.28931 | 94.14 | -0.1618 | 2.151 | 1.591 | +#> |.....................| 0.02250 | 0.7277 | 1.158 | 1.296 | +#> | X|<span style='font-weight: bold;'> 304.28931</span> | 94.14 | 0.8506 | 8.597 | 1.591 | +#> |.....................| 0.02250 | 0.7277 | 1.158 | 1.296 | +#> |<span style='font-weight: bold;'> 53</span>| 304.03244 | 1.011 | -1.042 | -1.033 | -0.05709 | +#> |.....................| -1.225 | -0.9843 | -0.8662 | -0.7633 | +#> | U| 304.03244 | 94.13 | -0.1630 | 2.149 | 1.597 | +#> |.....................| 0.02223 | 0.7253 | 1.159 | 1.298 | +#> | X|<span style='font-weight: bold;'> 304.03244</span> | 94.13 | 0.8496 | 8.578 | 1.597 | +#> |.....................| 0.02223 | 0.7253 | 1.159 | 1.298 | +#> |<span style='font-weight: bold;'> 54</span>| 302.98899 | 1.011 | -1.047 | -1.041 | -0.01055 | +#> |.....................| -1.314 | -0.9977 | -0.8638 | -0.7544 | +#> | U| 302.98899 | 94.10 | -0.1678 | 2.140 | 1.623 | +#> |.....................| 0.02111 | 0.7156 | 1.161 | 1.308 | +#> | X|<span style='font-weight: bold;'> 302.98899</span> | 94.10 | 0.8455 | 8.503 | 1.623 | +#> |.....................| 0.02111 | 0.7156 | 1.161 | 1.308 | +#> |<span style='font-weight: bold;'> 55</span>| 298.89653 | 1.010 | -1.068 | -1.080 | 0.1944 | +#> |.....................| -1.708 | -1.057 | -0.8531 | -0.7150 | +#> | U| 298.89653 | 93.99 | -0.1892 | 2.101 | 1.735 | +#> |.....................| 0.01618 | 0.6726 | 1.173 | 1.350 | +#> | X|<span style='font-weight: bold;'> 298.89653</span> | 93.99 | 0.8276 | 8.177 | 1.735 | +#> |.....................| 0.01618 | 0.6726 | 1.173 | 1.350 | +#> |<span style='font-weight: bold;'> 56</span>| 292.24425 | 1.012 | -1.205 | -1.331 | 1.218 | +#> |.....................| -2.997 | -1.313 | -0.8095 | -0.4981 | +#> | U| 292.24425 | 94.21 | -0.3257 | 1.851 | 2.296 | +#> |.....................| 5.960e-07 | 0.4863 | 1.218 | 1.582 | +#> | X|<span style='font-weight: bold;'> 292.24425</span> | 94.21 | 0.7221 | 6.365 | 2.296 | +#> |.....................| 5.960e-07 | 0.4863 | 1.218 | 1.582 | +#> | F| Forward Diff. | -17.20 | -1.896 | -10.23 | 0.3663 | +#> |.....................| 0.002021 | -17.85 | 0.1528 | 5.292 | +#> |<span style='font-weight: bold;'> 57</span>| 309.71599 | 0.9897 | -1.187 | -0.4357 | 2.442 | +#> |.....................| -2.997 | 0.5394 | -0.6812 | -0.7129 | +#> | U| 309.71599 | 92.14 | -0.3076 | 2.746 | 2.966 | +#> |.....................| 5.960e-07 | 1.833 | 1.352 | 1.352 | +#> | X|<span style='font-weight: bold;'> 309.71599</span> | 92.14 | 0.7352 | 15.58 | 2.966 | +#> |.....................| 5.960e-07 | 1.833 | 1.352 | 1.352 | +#> |<span style='font-weight: bold;'> 58</span>| 292.01474 | 1.005 | -1.198 | -1.013 | 1.651 | +#> |.....................| -2.997 | -0.6561 | -0.7641 | -0.5745 | +#> | U| 292.01474 | 93.60 | -0.3191 | 2.168 | 2.533 | +#> |.....................| 5.960e-07 | 0.9640 | 1.266 | 1.501 | +#> | X|<span style='font-weight: bold;'> 292.01474</span> | 93.60 | 0.7268 | 8.745 | 2.533 | +#> |.....................| 5.960e-07 | 0.9640 | 1.266 | 1.501 | +#> | F| Forward Diff. | -172.4 | -2.986 | 3.411 | 4.977 | +#> |.....................| 0.05585 | 3.841 | 3.028 | 0.3322 | +#> |<span style='font-weight: bold;'> 59</span>| 292.30890 | 1.013 | -0.8632 | -1.158 | 1.672 | +#> |.....................| -2.997 | -0.5770 | -0.9665 | -0.6082 | +#> | U| 292.3089 | 94.28 | 0.01586 | 2.024 | 2.544 | +#> |.....................| 5.960e-07 | 1.022 | 1.054 | 1.464 | +#> | X|<span style='font-weight: bold;'> 292.3089</span> | 94.28 | 1.016 | 7.565 | 2.544 | +#> |.....................| 5.960e-07 | 1.022 | 1.054 | 1.464 | +#> |<span style='font-weight: bold;'> 60</span>| 291.20170 | 1.015 | -1.046 | -1.079 | 1.660 | +#> |.....................| -2.997 | -0.6203 | -0.8561 | -0.5898 | +#> | U| 291.2017 | 94.51 | -0.1669 | 2.103 | 2.538 | +#> |.....................| 5.960e-07 | 0.9900 | 1.170 | 1.484 | +#> | X|<span style='font-weight: bold;'> 291.2017</span> | 94.51 | 0.8462 | 8.187 | 2.538 | +#> |.....................| 5.960e-07 | 0.9900 | 1.170 | 1.484 | +#> | F| Forward Diff. | 39.51 | 0.9033 | 2.112 | 5.106 | +#> |.....................| 0.03418 | 2.863 | -2.696 | -0.7695 | +#> |<span style='font-weight: bold;'> 61</span>| 291.43833 | 1.017 | -1.033 | -1.136 | 1.600 | +#> |.....................| -2.997 | -0.6066 | -0.6851 | -0.5537 | +#> | U| 291.43833 | 94.73 | -0.1542 | 2.046 | 2.505 | +#> |.....................| 5.960e-07 | 1.000 | 1.348 | 1.523 | +#> | X|<span style='font-weight: bold;'> 291.43833</span> | 94.73 | 0.8571 | 7.739 | 2.505 | +#> |.....................| 5.960e-07 | 1.000 | 1.348 | 1.523 | +#> |<span style='font-weight: bold;'> 62</span>| 290.99248 | 1.014 | -1.041 | -1.101 | 1.637 | +#> |.....................| -2.997 | -0.6152 | -0.7907 | -0.5760 | +#> | U| 290.99248 | 94.43 | -0.1621 | 2.081 | 2.525 | +#> |.....................| 5.960e-07 | 0.9938 | 1.238 | 1.499 | +#> | X|<span style='font-weight: bold;'> 290.99248</span> | 94.43 | 0.8503 | 8.012 | 2.525 | +#> |.....................| 5.960e-07 | 0.9938 | 1.238 | 1.499 | +#> | F| Forward Diff. | 14.98 | 1.278 | 1.101 | 4.858 | +#> |.....................| 0.03639 | 3.021 | 0.9673 | -0.2780 | +#> |<span style='font-weight: bold;'> 63</span>| 291.02454 | 1.009 | -1.102 | -1.088 | 1.608 | +#> |.....................| -2.997 | -0.6330 | -0.7900 | -0.5542 | +#> | U| 291.02454 | 93.95 | -0.2228 | 2.094 | 2.510 | +#> |.....................| 5.960e-07 | 0.9808 | 1.239 | 1.522 | +#> | X|<span style='font-weight: bold;'> 291.02454</span> | 93.95 | 0.8003 | 8.118 | 2.510 | +#> |.....................| 5.960e-07 | 0.9808 | 1.239 | 1.522 | +#> |<span style='font-weight: bold;'> 64</span>| 291.12722 | 1.009 | -1.068 | -1.095 | 1.623 | +#> |.....................| -2.997 | -0.6237 | -0.7906 | -0.5663 | +#> | U| 291.12722 | 93.94 | -0.1892 | 2.087 | 2.518 | +#> |.....................| 5.960e-07 | 0.9876 | 1.238 | 1.509 | +#> | X|<span style='font-weight: bold;'> 291.12722</span> | 93.94 | 0.8276 | 8.057 | 2.518 | +#> |.....................| 5.960e-07 | 0.9876 | 1.238 | 1.509 | +#> |<span style='font-weight: bold;'> 65</span>| 291.20836 | 1.009 | -1.048 | -1.100 | 1.633 | +#> |.....................| -2.997 | -0.6180 | -0.7910 | -0.5738 | +#> | U| 291.20836 | 93.93 | -0.1686 | 2.082 | 2.523 | +#> |.....................| 5.960e-07 | 0.9918 | 1.238 | 1.501 | +#> | X|<span style='font-weight: bold;'> 291.20836</span> | 93.93 | 0.8449 | 8.020 | 2.523 | +#> |.....................| 5.960e-07 | 0.9918 | 1.238 | 1.501 | +#> |<span style='font-weight: bold;'> 66</span>| 290.99661 | 1.013 | -1.041 | -1.101 | 1.637 | +#> |.....................| -2.997 | -0.6156 | -0.7909 | -0.5760 | +#> | U| 290.99661 | 94.27 | -0.1623 | 2.081 | 2.525 | +#> |.....................| 5.960e-07 | 0.9935 | 1.238 | 1.499 | +#> | X|<span style='font-weight: bold;'> 290.99661</span> | 94.27 | 0.8502 | 8.011 | 2.525 | +#> |.....................| 5.960e-07 | 0.9935 | 1.238 | 1.499 | +#> |<span style='font-weight: bold;'> 67</span>| 290.98636 | 1.014 | -1.041 | -1.101 | 1.637 | +#> |.....................| -2.997 | -0.6154 | -0.7908 | -0.5760 | +#> | U| 290.98636 | 94.36 | -0.1622 | 2.081 | 2.525 | +#> |.....................| 5.960e-07 | 0.9936 | 1.238 | 1.499 | +#> | X|<span style='font-weight: bold;'> 290.98636</span> | 94.36 | 0.8503 | 8.012 | 2.525 | +#> |.....................| 5.960e-07 | 0.9936 | 1.238 | 1.499 | +#> | F| Forward Diff. | -1.956 | 1.256 | 0.9523 | 4.835 | +#> |.....................| 0.03649 | 3.031 | 0.9657 | -0.2695 | +#> |<span style='font-weight: bold;'> 68</span>| 290.98211 | 1.014 | -1.041 | -1.101 | 1.636 | +#> |.....................| -2.997 | -0.6157 | -0.7909 | -0.5760 | +#> | U| 290.98211 | 94.38 | -0.1623 | 2.081 | 2.525 | +#> |.....................| 5.960e-07 | 0.9934 | 1.238 | 1.499 | +#> | X|<span style='font-weight: bold;'> 290.98211</span> | 94.38 | 0.8502 | 8.011 | 2.525 | +#> |.....................| 5.960e-07 | 0.9934 | 1.238 | 1.499 | +#> |<span style='font-weight: bold;'> 69</span>| 290.97746 | 1.014 | -1.042 | -1.101 | 1.635 | +#> |.....................| -2.997 | -0.6167 | -0.7912 | -0.5759 | +#> | U| 290.97746 | 94.44 | -0.1627 | 2.081 | 2.524 | +#> |.....................| 5.960e-07 | 0.9927 | 1.237 | 1.499 | +#> | X|<span style='font-weight: bold;'> 290.97746</span> | 94.44 | 0.8498 | 8.009 | 2.524 | +#> |.....................| 5.960e-07 | 0.9927 | 1.237 | 1.499 | +#> | F| Forward Diff. | 17.70 | 1.268 | 1.108 | 4.855 | +#> |.....................| 0.04257 | 3.066 | 0.9427 | -0.2771 | +#> |<span style='font-weight: bold;'> 70</span>| 290.96180 | 1.014 | -1.044 | -1.101 | 1.634 | +#> |.....................| -2.997 | -0.6175 | -0.7910 | -0.5752 | +#> | U| 290.9618 | 94.36 | -0.1647 | 2.081 | 2.523 | +#> |.....................| 5.960e-07 | 0.9921 | 1.238 | 1.500 | +#> | X|<span style='font-weight: bold;'> 290.9618</span> | 94.36 | 0.8481 | 8.013 | 2.523 | +#> |.....................| 5.960e-07 | 0.9921 | 1.238 | 1.500 | +#> | F| Forward Diff. | -1.598 | 1.197 | 0.9704 | 4.824 | +#> |.....................| 0.03731 | 2.941 | 0.9551 | -0.2334 | +#> |<span style='font-weight: bold;'> 71</span>| 290.95083 | 1.014 | -1.044 | -1.101 | 1.632 | +#> |.....................| -2.997 | -0.6188 | -0.7915 | -0.5751 | +#> | U| 290.95083 | 94.43 | -0.1653 | 2.081 | 2.522 | +#> |.....................| 5.960e-07 | 0.9912 | 1.237 | 1.500 | +#> | X|<span style='font-weight: bold;'> 290.95083</span> | 94.43 | 0.8477 | 8.010 | 2.522 | +#> |.....................| 5.960e-07 | 0.9912 | 1.237 | 1.500 | +#> | F| Forward Diff. | 14.81 | 1.204 | 1.097 | 4.820 | +#> |.....................| 0.03908 | 3.014 | 0.9116 | -0.2462 | +#> |<span style='font-weight: bold;'> 72</span>| 290.93714 | 1.014 | -1.046 | -1.101 | 1.630 | +#> |.....................| -2.997 | -0.6196 | -0.7913 | -0.5744 | +#> | U| 290.93714 | 94.36 | -0.1673 | 2.081 | 2.522 | +#> |.....................| 5.960e-07 | 0.9906 | 1.237 | 1.501 | +#> | X|<span style='font-weight: bold;'> 290.93714</span> | 94.36 | 0.8459 | 8.014 | 2.522 | +#> |.....................| 5.960e-07 | 0.9906 | 1.237 | 1.501 | +#> | F| Forward Diff. | -1.943 | 1.135 | 0.9791 | 4.793 | +#> |.....................| 0.03360 | 3.051 | 0.9080 | -0.2200 | +#> |<span style='font-weight: bold;'> 73</span>| 290.92845 | 1.014 | -1.047 | -1.101 | 1.628 | +#> |.....................| -2.997 | -0.6209 | -0.7917 | -0.5743 | +#> | U| 290.92845 | 94.44 | -0.1678 | 2.081 | 2.521 | +#> |.....................| 5.960e-07 | 0.9896 | 1.237 | 1.501 | +#> | X|<span style='font-weight: bold;'> 290.92845</span> | 94.44 | 0.8455 | 8.011 | 2.521 | +#> |.....................| 5.960e-07 | 0.9896 | 1.237 | 1.501 | +#> | F| Forward Diff. | 17.70 | 1.147 | 1.134 | 4.752 | +#> |.....................| 0.02729 | 3.018 | 0.8867 | -0.2229 | +#> |<span style='font-weight: bold;'> 74</span>| 290.91300 | 1.014 | -1.049 | -1.100 | 1.627 | +#> |.....................| -2.997 | -0.6219 | -0.7915 | -0.5737 | +#> | U| 290.913 | 94.36 | -0.1698 | 2.081 | 2.520 | +#> |.....................| 5.960e-07 | 0.9889 | 1.237 | 1.501 | +#> | X|<span style='font-weight: bold;'> 290.913</span> | 94.36 | 0.8439 | 8.016 | 2.520 | +#> |.....................| 5.960e-07 | 0.9889 | 1.237 | 1.501 | +#> | F| Forward Diff. | -1.940 | 1.078 | 0.9981 | 4.722 | +#> |.....................| 0.04064 | 3.105 | 0.9143 | -0.1849 | +#> |<span style='font-weight: bold;'> 75</span>| 290.90444 | 1.014 | -1.049 | -1.101 | 1.625 | +#> |.....................| -2.997 | -0.6232 | -0.7919 | -0.5736 | +#> | U| 290.90444 | 94.44 | -0.1702 | 2.081 | 2.519 | +#> |.....................| 5.960e-07 | 0.9879 | 1.237 | 1.501 | +#> | X|<span style='font-weight: bold;'> 290.90444</span> | 94.44 | 0.8435 | 8.013 | 2.519 | +#> |.....................| 5.960e-07 | 0.9879 | 1.237 | 1.501 | +#> | F| Forward Diff. | 17.76 | 1.091 | 1.153 | 4.713 | +#> |.....................| 0.03198 | 2.950 | 0.8627 | -0.2001 | +#> |<span style='font-weight: bold;'> 76</span>| 290.88905 | 1.014 | -1.051 | -1.100 | 1.624 | +#> |.....................| -2.997 | -0.6243 | -0.7916 | -0.5732 | +#> | U| 290.88905 | 94.36 | -0.1722 | 2.082 | 2.518 | +#> |.....................| 5.960e-07 | 0.9872 | 1.237 | 1.502 | +#> | X|<span style='font-weight: bold;'> 290.88905</span> | 94.36 | 0.8418 | 8.019 | 2.518 | +#> |.....................| 5.960e-07 | 0.9872 | 1.237 | 1.502 | +#> | F| Forward Diff. | -2.112 | 1.022 | 1.016 | 4.749 | +#> |.....................| 0.03990 | 3.117 | 0.8810 | -0.1779 | +#> |<span style='font-weight: bold;'> 77</span>| 290.87937 | 1.014 | -1.052 | -1.100 | 1.622 | +#> |.....................| -2.997 | -0.6257 | -0.7918 | -0.5730 | +#> | U| 290.87937 | 94.43 | -0.1731 | 2.082 | 2.517 | +#> |.....................| 5.960e-07 | 0.9861 | 1.237 | 1.502 | +#> | X|<span style='font-weight: bold;'> 290.87937</span> | 94.43 | 0.8411 | 8.018 | 2.517 | +#> |.....................| 5.960e-07 | 0.9861 | 1.237 | 1.502 | +#> | F| Forward Diff. | 15.72 | 1.022 | 1.168 | 4.728 | +#> |.....................| 0.04036 | 3.118 | 0.8621 | -0.1806 | +#> |<span style='font-weight: bold;'> 78</span>| 290.86528 | 1.014 | -1.054 | -1.099 | 1.621 | +#> |.....................| -2.997 | -0.6269 | -0.7915 | -0.5727 | +#> | U| 290.86528 | 94.36 | -0.1749 | 2.083 | 2.516 | +#> |.....................| 5.960e-07 | 0.9853 | 1.237 | 1.502 | +#> | X|<span style='font-weight: bold;'> 290.86528</span> | 94.36 | 0.8396 | 8.025 | 2.516 | +#> |.....................| 5.960e-07 | 0.9853 | 1.237 | 1.502 | +#> | F| Forward Diff. | -2.089 | 0.9583 | 1.055 | 4.711 | +#> |.....................| 0.04161 | 3.089 | 0.8790 | -0.1555 | +#> |<span style='font-weight: bold;'> 79</span>| 290.85625 | 1.014 | -1.055 | -1.099 | 1.619 | +#> |.....................| -2.997 | -0.6283 | -0.7918 | -0.5726 | +#> | U| 290.85625 | 94.44 | -0.1756 | 2.082 | 2.515 | +#> |.....................| 5.960e-07 | 0.9842 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.85625</span> | 94.44 | 0.8389 | 8.023 | 2.515 | +#> |.....................| 5.960e-07 | 0.9842 | 1.237 | 1.503 | +#> | F| Forward Diff. | 16.77 | 0.9641 | 1.212 | 4.706 | +#> |.....................| 0.04215 | 3.138 | 0.8554 | -0.1643 | +#> |<span style='font-weight: bold;'> 80</span>| 290.84140 | 1.014 | -1.056 | -1.099 | 1.618 | +#> |.....................| -2.997 | -0.6296 | -0.7915 | -0.5724 | +#> | U| 290.8414 | 94.36 | -0.1774 | 2.083 | 2.515 | +#> |.....................| 5.960e-07 | 0.9833 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.8414</span> | 94.36 | 0.8375 | 8.030 | 2.515 | +#> |.....................| 5.960e-07 | 0.9833 | 1.237 | 1.503 | +#> | F| Forward Diff. | -1.641 | 0.9006 | 1.093 | 4.694 | +#> |.....................| 0.04205 | 3.147 | 0.8775 | -0.1452 | +#> |<span style='font-weight: bold;'> 81</span>| 290.83107 | 1.014 | -1.057 | -1.099 | 1.616 | +#> |.....................| -2.997 | -0.6310 | -0.7919 | -0.5723 | +#> | U| 290.83107 | 94.43 | -0.1778 | 2.083 | 2.514 | +#> |.....................| 5.960e-07 | 0.9823 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.83107</span> | 94.43 | 0.8371 | 8.026 | 2.514 | +#> |.....................| 5.960e-07 | 0.9823 | 1.237 | 1.503 | +#> | F| Forward Diff. | 15.22 | 0.9116 | 1.221 | 4.655 | +#> |.....................| 0.04015 | 3.140 | 0.8393 | -0.1501 | +#> |<span style='font-weight: bold;'> 82</span>| 290.81725 | 1.014 | -1.059 | -1.098 | 1.615 | +#> |.....................| -2.997 | -0.6323 | -0.7916 | -0.5722 | +#> | U| 290.81725 | 94.36 | -0.1795 | 2.084 | 2.513 | +#> |.....................| 5.960e-07 | 0.9813 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.81725</span> | 94.36 | 0.8357 | 8.034 | 2.513 | +#> |.....................| 5.960e-07 | 0.9813 | 1.237 | 1.503 | +#> | F| Forward Diff. | -2.105 | 0.8517 | 1.114 | 4.660 | +#> |.....................| 0.03878 | 3.162 | 0.8666 | -0.1313 | +#> |<span style='font-weight: bold;'> 83</span>| 290.80795 | 1.014 | -1.059 | -1.098 | 1.613 | +#> |.....................| -2.997 | -0.6339 | -0.7918 | -0.5722 | +#> | U| 290.80795 | 94.43 | -0.1802 | 2.084 | 2.512 | +#> |.....................| 5.960e-07 | 0.9802 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.80795</span> | 94.43 | 0.8351 | 8.033 | 2.512 | +#> |.....................| 5.960e-07 | 0.9802 | 1.237 | 1.503 | +#> | F| Forward Diff. | 16.11 | 0.8564 | 1.267 | 4.653 | +#> |.....................| 0.04303 | 3.178 | 0.8469 | -0.1413 | +#> |<span style='font-weight: bold;'> 84</span>| 290.79348 | 1.014 | -1.061 | -1.097 | 1.611 | +#> |.....................| -2.997 | -0.6353 | -0.7914 | -0.5722 | +#> | U| 290.79348 | 94.36 | -0.1817 | 2.084 | 2.511 | +#> |.....................| 5.960e-07 | 0.9792 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.79348</span> | 94.36 | 0.8338 | 8.041 | 2.511 | +#> |.....................| 5.960e-07 | 0.9792 | 1.237 | 1.503 | +#> | F| Forward Diff. | -1.840 | 0.7976 | 1.155 | 4.587 | +#> |.....................| 0.02723 | 3.115 | 0.8603 | -0.1275 | +#> |<span style='font-weight: bold;'> 85</span>| 290.78474 | 1.014 | -1.061 | -1.098 | 1.609 | +#> |.....................| -2.997 | -0.6367 | -0.7918 | -0.5721 | +#> | U| 290.78474 | 94.44 | -0.1821 | 2.084 | 2.510 | +#> |.....................| 5.960e-07 | 0.9781 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.78474</span> | 94.44 | 0.8335 | 8.036 | 2.510 | +#> |.....................| 5.960e-07 | 0.9781 | 1.237 | 1.503 | +#> | F| Forward Diff. | 17.19 | 0.8130 | 1.300 | 4.618 | +#> |.....................| 0.03919 | 3.190 | 0.8345 | -0.1328 | +#> |<span style='font-weight: bold;'> 86</span>| 290.76934 | 1.014 | -1.063 | -1.097 | 1.608 | +#> |.....................| -2.997 | -0.6382 | -0.7915 | -0.5722 | +#> | U| 290.76934 | 94.36 | -0.1836 | 2.085 | 2.510 | +#> |.....................| 5.960e-07 | 0.9771 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.76934</span> | 94.36 | 0.8322 | 8.044 | 2.510 | +#> |.....................| 5.960e-07 | 0.9771 | 1.237 | 1.503 | +#> | F| Forward Diff. | -1.203 | 0.7543 | 1.182 | 4.565 | +#> |.....................| 0.03490 | 3.166 | 0.8589 | -0.1256 | +#> |<span style='font-weight: bold;'> 87</span>| 290.75687 | 1.014 | -1.063 | -1.097 | 1.606 | +#> |.....................| -2.997 | -0.6397 | -0.7919 | -0.5722 | +#> | U| 290.75687 | 94.41 | -0.1840 | 2.084 | 2.508 | +#> |.....................| 5.960e-07 | 0.9760 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.75687</span> | 94.41 | 0.8319 | 8.039 | 2.508 | +#> |.....................| 5.960e-07 | 0.9760 | 1.237 | 1.503 | +#> |<span style='font-weight: bold;'> 88</span>| 290.75123 | 1.015 | -1.063 | -1.098 | 1.604 | +#> |.....................| -2.997 | -0.6414 | -0.7924 | -0.5721 | +#> | U| 290.75123 | 94.47 | -0.1844 | 2.084 | 2.507 | +#> |.....................| 5.960e-07 | 0.9747 | 1.236 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.75123</span> | 94.47 | 0.8316 | 8.034 | 2.507 | +#> |.....................| 5.960e-07 | 0.9747 | 1.236 | 1.503 | +#> | F| Forward Diff. | 26.23 | 0.7709 | 1.374 | 4.560 | +#> |.....................| 0.04194 | 3.213 | 0.7966 | -0.1353 | +#> |<span style='font-weight: bold;'> 89</span>| 290.71744 | 1.014 | -1.067 | -1.096 | 1.601 | +#> |.....................| -2.997 | -0.6448 | -0.7915 | -0.5726 | +#> | U| 290.71744 | 94.37 | -0.1875 | 2.086 | 2.506 | +#> |.....................| 5.960e-07 | 0.9722 | 1.237 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.71744</span> | 94.37 | 0.8291 | 8.054 | 2.506 | +#> |.....................| 5.960e-07 | 0.9722 | 1.237 | 1.503 | +#> | F| Forward Diff. | 0.1928 | 0.6670 | 1.256 | 4.555 | +#> |.....................| 0.04212 | 3.227 | 0.8436 | -0.1302 | +#> |<span style='font-weight: bold;'> 90</span>| 290.68496 | 1.013 | -1.067 | -1.097 | 1.597 | +#> |.....................| -2.997 | -0.6481 | -0.7924 | -0.5725 | +#> | U| 290.68496 | 94.35 | -0.1881 | 2.085 | 2.503 | +#> |.....................| 5.960e-07 | 0.9698 | 1.236 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.68496</span> | 94.35 | 0.8285 | 8.044 | 2.503 | +#> |.....................| 5.960e-07 | 0.9698 | 1.236 | 1.503 | +#> |<span style='font-weight: bold;'> 91</span>| 290.59496 | 1.013 | -1.069 | -1.101 | 1.583 | +#> |.....................| -2.997 | -0.6580 | -0.7950 | -0.5721 | +#> | U| 290.59496 | 94.29 | -0.1902 | 2.081 | 2.496 | +#> |.....................| 5.960e-07 | 0.9627 | 1.233 | 1.503 | +#> | X|<span style='font-weight: bold;'> 290.59496</span> | 94.29 | 0.8268 | 8.013 | 2.496 | +#> |.....................| 5.960e-07 | 0.9627 | 1.233 | 1.503 | +#> |<span style='font-weight: bold;'> 92</span>| 290.34408 | 1.010 | -1.077 | -1.116 | 1.527 | +#> |.....................| -2.997 | -0.6974 | -0.8053 | -0.5705 | +#> | U| 290.34408 | 94.08 | -0.1983 | 2.066 | 2.465 | +#> |.....................| 5.960e-07 | 0.9340 | 1.223 | 1.505 | +#> | X|<span style='font-weight: bold;'> 290.34408</span> | 94.08 | 0.8201 | 7.891 | 2.465 | +#> |.....................| 5.960e-07 | 0.9340 | 1.223 | 1.505 | +#> | F| Forward Diff. | -74.08 | 0.3588 | -0.1794 | 3.803 | +#> |.....................| 0.04205 | 3.779 | 0.06785 | -0.005437 | +#> |<span style='font-weight: bold;'> 93</span>| 289.95778 | 1.012 | -1.081 | -1.068 | 1.490 | +#> |.....................| -2.997 | -0.7670 | -0.7909 | -0.5845 | +#> | U| 289.95778 | 94.18 | -0.2020 | 2.114 | 2.445 | +#> |.....................| 5.960e-07 | 0.8834 | 1.238 | 1.490 | +#> | X|<span style='font-weight: bold;'> 289.95778</span> | 94.18 | 0.8171 | 8.282 | 2.445 | +#> |.....................| 5.960e-07 | 0.8834 | 1.238 | 1.490 | +#> |<span style='font-weight: bold;'> 94</span>| 289.83089 | 1.009 | -1.086 | -1.006 | 1.442 | +#> |.....................| -2.997 | -0.8563 | -0.7725 | -0.6025 | +#> | U| 289.83089 | 93.98 | -0.2067 | 2.176 | 2.418 | +#> |.....................| 5.960e-07 | 0.8185 | 1.257 | 1.470 | +#> | X|<span style='font-weight: bold;'> 289.83089</span> | 93.98 | 0.8132 | 8.812 | 2.418 | +#> |.....................| 5.960e-07 | 0.8185 | 1.257 | 1.470 | +#> | F| Forward Diff. | -65.01 | -0.01626 | 4.198 | 3.297 | +#> |.....................| 0.05097 | 3.562 | 1.909 | -0.3175 | +#> |<span style='font-weight: bold;'> 95</span>| 290.63229 | 1.014 | -1.226 | -1.068 | 1.287 | +#> |.....................| -2.997 | -1.101 | -0.7595 | -0.8853 | +#> | U| 290.63229 | 94.43 | -0.3467 | 2.113 | 2.333 | +#> |.....................| 5.960e-07 | 0.6407 | 1.271 | 1.167 | +#> | X|<span style='font-weight: bold;'> 290.63229</span> | 94.43 | 0.7070 | 8.277 | 2.333 | +#> |.....................| 5.960e-07 | 0.6407 | 1.271 | 1.167 | +#> |<span style='font-weight: bold;'> 96</span>| 289.56584 | 1.017 | -1.134 | -1.028 | 1.388 | +#> |.....................| -2.997 | -0.9416 | -0.7681 | -0.7007 | +#> | U| 289.56584 | 94.70 | -0.2554 | 2.154 | 2.389 | +#> |.....................| 5.960e-07 | 0.7564 | 1.261 | 1.365 | +#> | X|<span style='font-weight: bold;'> 289.56584</span> | 94.70 | 0.7746 | 8.619 | 2.389 | +#> |.....................| 5.960e-07 | 0.7564 | 1.261 | 1.365 | +#> | F| Forward Diff. | 59.80 | -0.9076 | 3.450 | 2.884 | +#> |.....................| 0.04168 | 2.247 | 1.868 | -3.338 | +#> |<span style='font-weight: bold;'> 97</span>| 289.16078 | 1.017 | -1.094 | -1.010 | 1.317 | +#> |.....................| -2.997 | -0.9798 | -0.7948 | -0.5837 | +#> | U| 289.16078 | 94.64 | -0.2152 | 2.172 | 2.350 | +#> |.....................| 5.960e-07 | 0.7287 | 1.234 | 1.491 | +#> | X|<span style='font-weight: bold;'> 289.16078</span> | 94.64 | 0.8063 | 8.773 | 2.350 | +#> |.....................| 5.960e-07 | 0.7287 | 1.234 | 1.491 | +#> | F| Forward Diff. | 50.77 | -0.08196 | 5.132 | 1.948 | +#> |.....................| 0.04608 | 1.474 | 0.6389 | 0.4459 | +#> |<span style='font-weight: bold;'> 98</span>| 290.19527 | 1.002 | -1.018 | -1.037 | 1.157 | +#> |.....................| -2.997 | -1.195 | -0.7989 | -0.6967 | +#> | U| 290.19527 | 93.32 | -0.1385 | 2.145 | 2.263 | +#> |.....................| 5.960e-07 | 0.5724 | 1.229 | 1.370 | +#> | X|<span style='font-weight: bold;'> 290.19527</span> | 93.32 | 0.8707 | 8.542 | 2.263 | +#> |.....................| 5.960e-07 | 0.5724 | 1.229 | 1.370 | +#> |<span style='font-weight: bold;'> 99</span>| 289.65582 | 1.003 | -1.072 | -1.019 | 1.270 | +#> |.....................| -2.997 | -1.043 | -0.7961 | -0.6170 | +#> | U| 289.65582 | 93.34 | -0.1926 | 2.163 | 2.324 | +#> |.....................| 5.960e-07 | 0.6825 | 1.232 | 1.455 | +#> | X|<span style='font-weight: bold;'> 289.65582</span> | 93.34 | 0.8248 | 8.696 | 2.324 | +#> |.....................| 5.960e-07 | 0.6825 | 1.232 | 1.455 | +#> |<span style='font-weight: bold;'> 100</span>| 289.77865 | 1.003 | -1.088 | -1.014 | 1.303 | +#> |.....................| -2.997 | -0.9984 | -0.7953 | -0.5934 | +#> | U| 289.77865 | 93.35 | -0.2087 | 2.168 | 2.342 | +#> |.....................| 5.960e-07 | 0.7151 | 1.233 | 1.480 | +#> | X|<span style='font-weight: bold;'> 289.77865</span> | 93.35 | 0.8116 | 8.742 | 2.342 | +#> |.....................| 5.960e-07 | 0.7151 | 1.233 | 1.480 | +#> |<span style='font-weight: bold;'> 101</span>| 289.23886 | 1.008 | -1.094 | -1.011 | 1.317 | +#> |.....................| -2.997 | -0.9800 | -0.7949 | -0.5837 | +#> | U| 289.23886 | 93.87 | -0.2152 | 2.171 | 2.350 | +#> |.....................| 5.960e-07 | 0.7285 | 1.234 | 1.491 | +#> | X|<span style='font-weight: bold;'> 289.23886</span> | 93.87 | 0.8064 | 8.765 | 2.350 | +#> |.....................| 5.960e-07 | 0.7285 | 1.234 | 1.491 | +#> |<span style='font-weight: bold;'> 102</span>| 289.07165 | 1.013 | -1.094 | -1.010 | 1.317 | +#> |.....................| -2.997 | -0.9799 | -0.7948 | -0.5837 | +#> | U| 289.07165 | 94.31 | -0.2152 | 2.171 | 2.350 | +#> |.....................| 5.960e-07 | 0.7286 | 1.234 | 1.491 | +#> | X|<span style='font-weight: bold;'> 289.07165</span> | 94.31 | 0.8063 | 8.770 | 2.350 | +#> |.....................| 5.960e-07 | 0.7286 | 1.234 | 1.491 | +#> | F| Forward Diff. | -0.3607 | -0.1394 | 4.728 | 1.937 | +#> |.....................| 0.04518 | 1.333 | 0.6601 | 0.3686 | +#> |<span style='font-weight: bold;'> 103</span>| 289.05383 | 1.013 | -1.094 | -1.014 | 1.315 | +#> |.....................| -2.997 | -0.9807 | -0.7952 | -0.5839 | +#> | U| 289.05383 | 94.33 | -0.2152 | 2.168 | 2.349 | +#> |.....................| 5.960e-07 | 0.7280 | 1.233 | 1.490 | +#> | X|<span style='font-weight: bold;'> 289.05383</span> | 94.33 | 0.8064 | 8.742 | 2.349 | +#> |.....................| 5.960e-07 | 0.7280 | 1.233 | 1.490 | +#> |<span style='font-weight: bold;'> 104</span>| 289.00706 | 1.014 | -1.094 | -1.023 | 1.312 | +#> |.....................| -2.997 | -0.9834 | -0.7965 | -0.5847 | +#> | U| 289.00706 | 94.40 | -0.2149 | 2.159 | 2.347 | +#> |.....................| 5.960e-07 | 0.7260 | 1.232 | 1.490 | +#> | X|<span style='font-weight: bold;'> 289.00706</span> | 94.40 | 0.8066 | 8.661 | 2.347 | +#> |.....................| 5.960e-07 | 0.7260 | 1.232 | 1.490 | +#> |<span style='font-weight: bold;'> 105</span>| 288.92149 | 1.016 | -1.093 | -1.055 | 1.299 | +#> |.....................| -2.997 | -0.9924 | -0.8010 | -0.5872 | +#> | U| 288.92149 | 94.63 | -0.2139 | 2.127 | 2.340 | +#> |.....................| 5.960e-07 | 0.7195 | 1.227 | 1.487 | +#> | X|<span style='font-weight: bold;'> 288.92149</span> | 94.63 | 0.8074 | 8.388 | 2.340 | +#> |.....................| 5.960e-07 | 0.7195 | 1.227 | 1.487 | +#> | F| Forward Diff. | 43.21 | 0.03028 | 3.221 | 1.557 | +#> |.....................| 0.008151 | 1.175 | 0.2057 | -0.1154 | +#> |<span style='font-weight: bold;'> 106</span>| 288.79118 | 1.014 | -1.096 | -1.061 | 1.264 | +#> |.....................| -2.997 | -1.027 | -0.7973 | -0.5956 | +#> | U| 288.79118 | 94.43 | -0.2174 | 2.120 | 2.321 | +#> |.....................| 5.960e-07 | 0.6943 | 1.231 | 1.478 | +#> | X|<span style='font-weight: bold;'> 288.79118</span> | 94.43 | 0.8046 | 8.334 | 2.321 | +#> |.....................| 5.960e-07 | 0.6943 | 1.231 | 1.478 | +#> | F| Forward Diff. | 10.81 | -0.06252 | 2.679 | 1.204 | +#> |.....................| 0.03262 | -0.1240 | 0.4322 | -0.2470 | +#> |<span style='font-weight: bold;'> 107</span>| 288.75294 | 1.013 | -1.132 | -1.081 | 1.252 | +#> |.....................| -2.997 | -1.011 | -0.7930 | -0.5741 | +#> | U| 288.75294 | 94.35 | -0.2531 | 2.101 | 2.314 | +#> |.....................| 5.960e-07 | 0.7060 | 1.235 | 1.501 | +#> | X|<span style='font-weight: bold;'> 288.75294</span> | 94.35 | 0.7764 | 8.173 | 2.314 | +#> |.....................| 5.960e-07 | 0.7060 | 1.235 | 1.501 | +#> | F| Forward Diff. | -3.091 | -0.8602 | 1.971 | 1.009 | +#> |.....................| 0.04475 | 0.5130 | 0.7746 | 0.2303 | +#> |<span style='font-weight: bold;'> 108</span>| 288.69834 | 1.013 | -1.093 | -1.104 | 1.232 | +#> |.....................| -2.997 | -1.011 | -0.7973 | -0.5721 | +#> | U| 288.69834 | 94.27 | -0.2136 | 2.078 | 2.303 | +#> |.....................| 5.960e-07 | 0.7061 | 1.231 | 1.503 | +#> | X|<span style='font-weight: bold;'> 288.69834</span> | 94.27 | 0.8077 | 7.987 | 2.303 | +#> |.....................| 5.960e-07 | 0.7061 | 1.231 | 1.503 | +#> | F| Forward Diff. | -16.61 | 0.06814 | 0.8311 | 0.6184 | +#> |.....................| 0.03151 | 0.5612 | 0.4558 | 0.3067 | +#> |<span style='font-weight: bold;'> 109</span>| 288.67099 | 1.014 | -1.108 | -1.122 | 1.197 | +#> |.....................| -2.997 | -1.038 | -0.8030 | -0.5758 | +#> | U| 288.67099 | 94.36 | -0.2285 | 2.060 | 2.284 | +#> |.....................| 5.960e-07 | 0.6866 | 1.225 | 1.499 | +#> | X|<span style='font-weight: bold;'> 288.67099</span> | 94.36 | 0.7957 | 7.847 | 2.284 | +#> |.....................| 5.960e-07 | 0.6866 | 1.225 | 1.499 | +#> | F| Forward Diff. | -4.975 | -0.2154 | 0.1983 | 0.1047 | +#> |.....................| 0.03564 | -0.4652 | 0.1266 | 0.2269 | +#> |<span style='font-weight: bold;'> 110</span>| 288.66432 | 1.014 | -1.097 | -1.128 | 1.196 | +#> |.....................| -2.997 | -1.027 | -0.8055 | -0.5813 | +#> | U| 288.66432 | 94.40 | -0.2184 | 2.053 | 2.283 | +#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 | +#> | X|<span style='font-weight: bold;'> 288.66432</span> | 94.40 | 0.8038 | 7.793 | 2.283 | +#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 | +#> | F| Forward Diff. | 0.3927 | 0.02780 | -0.05986 | 0.04997 | +#> |.....................| 0.03453 | -0.01180 | -0.03408 | 0.03556 | +#> |<span style='font-weight: bold;'> 111</span>| 288.66432 | 1.014 | -1.097 | -1.128 | 1.196 | +#> |.....................| -2.997 | -1.027 | -0.8055 | -0.5813 | +#> | U| 288.66432 | 94.40 | -0.2184 | 2.053 | 2.283 | +#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 | +#> | X|<span style='font-weight: bold;'> 288.66432</span> | 94.40 | 0.8038 | 7.793 | 2.283 | +#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 | +#> done</div><div class='output co'>#> <span class='message'>Calculating residuals/tables</span></div><div class='output co'>#> <span class='message'>done</span></div><div class='output co'>#> <span class='warning'>Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))</span></div><div class='output co'>#> <span class='warning'>Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))</span></div><div class='output co'>#> <span class='warning'>Warning: last objective function was not at minimum, possible problems in optimization</span></div><div class='output co'>#> <span class='warning'>Warning: parameter estimate near boundary; covariance not calculated</span> +#> <span class='warning'> use 'getVarCov' to calculate anyway</span></div><div class='output co'>#> <span class='warning'>Warning: gradient problems with initial estimate; see $scaleInfo</span></div><div class='input'> +<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span> + <span class='va'>f_nlmixr_sfo_saem</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_sfo_focei</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_saem</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_fomc_focei</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_saem</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_dfop_focei</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_hs_saem</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_hs_focei</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_saem_tc</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_fomc_focei_tc</span><span class='op'>$</span><span class='va'>nm</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)</span></div><div class='output co'>#> </div><div class='output co'>#> df AIC +#> f_nlmixr_sfo_saem$nm 5 627.9197 +#> f_nlmixr_sfo_focei$nm 5 625.0512 +#> f_nlmixr_fomc_saem$nm 7 463.7245 +#> f_nlmixr_fomc_focei$nm 7 468.0822 +#> f_nlmixr_dfop_saem$nm 9 518.5794 +#> f_nlmixr_dfop_focei$nm 9 537.6309 +#> f_nlmixr_hs_saem$nm 9 535.9011 +#> f_nlmixr_hs_focei$nm 9 544.7590 +#> f_nlmixr_fomc_saem_tc$nm 8 463.5871 +#> f_nlmixr_fomc_focei_tc$nm 8 470.0733</div><div class='input'> +<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span><span class='op'>)</span> +</div><div class='output co'>#> [1] 468.0781</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"HS"</span>, <span class='op'>]</span><span class='op'>)</span><span class='op'>)</span> +</div><div class='output co'>#> [1] 535.609</div><div class='input'> +<span class='co'># nlme is comparable to nlmixr with focei, saem finds a better</span> +<span class='co'># solution, the two-component error model does not improve it</span> +<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlmixr_fomc_saem</span><span class='op'>)</span> +</div><div class='img'><img src='nlmixr.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'> +<span class='va'>sfo_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"A1"</span><span class='op'>)</span>, + A1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fomc_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"A1"</span><span class='op'>)</span>, + A1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='st'>"A1"</span><span class='op'>)</span>, + A1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> +<span class='va'>f_mmkin_const</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span> + <span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>sfo_sfo</span>, <span class='st'>"FOMC-SFO"</span> <span class='op'>=</span> <span class='va'>fomc_sfo</span>, <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>, + <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"const"</span><span class='op'>)</span> +<span class='va'>f_mmkin_obs</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span> + <span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>sfo_sfo</span>, <span class='st'>"FOMC-SFO"</span> <span class='op'>=</span> <span class='va'>fomc_sfo</span>, <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>, + <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> +<span class='va'>f_mmkin_tc</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span> + <span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>sfo_sfo</span>, <span class='st'>"FOMC-SFO"</span> <span class='op'>=</span> <span class='va'>fomc_sfo</span>, <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>, + <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> + +<span class='co'># A single constant variance is currently only possible with est = 'focei' in nlmixr</span> +<span class='va'>f_nlmixr_sfo_sfo_focei_const</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_const</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_10~exp(rx_expr_7);</span> +#> <span class='message'>d/dt(parent)=-rx_expr_10*parent;</span> +#> <span class='message'>rx_expr_8~ETA[3]+THETA[3];</span> +#> <span class='message'>rx_expr_11~exp(rx_expr_8);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_11*A1+rx_expr_10*parent*f_parent_to_A1;</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_13~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_9~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_14~rx_expr_9*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_14)*(rx_expr_0)+(rx_expr_4+rx_expr_14)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_12~Rx_pow_di(THETA[5],2);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*rx_expr_12+(rx_expr_2)*(rx_expr_1)*rx_expr_12;</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_parent=THETA[2];</span> +#> <span class='message'>log_k_A1=THETA[3];</span> +#> <span class='message'>f_parent_qlogis=THETA[4];</span> +#> <span class='message'>sigma=THETA[5];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_parent=ETA[2];</span> +#> <span class='message'>eta.log_k_A1=ETA[3];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[4];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_parent=rx_expr_10;</span> +#> <span class='message'>k_A1=rx_expr_11;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[4]+THETA[4])));</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 5.548 0.415 5.961</span></div><div class='input'><span class='va'>f_nlmixr_fomc_sfo_focei_const</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_const</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_13~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_15~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_16~1+rx_expr_15;</span> +#> <span class='message'>rx_expr_18~rx_expr_7-(rx_expr_8);</span> +#> <span class='message'>rx_expr_20~exp(rx_expr_18);</span> +#> <span class='message'>d/dt(parent)=-rx_expr_20*parent/(rx_expr_16);</span> +#> <span class='message'>rx_expr_9~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_11~exp(rx_expr_9);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_11*A1+rx_expr_20*parent*f_parent_to_A1/(rx_expr_16);</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_14~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_14+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_14+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_10~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_17~rx_expr_10*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_17)*(rx_expr_0)+(rx_expr_4+rx_expr_17)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_12~Rx_pow_di(THETA[6],2);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*rx_expr_12+(rx_expr_2)*(rx_expr_1)*rx_expr_12;</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_alpha=THETA[4];</span> +#> <span class='message'>log_beta=THETA[5];</span> +#> <span class='message'>sigma=THETA[6];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_alpha=ETA[4];</span> +#> <span class='message'>eta.log_beta=ETA[5];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_11;</span> +#> <span class='message'>alpha=exp(rx_expr_7);</span> +#> <span class='message'>beta=exp(rx_expr_8);</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 6.895 0.416 7.309</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_focei_const</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_const</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[6]+THETA[6];</span> +#> <span class='message'>rx_expr_9~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(rx_expr_7);</span> +#> <span class='message'>rx_expr_13~exp(rx_expr_9);</span> +#> <span class='message'>rx_expr_15~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_16~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_18~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_20~1+rx_expr_18;</span> +#> <span class='message'>rx_expr_25~1/(rx_expr_20);</span> +#> <span class='message'>rx_expr_27~(rx_expr_25);</span> +#> <span class='message'>rx_expr_28~1-rx_expr_27;</span> +#> <span class='message'>d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_20)+exp(rx_expr_9-rx_expr_16)*(rx_expr_28))/(exp(-t*rx_expr_12)/(rx_expr_20)+exp(-t*rx_expr_13)*(rx_expr_28));</span> +#> <span class='message'>rx_expr_10~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_14~exp(rx_expr_10);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_20)+exp(rx_expr_9-rx_expr_16)*(rx_expr_28))/(exp(-t*rx_expr_12)/(rx_expr_20)+exp(-t*rx_expr_13)*(rx_expr_28));</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_19~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_19+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_19+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_11~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_23~rx_expr_11*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_23)*(rx_expr_0)+(rx_expr_4+rx_expr_23)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_17~Rx_pow_di(THETA[7],2);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*rx_expr_17+(rx_expr_2)*(rx_expr_1)*rx_expr_17;</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_k1=THETA[4];</span> +#> <span class='message'>log_k2=THETA[5];</span> +#> <span class='message'>g_qlogis=THETA[6];</span> +#> <span class='message'>sigma=THETA[7];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_k1=ETA[4];</span> +#> <span class='message'>eta.log_k2=ETA[5];</span> +#> <span class='message'>eta.g_qlogis=ETA[6];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_14;</span> +#> <span class='message'>k1=rx_expr_12;</span> +#> <span class='message'>k2=rx_expr_13;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>g=1/(rx_expr_20);</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 15.03 0.478 15.51</span></div><div class='input'> +<span class='co'># Variance by variable is supported by 'saem' and 'focei'</span> +<span class='va'>f_nlmixr_fomc_sfo_saem_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_obs</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='error'>Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 1.294 0.134 1.427</span></div><div class='input'><span class='va'>f_nlmixr_fomc_sfo_focei_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_obs</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_14~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_15~1+rx_expr_14;</span> +#> <span class='message'>rx_expr_17~rx_expr_7-(rx_expr_8);</span> +#> <span class='message'>rx_expr_19~exp(rx_expr_17);</span> +#> <span class='message'>d/dt(parent)=-rx_expr_19*parent/(rx_expr_15);</span> +#> <span class='message'>rx_expr_9~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_11~exp(rx_expr_9);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_11*A1+rx_expr_19*parent*f_parent_to_A1/(rx_expr_15);</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_13~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_10~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_16~rx_expr_10*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*Rx_pow_di(THETA[7],2)+(rx_expr_2)*(rx_expr_1)*Rx_pow_di(THETA[6],2);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_alpha=THETA[4];</span> +#> <span class='message'>log_beta=THETA[5];</span> +#> <span class='message'>sigma_parent=THETA[6];</span> +#> <span class='message'>sigma_A1=THETA[7];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_alpha=ETA[4];</span> +#> <span class='message'>eta.log_beta=ETA[5];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_11;</span> +#> <span class='message'>alpha=exp(rx_expr_7);</span> +#> <span class='message'>beta=exp(rx_expr_8);</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 6.584 0.393 6.976</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_saem_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='error'>Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 1.302 0.142 1.443</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_focei_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[6]+THETA[6];</span> +#> <span class='message'>rx_expr_9~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(rx_expr_7);</span> +#> <span class='message'>rx_expr_13~exp(rx_expr_9);</span> +#> <span class='message'>rx_expr_15~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_16~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_17~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_19~1+rx_expr_17;</span> +#> <span class='message'>rx_expr_24~1/(rx_expr_19);</span> +#> <span class='message'>rx_expr_26~(rx_expr_24);</span> +#> <span class='message'>rx_expr_27~1-rx_expr_26;</span> +#> <span class='message'>d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));</span> +#> <span class='message'>rx_expr_10~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_14~exp(rx_expr_10);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_18~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_18+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_18+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_11~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_22~rx_expr_11*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*Rx_pow_di(THETA[8],2)+(rx_expr_2)*(rx_expr_1)*Rx_pow_di(THETA[7],2);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_k1=THETA[4];</span> +#> <span class='message'>log_k2=THETA[5];</span> +#> <span class='message'>g_qlogis=THETA[6];</span> +#> <span class='message'>sigma_parent=THETA[7];</span> +#> <span class='message'>sigma_A1=THETA[8];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_k1=ETA[4];</span> +#> <span class='message'>eta.log_k2=ETA[5];</span> +#> <span class='message'>eta.g_qlogis=ETA[6];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_14;</span> +#> <span class='message'>k1=rx_expr_12;</span> +#> <span class='message'>k2=rx_expr_13;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>g=1/(rx_expr_19);</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 14.58 0.482 15.06</span></div><div class='input'> +<span class='co'># Identical two-component error for all variables is only possible with</span> +<span class='co'># est = 'focei' in nlmixr</span> +<span class='va'>f_nlmixr_fomc_sfo_focei_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_14~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_16~t*rx_expr_14;</span> +#> <span class='message'>rx_expr_17~1+rx_expr_16;</span> +#> <span class='message'>rx_expr_19~rx_expr_7-(rx_expr_8);</span> +#> <span class='message'>rx_expr_21~exp(rx_expr_19);</span> +#> <span class='message'>d/dt(parent)=-rx_expr_21*parent/(rx_expr_17);</span> +#> <span class='message'>rx_expr_9~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_11~exp(rx_expr_9);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_11*A1+rx_expr_21*parent*f_parent_to_A1/(rx_expr_17);</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_15~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_15+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_15+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_10~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_18~rx_expr_10*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_18)*(rx_expr_0)+(rx_expr_4+rx_expr_18)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_12~Rx_pow_di(THETA[7],2);</span> +#> <span class='message'>rx_expr_13~Rx_pow_di(THETA[6],2);</span> +#> <span class='message'>rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_18)*(rx_expr_0)+(rx_expr_4+rx_expr_18)*(rx_expr_2)*(rx_expr_1)),2)*rx_expr_12+rx_expr_13)*(rx_expr_0)+(rx_expr_12*Rx_pow_di(((rx_expr_4+rx_expr_18)*(rx_expr_1)),2)+rx_expr_13)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_alpha=THETA[4];</span> +#> <span class='message'>log_beta=THETA[5];</span> +#> <span class='message'>sigma_low=THETA[6];</span> +#> <span class='message'>rsd_high=THETA[7];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_alpha=ETA[4];</span> +#> <span class='message'>eta.log_beta=ETA[5];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_11;</span> +#> <span class='message'>alpha=exp(rx_expr_7);</span> +#> <span class='message'>beta=exp(rx_expr_8);</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 8.484 0.401 8.883</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_focei_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[6]+THETA[6];</span> +#> <span class='message'>rx_expr_9~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(rx_expr_7);</span> +#> <span class='message'>rx_expr_13~exp(rx_expr_9);</span> +#> <span class='message'>rx_expr_15~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_16~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_19~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_21~1+rx_expr_19;</span> +#> <span class='message'>rx_expr_26~1/(rx_expr_21);</span> +#> <span class='message'>rx_expr_28~(rx_expr_26);</span> +#> <span class='message'>rx_expr_29~1-rx_expr_28;</span> +#> <span class='message'>d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));</span> +#> <span class='message'>rx_expr_10~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_14~exp(rx_expr_10);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_20~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_20+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_20+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_11~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_24~rx_expr_11*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_17~Rx_pow_di(THETA[8],2);</span> +#> <span class='message'>rx_expr_18~Rx_pow_di(THETA[7],2);</span> +#> <span class='message'>rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1)),2)*rx_expr_17+rx_expr_18)*(rx_expr_0)+(rx_expr_17*Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_1)),2)+rx_expr_18)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_k1=THETA[4];</span> +#> <span class='message'>log_k2=THETA[5];</span> +#> <span class='message'>g_qlogis=THETA[6];</span> +#> <span class='message'>sigma_low=THETA[7];</span> +#> <span class='message'>rsd_high=THETA[8];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_k1=ETA[4];</span> +#> <span class='message'>eta.log_k2=ETA[5];</span> +#> <span class='message'>eta.g_qlogis=ETA[6];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_14;</span> +#> <span class='message'>k1=rx_expr_12;</span> +#> <span class='message'>k2=rx_expr_13;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>g=1/(rx_expr_21);</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 18.44 0.438 18.87</span></div><div class='input'> +<span class='co'># Two-component error by variable is possible with both estimation methods</span> +<span class='co'># Variance by variable is supported by 'saem' and 'focei'</span> +<span class='va'>f_nlmixr_fomc_sfo_saem_obs_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span>, + error_model <span class='op'>=</span> <span class='st'>"obs_tc"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='error'>Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.784 0.028 0.812</span></div><div class='input'><span class='va'>f_nlmixr_fomc_sfo_focei_obs_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span>, + error_model <span class='op'>=</span> <span class='st'>"obs_tc"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_14~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_15~1+rx_expr_14;</span> +#> <span class='message'>rx_expr_17~rx_expr_7-(rx_expr_8);</span> +#> <span class='message'>rx_expr_19~exp(rx_expr_17);</span> +#> <span class='message'>d/dt(parent)=-rx_expr_19*parent/(rx_expr_15);</span> +#> <span class='message'>rx_expr_9~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_11~exp(rx_expr_9);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_11*A1+rx_expr_19*parent*f_parent_to_A1/(rx_expr_15);</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_13~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_13+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_10~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_16~rx_expr_10*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1)),2)*Rx_pow_di(THETA[9],2)+Rx_pow_di(THETA[8],2))*(rx_expr_0)+(Rx_pow_di(THETA[7],2)*Rx_pow_di(((rx_expr_4+rx_expr_16)*(rx_expr_1)),2)+Rx_pow_di(THETA[6],2))*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_alpha=THETA[4];</span> +#> <span class='message'>log_beta=THETA[5];</span> +#> <span class='message'>sigma_low_parent=THETA[6];</span> +#> <span class='message'>rsd_high_parent=THETA[7];</span> +#> <span class='message'>sigma_low_A1=THETA[8];</span> +#> <span class='message'>rsd_high_A1=THETA[9];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_alpha=ETA[4];</span> +#> <span class='message'>eta.log_beta=ETA[5];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_11;</span> +#> <span class='message'>alpha=exp(rx_expr_7);</span> +#> <span class='message'>beta=exp(rx_expr_8);</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 8.157 0.51 8.664</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_saem_obs_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"saem"</span>, + error_model <span class='op'>=</span> <span class='st'>"obs_tc"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='error'>Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.81 0.045 0.854</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_focei_obs_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_tc</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, est <span class='op'>=</span> <span class='st'>"focei"</span>, + error_model <span class='op'>=</span> <span class='st'>"obs_tc"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(A1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[6]+THETA[6];</span> +#> <span class='message'>rx_expr_9~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(rx_expr_7);</span> +#> <span class='message'>rx_expr_13~exp(rx_expr_9);</span> +#> <span class='message'>rx_expr_15~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_16~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_17~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_19~1+rx_expr_17;</span> +#> <span class='message'>rx_expr_24~1/(rx_expr_19);</span> +#> <span class='message'>rx_expr_26~(rx_expr_24);</span> +#> <span class='message'>rx_expr_27~1-rx_expr_26;</span> +#> <span class='message'>d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));</span> +#> <span class='message'>rx_expr_10~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_14~exp(rx_expr_10);</span> +#> <span class='message'>d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_18~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_18+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_18+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~A1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_11~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_22~rx_expr_11*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_r_=(rx_expr_0)*(Rx_pow_di(((rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1)),2)*Rx_pow_di(THETA[10],2)+Rx_pow_di(THETA[9],2))+(Rx_pow_di(THETA[8],2)*Rx_pow_di(((rx_expr_4+rx_expr_22)*(rx_expr_1)),2)+Rx_pow_di(THETA[7],2))*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_A1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_k1=THETA[4];</span> +#> <span class='message'>log_k2=THETA[5];</span> +#> <span class='message'>g_qlogis=THETA[6];</span> +#> <span class='message'>sigma_low_parent=THETA[7];</span> +#> <span class='message'>rsd_high_parent=THETA[8];</span> +#> <span class='message'>sigma_low_A1=THETA[9];</span> +#> <span class='message'>rsd_high_A1=THETA[10];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_A1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_k1=ETA[4];</span> +#> <span class='message'>eta.log_k2=ETA[5];</span> +#> <span class='message'>eta.g_qlogis=ETA[6];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_A1=rx_expr_14;</span> +#> <span class='message'>k1=rx_expr_12;</span> +#> <span class='message'>k2=rx_expr_13;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>g=1/(rx_expr_19);</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_A1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 17.34 0.397 17.73</span></div><div class='input'> +<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span> + <span class='va'>f_nlmixr_sfo_sfo_focei_const</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_focei_const</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_focei_const</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_saem_obs</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_focei_obs</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_saem_obs</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_focei_obs</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_focei_tc</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_focei_tc</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_saem_obs_tc</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_fomc_sfo_focei_obs_tc</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_saem_obs_tc</span><span class='op'>$</span><span class='va'>nm</span>, + <span class='va'>f_nlmixr_dfop_sfo_focei_obs_tc</span><span class='op'>$</span><span class='va'>nm</span> +<span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in AIC(f_nlmixr_sfo_sfo_focei_const$nm, f_nlmixr_fomc_sfo_focei_const$nm, f_nlmixr_dfop_sfo_focei_const$nm, f_nlmixr_fomc_sfo_saem_obs$nm, f_nlmixr_fomc_sfo_focei_obs$nm, f_nlmixr_dfop_sfo_saem_obs$nm, f_nlmixr_dfop_sfo_focei_obs$nm, f_nlmixr_fomc_sfo_focei_tc$nm, f_nlmixr_dfop_sfo_focei_tc$nm, f_nlmixr_fomc_sfo_saem_obs_tc$nm, f_nlmixr_fomc_sfo_focei_obs_tc$nm, f_nlmixr_dfop_sfo_saem_obs_tc$nm, f_nlmixr_dfop_sfo_focei_obs_tc$nm): object 'f_nlmixr_sfo_sfo_focei_const' not found</span></div><div class='input'><span class='co'># Currently, FOMC-SFO with two-component error by variable fitted by focei gives the</span> +<span class='co'># lowest AIC</span> +<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlmixr_fomc_sfo_focei_obs_tc</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in plot(f_nlmixr_fomc_sfo_focei_obs_tc): object 'f_nlmixr_fomc_sfo_focei_obs_tc' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>f_nlmixr_fomc_sfo_focei_obs_tc</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in summary(f_nlmixr_fomc_sfo_focei_obs_tc): object 'f_nlmixr_fomc_sfo_focei_obs_tc' not found</span></div><div class='input'><span class='co'># }</span> +</div></pre> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"> + <h2 data-toc-skip>Contents</h2> + </nav> + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + diff --git a/docs/dev/reference/nobs.mkinfit.html b/docs/dev/reference/nobs.mkinfit.html index 621eb622..0b6c963c 100644 --- a/docs/dev/reference/nobs.mkinfit.html +++ b/docs/dev/reference/nobs.mkinfit.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/parms.html b/docs/dev/reference/parms.html index ba0e89bb..9f6f4225 100644 --- a/docs/dev/reference/parms.html +++ b/docs/dev/reference/parms.html @@ -74,7 +74,7 @@ considering the error structure that was assumed for the fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ considering the error structure that was assumed for the fit." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -219,10 +219,10 @@ such matrices is returned.</p> #> #> $DFOP #> Dataset 7 -#> parent_0 91.058971597 +#> parent_0 91.058971589 #> k1 0.044946770 #> k2 0.002868336 -#> g 0.526942414 +#> g 0.526942415 #> sigma 2.221302196 #> </div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span><span class='op'>)</span> </div><div class='output co'>#> $SFO @@ -233,17 +233,17 @@ such matrices is returned.</p> #> #> $FOMC #> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481458 +#> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481459 #> alpha 1.338667 0.4967832 1.639099 1.074460 0.2805272 #> beta 13.033315 14.1451255 5.007077 4.397126 6.9052224 #> sigma 1.847671 1.9167519 1.066063 3.146056 1.6222778 #> #> $DFOP #> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 96.55213663 91.058971597 90.34509493 98.14858820 94.311323733 +#> parent_0 96.55213663 91.058971589 90.34509493 98.14858820 94.311323734 #> k1 0.21954588 0.044946770 0.41232288 0.31697588 0.080663857 #> k2 0.02957934 0.002868336 0.07581766 0.03260384 0.003425417 -#> g 0.44845068 0.526942414 0.66091967 0.65322767 0.342652880 +#> g 0.44845068 0.526942415 0.66091967 0.65322767 0.342652880 #> sigma 1.35690468 2.221302196 1.34169076 2.87159846 1.942067831 #> </div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span>, transformed <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> $SFO diff --git a/docs/dev/reference/plot.mixed.mmkin-1.png b/docs/dev/reference/plot.mixed.mmkin-1.png Binary files differindex 5cb33214..be3c664a 100644 --- a/docs/dev/reference/plot.mixed.mmkin-1.png +++ b/docs/dev/reference/plot.mixed.mmkin-1.png diff --git a/docs/dev/reference/plot.mixed.mmkin-2.png b/docs/dev/reference/plot.mixed.mmkin-2.png Binary files differindex c0d67204..b0e43b11 100644 --- a/docs/dev/reference/plot.mixed.mmkin-2.png +++ b/docs/dev/reference/plot.mixed.mmkin-2.png diff --git a/docs/dev/reference/plot.mixed.mmkin-3.png b/docs/dev/reference/plot.mixed.mmkin-3.png Binary files differindex 5e00afe6..7e2876b3 100644 --- a/docs/dev/reference/plot.mixed.mmkin-3.png +++ b/docs/dev/reference/plot.mixed.mmkin-3.png diff --git a/docs/dev/reference/plot.mixed.mmkin-4.png b/docs/dev/reference/plot.mixed.mmkin-4.png Binary files differindex 6a5f3b9c..945c4d41 100644 --- a/docs/dev/reference/plot.mixed.mmkin-4.png +++ b/docs/dev/reference/plot.mixed.mmkin-4.png diff --git a/docs/dev/reference/plot.mixed.mmkin.html b/docs/dev/reference/plot.mixed.mmkin.html index 55c411e7..7f3faa90 100644 --- a/docs/dev/reference/plot.mixed.mmkin.html +++ b/docs/dev/reference/plot.mixed.mmkin.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -157,11 +157,13 @@ xlim <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/range.html'>range</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</span><span class='op'>$</span><span class='va'>time</span><span class='op'>)</span>, resplot <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"predicted"</span>, <span class='st'>"time"</span><span class='op'>)</span>, pred_over <span class='op'>=</span> <span class='cn'>NULL</span>, + test_log_parms <span class='op'>=</span> <span class='cn'>FALSE</span>, + conf.level <span class='op'>=</span> <span class='fl'>0.6</span>, ymax <span class='op'>=</span> <span class='st'>"auto"</span>, maxabs <span class='op'>=</span> <span class='st'>"auto"</span>, ncol.legend <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'><=</span> <span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'>+</span> <span class='fl'>1</span>, <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'><=</span> <span class='fl'>8</span>, <span class='fl'>3</span>, <span class='fl'>4</span><span class='op'>)</span><span class='op'>)</span>, nrow.legend <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Round.html'>ceiling</a></span><span class='op'>(</span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'>+</span> <span class='fl'>1</span><span class='op'>)</span><span class='op'>/</span><span class='va'>ncol.legend</span><span class='op'>)</span>, - rel.height.legend <span class='op'>=</span> <span class='fl'>0.03</span> <span class='op'>+</span> <span class='fl'>0.08</span> <span class='op'>*</span> <span class='va'>nrow.legend</span>, + rel.height.legend <span class='op'>=</span> <span class='fl'>0.02</span> <span class='op'>+</span> <span class='fl'>0.07</span> <span class='op'>*</span> <span class='va'>nrow.legend</span>, rel.height.bottom <span class='op'>=</span> <span class='fl'>1.1</span>, pch_ds <span class='op'>=</span> <span class='fl'>1</span><span class='op'>:</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span>, col_ds <span class='op'>=</span> <span class='va'>pch_ds</span> <span class='op'>+</span> <span class='fl'>1</span>, @@ -212,6 +214,16 @@ predicted values?</p></td> from <a href='mkinpredict.html'>mkinpredict</a> with a compatible <a href='mkinmod.html'>mkinmod</a>.</p></td> </tr> <tr> + <th>test_log_parms</th> + <td><p>Passed to <a href='mean_degparms.html'>mean_degparms</a> in the case of an +<a href='mixed.html'>mixed.mmkin</a> object</p></td> + </tr> + <tr> + <th>conf.level</th> + <td><p>Passed to <a href='mean_degparms.html'>mean_degparms</a> in the case of an +<a href='mixed.html'>mixed.mmkin</a> object</p></td> + </tr> + <tr> <th>ymax</th> <td><p>Vector of maximum y axis values</p></td> </tr> @@ -278,16 +290,21 @@ corresponding model prediction lines for the different datasets.</p></td> </div><div class='img'><img src='plot.mixed.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='co'># For this fit we need to increase pnlsMaxiter, and we increase the</span> <span class='co'># tolerance in order to speed up the fit for this example evaluation</span> +<span class='co'># It still takes 20 seconds to run</span> <span class='va'>f_nlme</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f</span>, control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>1e-3</span><span class='op'>)</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme</span><span class='op'>)</span> </div><div class='img'><img src='plot.mixed.mmkin-2.png' alt='' width='700' height='433' /></div><div class='input'> <span class='va'>f_saem</span> <span class='op'><-</span> <span class='fu'><a href='saem.html'>saem</a></span><span class='op'>(</span><span class='va'>f</span>, transformations <span class='op'>=</span> <span class='st'>"saemix"</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Dec 21 05:58:23 2020" +#> [1] "Tue Jul 27 16:30:50 2021" #> .... #> Minimisation finished -#> [1] "Mon Dec 21 05:58:30 2020"</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem</span><span class='op'>)</span> +#> [1] "Tue Jul 27 16:30:58 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem</span><span class='op'>)</span> </div><div class='img'><img src='plot.mixed.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'> +<span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> +<span class='va'>f_nlmix</span> <span class='op'><-</span> <span class='fu'>nlmix</span><span class='op'>(</span><span class='va'>f_obs</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in nlmix(f_obs): could not find function "nlmix"</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlmix</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in plot(f_nlmix): object 'f_nlmix' not found</span></div><div class='input'> <span class='co'># We can overlay the two variants if we generate predictions</span> <span class='va'>pred_nlme</span> <span class='op'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>dfop_sfo</span>, <span class='va'>f_nlme</span><span class='op'>$</span><span class='va'>bparms.optim</span><span class='op'>[</span><span class='op'>-</span><span class='fl'>1</span><span class='op'>]</span>, diff --git a/docs/dev/reference/plot.mkinfit-2.png b/docs/dev/reference/plot.mkinfit-2.png Binary files differindex 376c812f..a11d1680 100644 --- a/docs/dev/reference/plot.mkinfit-2.png +++ b/docs/dev/reference/plot.mkinfit-2.png diff --git a/docs/dev/reference/plot.mkinfit-5.png b/docs/dev/reference/plot.mkinfit-5.png Binary files differindex bc44de88..6631aa68 100644 --- a/docs/dev/reference/plot.mkinfit-5.png +++ b/docs/dev/reference/plot.mkinfit-5.png diff --git a/docs/dev/reference/plot.mkinfit-6.png b/docs/dev/reference/plot.mkinfit-6.png Binary files differindex eb8cbd92..946b20c5 100644 --- a/docs/dev/reference/plot.mkinfit-6.png +++ b/docs/dev/reference/plot.mkinfit-6.png diff --git a/docs/dev/reference/plot.mkinfit-7.png b/docs/dev/reference/plot.mkinfit-7.png Binary files differindex 92a664f4..10807ea8 100644 --- a/docs/dev/reference/plot.mkinfit-7.png +++ b/docs/dev/reference/plot.mkinfit-7.png diff --git a/docs/dev/reference/plot.mkinfit.html b/docs/dev/reference/plot.mkinfit.html index c5bfb528..c5249ecd 100644 --- a/docs/dev/reference/plot.mkinfit.html +++ b/docs/dev/reference/plot.mkinfit.html @@ -74,7 +74,7 @@ observed data together with the solution of the fitted model." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> diff --git a/docs/dev/reference/plot.mmkin-1.png b/docs/dev/reference/plot.mmkin-1.png Binary files differindex f12b7907..647dfb8a 100644 --- a/docs/dev/reference/plot.mmkin-1.png +++ b/docs/dev/reference/plot.mmkin-1.png diff --git a/docs/dev/reference/plot.mmkin-2.png b/docs/dev/reference/plot.mmkin-2.png Binary files differindex e3127554..1bc1c9db 100644 --- a/docs/dev/reference/plot.mmkin-2.png +++ b/docs/dev/reference/plot.mmkin-2.png diff --git a/docs/dev/reference/plot.mmkin-3.png b/docs/dev/reference/plot.mmkin-3.png Binary files differindex 5448976e..50d6ffac 100644 --- a/docs/dev/reference/plot.mmkin-3.png +++ b/docs/dev/reference/plot.mmkin-3.png diff --git a/docs/dev/reference/plot.mmkin-4.png b/docs/dev/reference/plot.mmkin-4.png Binary files differindex 9a25fc50..e049fa16 100644 --- a/docs/dev/reference/plot.mmkin-4.png +++ b/docs/dev/reference/plot.mmkin-4.png diff --git a/docs/dev/reference/plot.mmkin-5.png b/docs/dev/reference/plot.mmkin-5.png Binary files differindex 82b422b5..2421995b 100644 --- a/docs/dev/reference/plot.mmkin-5.png +++ b/docs/dev/reference/plot.mmkin-5.png diff --git a/docs/dev/reference/plot.mmkin.html b/docs/dev/reference/plot.mmkin.html index ee80c6e4..9ca0df94 100644 --- a/docs/dev/reference/plot.mmkin.html +++ b/docs/dev/reference/plot.mmkin.html @@ -76,7 +76,7 @@ the fit of at least one model to the same dataset is shown." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> diff --git a/docs/dev/reference/plot.nafta.html b/docs/dev/reference/plot.nafta.html index 9fc59f94..c24fba99 100644 --- a/docs/dev/reference/plot.nafta.html +++ b/docs/dev/reference/plot.nafta.html @@ -73,7 +73,7 @@ function (SFO, then IORE, then DFOP)." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ function (SFO, then IORE, then DFOP)." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> diff --git a/docs/dev/reference/reexports.html b/docs/dev/reference/reexports.html index f12a2690..ac4fa4d9 100644 --- a/docs/dev/reference/reexports.html +++ b/docs/dev/reference/reexports.html @@ -47,6 +47,8 @@ below to see their documentation. nlmenlme + nlmixrnlmixr + " /> @@ -79,7 +81,7 @@ below to see their documentation. </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -128,7 +130,7 @@ below to see their documentation. <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -146,7 +148,7 @@ below to see their documentation. <div class="col-md-9 contents"> <div class="page-header"> <h1>Objects exported from other packages</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/lrtest.mkinfit.R'><code>R/lrtest.mkinfit.R</code></a>, <a href='https://github.com/jranke/mkin/blob/master/R/nlme.mmkin.R'><code>R/nlme.mmkin.R</code></a></small> + <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/lrtest.mkinfit.R'><code>R/lrtest.mkinfit.R</code></a>, <a href='https://github.com/jranke/mkin/blob/master/R/nlme.mmkin.R'><code>R/nlme.mmkin.R</code></a>, <a href='https://github.com/jranke/mkin/blob/master/R/nlmixr.R'><code>R/nlmixr.R</code></a></small> <div class="hidden name"><code>reexports.Rd</code></div> </div> @@ -158,6 +160,8 @@ below to see their documentation.</p> <dt>nlme</dt><dd><p><code><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></code></p></dd> + <dt>nlmixr</dt><dd><p><code><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></code></p></dd> + </dl> </div> diff --git a/docs/dev/reference/residuals.mkinfit.html b/docs/dev/reference/residuals.mkinfit.html index 95114dae..3f518ab7 100644 --- a/docs/dev/reference/residuals.mkinfit.html +++ b/docs/dev/reference/residuals.mkinfit.html @@ -72,7 +72,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -121,7 +121,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -175,7 +175,7 @@ standard deviation obtained from the fitted error model?</p></td> </div><div class='output co'>#> [1] 0.09726374 -0.13912142 -0.15351210 0.73388322 -0.08657004 -0.93204702 #> [7] -0.03269080 1.45347823 -0.88423697</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/residuals.html'>residuals</a></span><span class='op'>(</span><span class='va'>f</span>, standardized <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> [1] 0.13969917 -0.19981904 -0.22048826 1.05407091 -0.12433989 -1.33869208 -#> [7] -0.04695354 2.08761977 -1.27002287</div></pre> +#> [7] -0.04695355 2.08761977 -1.27002287</div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> <nav id="toc" data-toggle="toc" class="sticky-top"> diff --git a/docs/dev/reference/saem-1.png b/docs/dev/reference/saem-1.png Binary files differindex 2df248bb..0e87d741 100644 --- a/docs/dev/reference/saem-1.png +++ b/docs/dev/reference/saem-1.png diff --git a/docs/dev/reference/saem-2.png b/docs/dev/reference/saem-2.png Binary files differindex d4a2c1be..456a4c58 100644 --- a/docs/dev/reference/saem-2.png +++ b/docs/dev/reference/saem-2.png diff --git a/docs/dev/reference/saem-3.png b/docs/dev/reference/saem-3.png Binary files differindex 6a32cda1..27d43e53 100644 --- a/docs/dev/reference/saem-3.png +++ b/docs/dev/reference/saem-3.png diff --git a/docs/dev/reference/saem-4.png b/docs/dev/reference/saem-4.png Binary files differindex bf24d6b0..5c089bbc 100644 --- a/docs/dev/reference/saem-4.png +++ b/docs/dev/reference/saem-4.png diff --git a/docs/dev/reference/saem-5.png b/docs/dev/reference/saem-5.png Binary files differindex 6e6e0f91..d22e7285 100644 --- a/docs/dev/reference/saem-5.png +++ b/docs/dev/reference/saem-5.png diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index 59589378..15271c8a 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -74,7 +74,7 @@ Expectation Maximisation algorithm (SAEM)." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> </span> </div> @@ -158,9 +158,13 @@ Expectation Maximisation algorithm (SAEM).</p> <span class='va'>object</span>, transformations <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"mkin"</span>, <span class='st'>"saemix"</span><span class='op'>)</span>, degparms_start <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></span><span class='op'>(</span><span class='op'>)</span>, + test_log_parms <span class='op'>=</span> <span class='cn'>TRUE</span>, + conf.level <span class='op'>=</span> <span class='fl'>0.6</span>, solution_type <span class='op'>=</span> <span class='st'>"auto"</span>, - control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>displayProgress <span class='op'>=</span> <span class='cn'>FALSE</span>, print <span class='op'>=</span> <span class='cn'>FALSE</span>, save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span> - <span class='cn'>FALSE</span><span class='op'>)</span>, + nbiter.saemix <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>300</span>, <span class='fl'>100</span><span class='op'>)</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>displayProgress <span class='op'>=</span> <span class='cn'>FALSE</span>, print <span class='op'>=</span> <span class='cn'>FALSE</span>, nbiter.saemix <span class='op'>=</span> <span class='va'>nbiter.saemix</span>, + save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>, + fail_with_errors <span class='op'>=</span> <span class='cn'>TRUE</span>, verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, quiet <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span> @@ -174,6 +178,7 @@ Expectation Maximisation algorithm (SAEM).</p> solution_type <span class='op'>=</span> <span class='st'>"auto"</span>, transformations <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"mkin"</span>, <span class='st'>"saemix"</span><span class='op'>)</span>, degparms_start <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></span><span class='op'>(</span><span class='op'>)</span>, + test_log_parms <span class='op'>=</span> <span class='cn'>FALSE</span>, verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span> <span class='op'>)</span> @@ -206,13 +211,35 @@ SFO or DFOP is used for the parent and there is either no metabolite or one.</p> be used to override the starting values obtained from the 'mmkin' object.</p></td> </tr> <tr> + <th>test_log_parms</th> + <td><p>If TRUE, an attempt is made to use more robust starting +values for population parameters fitted as log parameters in mkin (like +rate constants) by only considering rate constants that pass the t-test +when calculating mean degradation parameters using <a href='mean_degparms.html'>mean_degparms</a>.</p></td> + </tr> + <tr> + <th>conf.level</th> + <td><p>Possibility to adjust the required confidence level +for parameter that are tested if requested by 'test_log_parms'.</p></td> + </tr> + <tr> <th>solution_type</th> <td><p>Possibility to specify the solution type in case the automatic choice is not desired</p></td> </tr> <tr> + <th>nbiter.saemix</th> + <td><p>Convenience option to increase the number of +iterations</p></td> + </tr> + <tr> <th>control</th> - <td><p>Passed to <a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix::saemix</a></p></td> + <td><p>Passed to <a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix::saemix</a>.</p></td> + </tr> + <tr> + <th>fail_with_errors</th> + <td><p>Should a failure to compute standard errors +from the inverse of the Fisher Information Matrix be a failure?</p></td> </tr> <tr> <th>verbose</th> @@ -261,33 +288,39 @@ using <a href='mmkin.html'>mmkin</a>.</p> state.ini <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span><span class='op'>)</span>, fixed_initials <span class='op'>=</span> <span class='st'>"parent"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>f_saem_p0_fixed</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:42 2021" +#> [1] "Tue Jul 27 16:31:02 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:43 2021"</div><div class='input'> +#> [1] "Tue Jul 27 16:31:04 2021"</div><div class='input'> <span class='va'>f_mmkin_parent</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>f_saem_sfo</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:45 2021" +#> [1] "Tue Jul 27 16:31:06 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:46 2021"</div><div class='input'><span class='va'>f_saem_fomc</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span> +#> [1] "Tue Jul 27 16:31:07 2021"</div><div class='input'><span class='va'>f_saem_fomc</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:47 2021" +#> [1] "Tue Jul 27 16:31:07 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:49 2021"</div><div class='input'><span class='va'>f_saem_dfop</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span><span class='op'>)</span> +#> [1] "Tue Jul 27 16:31:09 2021"</div><div class='input'><span class='va'>f_saem_dfop</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:49 2021" +#> [1] "Tue Jul 27 16:31:10 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:52 2021"</div><div class='input'> +#> [1] "Tue Jul 27 16:31:12 2021"</div><div class='input'> <span class='co'># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span> <span class='co'># functions from saemix</span> <span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'>saemix</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Package saemix, version 3.1.9000</span> -#> <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>f_saem_sfo</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_dfop</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in compare.saemix(list(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so)): 'compare.saemix' requires at least two models.</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span> +#> <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='output co'>#> <span class='message'></span> +#> <span class='message'>Attaching package: ‘saemix’</span></div><div class='output co'>#> <span class='message'>The following object is masked from ‘package:RxODE’:</span> +#> <span class='message'></span> +#> <span class='message'> phi</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='va'>f_saem_sfo</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_dfop</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Likelihoods calculated by importance sampling</span></div><div class='output co'>#> AIC BIC +#> 1 624.2484 622.2956 +#> 2 467.7096 464.9757 +#> 3 495.4373 491.9222</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span> </div><div class='output co'>#> Plotting convergence plots</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"individual.fit"</span><span class='op'>)</span> </div><div class='img'><img src='saem-1.png' alt='' width='700' height='433' /></div><div class='output co'>#> Plotting individual fits</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"npde"</span><span class='op'>)</span> </div><div class='img'><img src='saem-2.png' alt='' width='700' height='433' /></div><div class='output co'>#> Simulating data using nsim = 1000 simulated datasets @@ -324,11 +357,13 @@ using <a href='mmkin.html'>mmkin</a>.</p> <span class='va'>f_mmkin_parent_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> <span class='va'>f_saem_fomc_tc</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:55 2021" +#> [1] "Tue Jul 27 16:31:16 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:00 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc_tc</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)): 'compare.saemix' requires at least two models.</span></div><div class='input'> +#> [1] "Tue Jul 27 16:31:20 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc_tc</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Likelihoods calculated by importance sampling</span></div><div class='output co'>#> AIC BIC +#> 1 467.7096 464.9757 +#> 2 469.6831 466.5586</div><div class='input'> <span class='va'>sfo_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"A1"</span><span class='op'>)</span>, A1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fomc_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"A1"</span><span class='op'>)</span>, @@ -346,15 +381,15 @@ using <a href='mmkin.html'>mmkin</a>.</p> <span class='co'># four minutes</span> <span class='va'>f_saem_sfo_sfo</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:42:02 2021" +#> [1] "Tue Jul 27 16:31:24 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:07 2021"</div><div class='input'><span class='va'>f_saem_dfop_sfo</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> +#> [1] "Tue Jul 27 16:31:29 2021"</div><div class='input'><span class='va'>f_saem_dfop_sfo</span> <span class='op'><-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:42:08 2021" +#> [1] "Tue Jul 27 16:31:30 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:17 2021"</div><div class='input'><span class='co'># We can use print, plot and summary methods to check the results</span> +#> [1] "Tue Jul 27 16:31:38 2021"</div><div class='input'><span class='co'># We can use print, plot and summary methods to check the results</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span><span class='op'>)</span> </div><div class='output co'>#> Kinetic nonlinear mixed-effects model fit by SAEM #> Structural model: @@ -370,35 +405,35 @@ using <a href='mmkin.html'>mmkin</a>.</p> #> #> Likelihood computed by importance sampling #> AIC BIC logLik -#> 841.6 836.5 -407.8 +#> 839.6 834.6 -406.8 #> #> Fitted parameters: #> estimate lower upper -#> parent_0 93.76647 91.15312 96.3798 -#> log_k_A1 -6.13235 -8.45788 -3.8068 -#> f_parent_qlogis -0.97364 -1.36940 -0.5779 -#> log_k1 -2.53176 -3.80372 -1.2598 -#> log_k2 -3.58667 -5.29524 -1.8781 -#> g_qlogis 0.01238 -1.07968 1.1044 -#> Var.parent_0 7.61106 -3.34955 18.5717 -#> Var.log_k_A1 4.64679 -2.73133 12.0249 -#> Var.f_parent_qlogis 0.19693 -0.05498 0.4488 -#> Var.log_k1 2.01717 -0.51980 4.5542 -#> Var.log_k2 3.63412 -0.92964 8.1979 -#> Var.g_qlogis 0.20045 -0.97425 1.3751 -#> a.1 1.88335 1.66636 2.1004 -#> SD.parent_0 2.75881 0.77234 4.7453 -#> SD.log_k_A1 2.15564 0.44429 3.8670 -#> SD.f_parent_qlogis 0.44377 0.15994 0.7276 -#> SD.log_k1 1.42027 0.52714 2.3134 -#> SD.log_k2 1.90634 0.70934 3.1033 -#> SD.g_qlogis 0.44771 -0.86417 1.7596</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span><span class='op'>)</span> +#> parent_0 93.80521 91.22487 96.3856 +#> log_k_A1 -6.06244 -8.26517 -3.8597 +#> f_parent_qlogis -0.97319 -1.37024 -0.5761 +#> log_k1 -2.55394 -4.00815 -1.0997 +#> log_k2 -3.47160 -5.18763 -1.7556 +#> g_qlogis -0.09324 -1.42737 1.2409 +#> Var.parent_0 7.42157 -3.25683 18.1000 +#> Var.log_k_A1 4.22850 -2.46339 10.9204 +#> Var.f_parent_qlogis 0.19803 -0.05541 0.4515 +#> Var.log_k1 2.28644 -0.86079 5.4337 +#> Var.log_k2 3.35626 -1.14639 7.8589 +#> Var.g_qlogis 0.20084 -1.32516 1.7268 +#> a.1 1.88399 1.66794 2.1000 +#> SD.parent_0 2.72425 0.76438 4.6841 +#> SD.log_k_A1 2.05633 0.42919 3.6835 +#> SD.f_parent_qlogis 0.44501 0.16025 0.7298 +#> SD.log_k1 1.51210 0.47142 2.5528 +#> SD.log_k2 1.83201 0.60313 3.0609 +#> SD.g_qlogis 0.44816 -1.25437 2.1507</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span><span class='op'>)</span> </div><div class='img'><img src='saem-5.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> saemix version used for fitting: 3.1.9000 -#> mkin version used for pre-fitting: 0.9.50.4 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Jan 25 14:42:18 2021 -#> Date of summary: Mon Jan 25 14:42:18 2021 +#> mkin version used for pre-fitting: 1.1.0 +#> R version used for fitting: 4.1.0 +#> Date of fit: Tue Jul 27 16:31:39 2021 +#> Date of summary: Tue Jul 27 16:31:39 2021 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -413,13 +448,13 @@ using <a href='mmkin.html'>mmkin</a>.</p> #> #> Model predictions using solution type analytical #> -#> Fitted in 9.954 s using 300, 100 iterations +#> Fitted in 9.479 s using 300, 100 iterations #> #> Variance model: Constant variance #> #> Mean of starting values for individual parameters: #> parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 -#> 93.8102 -9.7647 -0.9711 -1.8799 -4.2708 +#> 93.8102 -5.3734 -0.9711 -1.8799 -4.2708 #> g_qlogis #> 0.1356 #> @@ -430,46 +465,46 @@ using <a href='mmkin.html'>mmkin</a>.</p> #> #> Likelihood computed by importance sampling #> AIC BIC logLik -#> 841.6 836.5 -407.8 +#> 839.6 834.6 -406.8 #> #> Optimised parameters: #> est. lower upper -#> parent_0 93.76647 91.153 96.3798 -#> log_k_A1 -6.13235 -8.458 -3.8068 -#> f_parent_qlogis -0.97364 -1.369 -0.5779 -#> log_k1 -2.53176 -3.804 -1.2598 -#> log_k2 -3.58667 -5.295 -1.8781 -#> g_qlogis 0.01238 -1.080 1.1044 +#> parent_0 93.80521 91.225 96.3856 +#> log_k_A1 -6.06244 -8.265 -3.8597 +#> f_parent_qlogis -0.97319 -1.370 -0.5761 +#> log_k1 -2.55394 -4.008 -1.0997 +#> log_k2 -3.47160 -5.188 -1.7556 +#> g_qlogis -0.09324 -1.427 1.2409 #> #> Correlation: #> prnt_0 lg__A1 f_prn_ log_k1 log_k2 -#> log_k_A1 -0.013 -#> f_parent_qlogis -0.025 0.050 -#> log_k1 0.030 0.000 -0.005 -#> log_k2 0.010 0.005 -0.003 0.032 -#> g_qlogis -0.063 -0.015 0.010 -0.167 -0.177 +#> log_k_A1 -0.014 +#> f_parent_qlogis -0.025 0.054 +#> log_k1 0.027 -0.003 -0.005 +#> log_k2 0.011 0.005 -0.002 -0.070 +#> g_qlogis -0.067 -0.009 0.011 -0.189 -0.171 #> #> Random effects: #> est. lower upper -#> SD.parent_0 2.7588 0.7723 4.7453 -#> SD.log_k_A1 2.1556 0.4443 3.8670 -#> SD.f_parent_qlogis 0.4438 0.1599 0.7276 -#> SD.log_k1 1.4203 0.5271 2.3134 -#> SD.log_k2 1.9063 0.7093 3.1033 -#> SD.g_qlogis 0.4477 -0.8642 1.7596 +#> SD.parent_0 2.7243 0.7644 4.6841 +#> SD.log_k_A1 2.0563 0.4292 3.6835 +#> SD.f_parent_qlogis 0.4450 0.1602 0.7298 +#> SD.log_k1 1.5121 0.4714 2.5528 +#> SD.log_k2 1.8320 0.6031 3.0609 +#> SD.g_qlogis 0.4482 -1.2544 2.1507 #> #> Variance model: #> est. lower upper -#> a.1 1.883 1.666 2.1 +#> a.1 1.884 1.668 2.1 #> #> Backtransformed parameters: #> est. lower upper -#> parent_0 93.766473 9.115e+01 96.37983 -#> k_A1 0.002171 2.122e-04 0.02222 -#> f_parent_to_A1 0.274156 2.027e-01 0.35942 -#> k1 0.079519 2.229e-02 0.28371 -#> k2 0.027691 5.015e-03 0.15288 -#> g 0.503095 2.536e-01 0.75109 +#> parent_0 93.805214 9.122e+01 96.38556 +#> k_A1 0.002329 2.573e-04 0.02107 +#> f_parent_to_A1 0.274245 2.026e-01 0.35982 +#> k1 0.077775 1.817e-02 0.33296 +#> k2 0.031067 5.585e-03 0.17281 +#> g 0.476707 1.935e-01 0.77572 #> #> Resulting formation fractions: #> ff @@ -477,182 +512,182 @@ using <a href='mmkin.html'>mmkin</a>.</p> #> parent_sink 0.7258 #> #> Estimated disappearance times: -#> DT50 DT90 DT50back DT50_k1 DT50_k2 -#> parent 14.11 59.53 17.92 8.717 25.03 -#> A1 319.21 1060.38 NA NA NA +#> DT50 DT90 DT50back DT50_k1 DT50_k2 +#> parent 13.96 55.4 16.68 8.912 22.31 +#> A1 297.65 988.8 NA NA NA #> #> Data: -#> ds name time observed predicted residual std standardized -#> Dataset 6 parent 0 97.2 95.79523 -1.40477 1.883 -0.745888 -#> Dataset 6 parent 0 96.4 95.79523 -0.60477 1.883 -0.321114 -#> Dataset 6 parent 3 71.1 71.32042 0.22042 1.883 0.117035 -#> Dataset 6 parent 3 69.2 71.32042 2.12042 1.883 1.125873 -#> Dataset 6 parent 6 58.1 56.45256 -1.64744 1.883 -0.874739 -#> Dataset 6 parent 6 56.6 56.45256 -0.14744 1.883 -0.078288 -#> Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045256 -#> Dataset 6 parent 10 43.4 44.48523 1.08523 1.883 0.576224 -#> Dataset 6 parent 20 33.3 29.75774 -3.54226 1.883 -1.880826 -#> Dataset 6 parent 20 29.2 29.75774 0.55774 1.883 0.296141 -#> Dataset 6 parent 34 17.6 19.35710 1.75710 1.883 0.932966 -#> Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720578 -#> Dataset 6 parent 55 10.5 10.48443 -0.01557 1.883 -0.008266 -#> Dataset 6 parent 55 9.3 10.48443 1.18443 1.883 0.628895 -#> Dataset 6 parent 90 4.5 3.78622 -0.71378 1.883 -0.378995 -#> Dataset 6 parent 90 4.7 3.78622 -0.91378 1.883 -0.485188 -#> Dataset 6 parent 112 3.0 1.99608 -1.00392 1.883 -0.533048 -#> Dataset 6 parent 112 3.4 1.99608 -1.40392 1.883 -0.745435 -#> Dataset 6 parent 132 2.3 1.11539 -1.18461 1.883 -0.628990 -#> Dataset 6 parent 132 2.7 1.11539 -1.58461 1.883 -0.841377 -#> Dataset 6 A1 3 4.3 4.66132 0.36132 1.883 0.191849 -#> Dataset 6 A1 3 4.6 4.66132 0.06132 1.883 0.032559 -#> Dataset 6 A1 6 7.0 7.41087 0.41087 1.883 0.218157 -#> Dataset 6 A1 6 7.2 7.41087 0.21087 1.883 0.111964 -#> Dataset 6 A1 10 8.2 9.50878 1.30878 1.883 0.694921 -#> Dataset 6 A1 10 8.0 9.50878 1.50878 1.883 0.801114 -#> Dataset 6 A1 20 11.0 11.69902 0.69902 1.883 0.371157 -#> Dataset 6 A1 20 13.7 11.69902 -2.00098 1.883 -1.062455 -#> Dataset 6 A1 34 11.5 12.67784 1.17784 1.883 0.625396 -#> Dataset 6 A1 34 12.7 12.67784 -0.02216 1.883 -0.011765 -#> Dataset 6 A1 55 14.9 12.78556 -2.11444 1.883 -1.122701 -#> Dataset 6 A1 55 14.5 12.78556 -1.71444 1.883 -0.910314 -#> Dataset 6 A1 90 12.1 11.52954 -0.57046 1.883 -0.302898 -#> Dataset 6 A1 90 12.3 11.52954 -0.77046 1.883 -0.409092 -#> Dataset 6 A1 112 9.9 10.43825 0.53825 1.883 0.285793 -#> Dataset 6 A1 112 10.2 10.43825 0.23825 1.883 0.126503 -#> Dataset 6 A1 132 8.8 9.42830 0.62830 1.883 0.333609 -#> Dataset 6 A1 132 7.8 9.42830 1.62830 1.883 0.864577 -#> Dataset 7 parent 0 93.6 90.91477 -2.68523 1.883 -1.425772 -#> Dataset 7 parent 0 92.3 90.91477 -1.38523 1.883 -0.735514 -#> Dataset 7 parent 3 87.0 84.76874 -2.23126 1.883 -1.184726 -#> Dataset 7 parent 3 82.2 84.76874 2.56874 1.883 1.363919 -#> Dataset 7 parent 7 74.0 77.62735 3.62735 1.883 1.926003 -#> Dataset 7 parent 7 73.9 77.62735 3.72735 1.883 1.979100 -#> Dataset 7 parent 14 64.2 67.52266 3.32266 1.883 1.764224 -#> Dataset 7 parent 14 69.5 67.52266 -1.97734 1.883 -1.049904 -#> Dataset 7 parent 30 54.0 52.41949 -1.58051 1.883 -0.839202 -#> Dataset 7 parent 30 54.6 52.41949 -2.18051 1.883 -1.157783 -#> Dataset 7 parent 60 41.1 39.36582 -1.73418 1.883 -0.920794 -#> Dataset 7 parent 60 38.4 39.36582 0.96582 1.883 0.512818 -#> Dataset 7 parent 90 32.5 33.75388 1.25388 1.883 0.665771 -#> Dataset 7 parent 90 35.5 33.75388 -1.74612 1.883 -0.927132 -#> Dataset 7 parent 120 28.1 30.41716 2.31716 1.883 1.230335 -#> Dataset 7 parent 120 29.0 30.41716 1.41716 1.883 0.752464 -#> Dataset 7 parent 180 26.5 25.66046 -0.83954 1.883 -0.445767 -#> Dataset 7 parent 180 27.6 25.66046 -1.93954 1.883 -1.029832 -#> Dataset 7 A1 3 3.9 2.69355 -1.20645 1.883 -0.640585 -#> Dataset 7 A1 3 3.1 2.69355 -0.40645 1.883 -0.215811 -#> Dataset 7 A1 7 6.9 5.81807 -1.08193 1.883 -0.574470 -#> Dataset 7 A1 7 6.6 5.81807 -0.78193 1.883 -0.415180 -#> Dataset 7 A1 14 10.4 10.22529 -0.17471 1.883 -0.092767 -#> Dataset 7 A1 14 8.3 10.22529 1.92529 1.883 1.022265 -#> Dataset 7 A1 30 14.4 16.75484 2.35484 1.883 1.250345 -#> Dataset 7 A1 30 13.7 16.75484 3.05484 1.883 1.622022 -#> Dataset 7 A1 60 22.1 22.22540 0.12540 1.883 0.066583 -#> Dataset 7 A1 60 22.3 22.22540 -0.07460 1.883 -0.039610 -#> Dataset 7 A1 90 27.5 24.38799 -3.11201 1.883 -1.652376 -#> Dataset 7 A1 90 25.4 24.38799 -1.01201 1.883 -0.537344 -#> Dataset 7 A1 120 28.0 25.53294 -2.46706 1.883 -1.309927 -#> Dataset 7 A1 120 26.6 25.53294 -1.06706 1.883 -0.566572 -#> Dataset 7 A1 180 25.8 26.94943 1.14943 1.883 0.610309 -#> Dataset 7 A1 180 25.3 26.94943 1.64943 1.883 0.875793 -#> Dataset 8 parent 0 91.9 91.53246 -0.36754 1.883 -0.195151 -#> Dataset 8 parent 0 90.8 91.53246 0.73246 1.883 0.388914 -#> Dataset 8 parent 1 64.9 67.73197 2.83197 1.883 1.503686 -#> Dataset 8 parent 1 66.2 67.73197 1.53197 1.883 0.813428 -#> Dataset 8 parent 3 43.5 41.58448 -1.91552 1.883 -1.017081 -#> Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335661 -#> Dataset 8 parent 8 18.3 19.62286 1.32286 1.883 0.702395 -#> Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808589 -#> Dataset 8 parent 14 10.2 10.77819 0.57819 1.883 0.306999 -#> Dataset 8 parent 14 10.8 10.77819 -0.02181 1.883 -0.011582 -#> Dataset 8 parent 27 4.9 3.26977 -1.63023 1.883 -0.865599 -#> Dataset 8 parent 27 3.3 3.26977 -0.03023 1.883 -0.016051 -#> Dataset 8 parent 48 1.6 0.48024 -1.11976 1.883 -0.594557 -#> Dataset 8 parent 48 1.5 0.48024 -1.01976 1.883 -0.541460 -#> Dataset 8 parent 70 1.1 0.06438 -1.03562 1.883 -0.549881 -#> Dataset 8 parent 70 0.9 0.06438 -0.83562 1.883 -0.443688 -#> Dataset 8 A1 1 9.6 7.61539 -1.98461 1.883 -1.053761 -#> Dataset 8 A1 1 7.7 7.61539 -0.08461 1.883 -0.044923 -#> Dataset 8 A1 3 15.0 15.47954 0.47954 1.883 0.254622 -#> Dataset 8 A1 3 15.1 15.47954 0.37954 1.883 0.201525 -#> Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517076 -#> Dataset 8 A1 8 21.1 20.22616 -0.87384 1.883 -0.463979 -#> Dataset 8 A1 14 19.7 20.00067 0.30067 1.883 0.159645 -#> Dataset 8 A1 14 18.9 20.00067 1.10067 1.883 0.584419 -#> Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593929 -#> Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255619 -#> Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400123 -#> Dataset 8 A1 48 9.8 10.25357 0.45357 1.883 0.240833 -#> Dataset 8 A1 70 6.2 5.95728 -0.24272 1.883 -0.128878 -#> Dataset 8 A1 70 6.1 5.95728 -0.14272 1.883 -0.075781 -#> Dataset 9 parent 0 99.8 97.47274 -2.32726 1.883 -1.235697 -#> Dataset 9 parent 0 98.3 97.47274 -0.82726 1.883 -0.439246 -#> Dataset 9 parent 1 77.1 79.72257 2.62257 1.883 1.392500 -#> Dataset 9 parent 1 77.2 79.72257 2.52257 1.883 1.339404 -#> Dataset 9 parent 3 59.0 56.26497 -2.73503 1.883 -1.452212 -#> Dataset 9 parent 3 58.1 56.26497 -1.83503 1.883 -0.974342 -#> Dataset 9 parent 8 27.4 31.66985 4.26985 1.883 2.267151 -#> Dataset 9 parent 8 29.2 31.66985 2.46985 1.883 1.311410 -#> Dataset 9 parent 14 19.1 22.39789 3.29789 1.883 1.751071 -#> Dataset 9 parent 14 29.6 22.39789 -7.20211 1.883 -3.824090 -#> Dataset 9 parent 27 10.1 14.21758 4.11758 1.883 2.186301 -#> Dataset 9 parent 27 18.2 14.21758 -3.98242 1.883 -2.114537 -#> Dataset 9 parent 48 4.5 7.27921 2.77921 1.883 1.475671 -#> Dataset 9 parent 48 9.1 7.27921 -1.82079 1.883 -0.966780 -#> Dataset 9 parent 70 2.3 3.61470 1.31470 1.883 0.698065 -#> Dataset 9 parent 70 2.9 3.61470 0.71470 1.883 0.379485 -#> Dataset 9 parent 91 2.0 1.85303 -0.14697 1.883 -0.078038 -#> Dataset 9 parent 91 1.8 1.85303 0.05303 1.883 0.028155 -#> Dataset 9 parent 120 2.0 0.73645 -1.26355 1.883 -0.670906 -#> Dataset 9 parent 120 2.2 0.73645 -1.46355 1.883 -0.777099 -#> Dataset 9 A1 1 4.2 3.87843 -0.32157 1.883 -0.170743 -#> Dataset 9 A1 1 3.9 3.87843 -0.02157 1.883 -0.011453 -#> Dataset 9 A1 3 7.4 8.90535 1.50535 1.883 0.799291 -#> Dataset 9 A1 3 7.9 8.90535 1.00535 1.883 0.533807 -#> Dataset 9 A1 8 14.5 13.75172 -0.74828 1.883 -0.397312 -#> Dataset 9 A1 8 13.7 13.75172 0.05172 1.883 0.027462 -#> Dataset 9 A1 14 14.2 14.97541 0.77541 1.883 0.411715 -#> Dataset 9 A1 14 12.2 14.97541 2.77541 1.883 1.473650 -#> Dataset 9 A1 27 13.7 14.94728 1.24728 1.883 0.662266 -#> Dataset 9 A1 27 13.2 14.94728 1.74728 1.883 0.927750 -#> Dataset 9 A1 48 13.6 13.66078 0.06078 1.883 0.032272 -#> Dataset 9 A1 48 15.4 13.66078 -1.73922 1.883 -0.923470 -#> Dataset 9 A1 70 10.4 11.84899 1.44899 1.883 0.769365 -#> Dataset 9 A1 70 11.6 11.84899 0.24899 1.883 0.132204 -#> Dataset 9 A1 91 10.0 10.09177 0.09177 1.883 0.048727 -#> Dataset 9 A1 91 9.5 10.09177 0.59177 1.883 0.314211 -#> Dataset 9 A1 120 9.1 7.91379 -1.18621 1.883 -0.629841 -#> Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576745 -#> Dataset 10 parent 0 96.1 93.65257 -2.44743 1.883 -1.299505 -#> Dataset 10 parent 0 94.3 93.65257 -0.64743 1.883 -0.343763 -#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 -#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 -#> Dataset 10 parent 14 69.4 70.17143 0.77143 1.883 0.409606 -#> Dataset 10 parent 14 73.1 70.17143 -2.92857 1.883 -1.554974 -#> Dataset 10 parent 21 65.6 63.99188 -1.60812 1.883 -0.853862 -#> Dataset 10 parent 21 65.3 63.99188 -1.30812 1.883 -0.694572 -#> Dataset 10 parent 41 55.9 54.64292 -1.25708 1.883 -0.667467 -#> Dataset 10 parent 41 54.4 54.64292 0.24292 1.883 0.128985 -#> Dataset 10 parent 63 47.0 49.61303 2.61303 1.883 1.387433 -#> Dataset 10 parent 63 49.3 49.61303 0.31303 1.883 0.166207 -#> Dataset 10 parent 91 44.7 45.17807 0.47807 1.883 0.253839 -#> Dataset 10 parent 91 46.7 45.17807 -1.52193 1.883 -0.808096 -#> Dataset 10 parent 120 42.1 41.27970 -0.82030 1.883 -0.435552 -#> Dataset 10 parent 120 41.3 41.27970 -0.02030 1.883 -0.010778 -#> Dataset 10 A1 8 3.3 3.99294 0.69294 1.883 0.367929 -#> Dataset 10 A1 8 3.4 3.99294 0.59294 1.883 0.314832 -#> Dataset 10 A1 14 3.9 5.92756 2.02756 1.883 1.076570 -#> Dataset 10 A1 14 2.9 5.92756 3.02756 1.883 1.607538 -#> Dataset 10 A1 21 6.4 7.47313 1.07313 1.883 0.569799 -#> Dataset 10 A1 21 7.2 7.47313 0.27313 1.883 0.145025 -#> Dataset 10 A1 41 9.1 9.76819 0.66819 1.883 0.354786 -#> Dataset 10 A1 41 8.5 9.76819 1.26819 1.883 0.673367 -#> Dataset 10 A1 63 11.7 10.94733 -0.75267 1.883 -0.399643 -#> Dataset 10 A1 63 12.0 10.94733 -1.05267 1.883 -0.558933 -#> Dataset 10 A1 91 13.3 11.93773 -1.36227 1.883 -0.723321 -#> Dataset 10 A1 91 13.2 11.93773 -1.26227 1.883 -0.670224 -#> Dataset 10 A1 120 14.3 12.77666 -1.52334 1.883 -0.808847 -#> Dataset 10 A1 120 12.1 12.77666 0.67666 1.883 0.359282</div><div class='input'> +#> ds name time observed predicted residual std standardized +#> Dataset 6 parent 0 97.2 95.75408 1.445920 1.884 0.767479 +#> Dataset 6 parent 0 96.4 95.75408 0.645920 1.884 0.342847 +#> Dataset 6 parent 3 71.1 71.22466 -0.124662 1.884 -0.066169 +#> Dataset 6 parent 3 69.2 71.22466 -2.024662 1.884 -1.074669 +#> Dataset 6 parent 6 58.1 56.42290 1.677100 1.884 0.890187 +#> Dataset 6 parent 6 56.6 56.42290 0.177100 1.884 0.094003 +#> Dataset 6 parent 10 44.4 44.55255 -0.152554 1.884 -0.080974 +#> Dataset 6 parent 10 43.4 44.55255 -1.152554 1.884 -0.611763 +#> Dataset 6 parent 20 33.3 29.88846 3.411537 1.884 1.810807 +#> Dataset 6 parent 20 29.2 29.88846 -0.688463 1.884 -0.365429 +#> Dataset 6 parent 34 17.6 19.40826 -1.808260 1.884 -0.959805 +#> Dataset 6 parent 34 18.0 19.40826 -1.408260 1.884 -0.747489 +#> Dataset 6 parent 55 10.5 10.45560 0.044398 1.884 0.023566 +#> Dataset 6 parent 55 9.3 10.45560 -1.155602 1.884 -0.613381 +#> Dataset 6 parent 90 4.5 3.74026 0.759744 1.884 0.403264 +#> Dataset 6 parent 90 4.7 3.74026 0.959744 1.884 0.509421 +#> Dataset 6 parent 112 3.0 1.96015 1.039853 1.884 0.551943 +#> Dataset 6 parent 112 3.4 1.96015 1.439853 1.884 0.764258 +#> Dataset 6 parent 132 2.3 1.08940 1.210603 1.884 0.642575 +#> Dataset 6 parent 132 2.7 1.08940 1.610603 1.884 0.854890 +#> Dataset 6 A1 3 4.3 4.75601 -0.456009 1.884 -0.242045 +#> Dataset 6 A1 3 4.6 4.75601 -0.156009 1.884 -0.082808 +#> Dataset 6 A1 6 7.0 7.53839 -0.538391 1.884 -0.285772 +#> Dataset 6 A1 6 7.2 7.53839 -0.338391 1.884 -0.179614 +#> Dataset 6 A1 10 8.2 9.64728 -1.447276 1.884 -0.768198 +#> Dataset 6 A1 10 8.0 9.64728 -1.647276 1.884 -0.874356 +#> Dataset 6 A1 20 11.0 11.83954 -0.839545 1.884 -0.445621 +#> Dataset 6 A1 20 13.7 11.83954 1.860455 1.884 0.987509 +#> Dataset 6 A1 34 11.5 12.81233 -1.312327 1.884 -0.696569 +#> Dataset 6 A1 34 12.7 12.81233 -0.112327 1.884 -0.059622 +#> Dataset 6 A1 55 14.9 12.87919 2.020809 1.884 1.072624 +#> Dataset 6 A1 55 14.5 12.87919 1.620809 1.884 0.860308 +#> Dataset 6 A1 90 12.1 11.52464 0.575364 1.884 0.305397 +#> Dataset 6 A1 90 12.3 11.52464 0.775364 1.884 0.411555 +#> Dataset 6 A1 112 9.9 10.37694 -0.476938 1.884 -0.253153 +#> Dataset 6 A1 112 10.2 10.37694 -0.176938 1.884 -0.093917 +#> Dataset 6 A1 132 8.8 9.32474 -0.524742 1.884 -0.278528 +#> Dataset 6 A1 132 7.8 9.32474 -1.524742 1.884 -0.809317 +#> Dataset 7 parent 0 93.6 90.16918 3.430816 1.884 1.821040 +#> Dataset 7 parent 0 92.3 90.16918 2.130816 1.884 1.131014 +#> Dataset 7 parent 3 87.0 84.05442 2.945583 1.884 1.563483 +#> Dataset 7 parent 3 82.2 84.05442 -1.854417 1.884 -0.984304 +#> Dataset 7 parent 7 74.0 77.00960 -3.009596 1.884 -1.597461 +#> Dataset 7 parent 7 73.9 77.00960 -3.109596 1.884 -1.650540 +#> Dataset 7 parent 14 64.2 67.15684 -2.956840 1.884 -1.569459 +#> Dataset 7 parent 14 69.5 67.15684 2.343160 1.884 1.243724 +#> Dataset 7 parent 30 54.0 52.66290 1.337101 1.884 0.709719 +#> Dataset 7 parent 30 54.6 52.66290 1.937101 1.884 1.028192 +#> Dataset 7 parent 60 41.1 40.04995 1.050050 1.884 0.557355 +#> Dataset 7 parent 60 38.4 40.04995 -1.649950 1.884 -0.875775 +#> Dataset 7 parent 90 32.5 34.09675 -1.596746 1.884 -0.847535 +#> Dataset 7 parent 90 35.5 34.09675 1.403254 1.884 0.744832 +#> Dataset 7 parent 120 28.1 30.12281 -2.022814 1.884 -1.073688 +#> Dataset 7 parent 120 29.0 30.12281 -1.122814 1.884 -0.595977 +#> Dataset 7 parent 180 26.5 24.10888 2.391123 1.884 1.269182 +#> Dataset 7 parent 180 27.6 24.10888 3.491123 1.884 1.853050 +#> Dataset 7 A1 3 3.9 2.77684 1.123161 1.884 0.596161 +#> Dataset 7 A1 3 3.1 2.77684 0.323161 1.884 0.171530 +#> Dataset 7 A1 7 6.9 5.96705 0.932950 1.884 0.495200 +#> Dataset 7 A1 7 6.6 5.96705 0.632950 1.884 0.335963 +#> Dataset 7 A1 14 10.4 10.40535 -0.005348 1.884 -0.002839 +#> Dataset 7 A1 14 8.3 10.40535 -2.105348 1.884 -1.117496 +#> Dataset 7 A1 30 14.4 16.83722 -2.437216 1.884 -1.293648 +#> Dataset 7 A1 30 13.7 16.83722 -3.137216 1.884 -1.665200 +#> Dataset 7 A1 60 22.1 22.15018 -0.050179 1.884 -0.026635 +#> Dataset 7 A1 60 22.3 22.15018 0.149821 1.884 0.079523 +#> Dataset 7 A1 90 27.5 24.36286 3.137143 1.884 1.665161 +#> Dataset 7 A1 90 25.4 24.36286 1.037143 1.884 0.550504 +#> Dataset 7 A1 120 28.0 25.64064 2.359361 1.884 1.252323 +#> Dataset 7 A1 120 26.6 25.64064 0.959361 1.884 0.509218 +#> Dataset 7 A1 180 25.8 27.25486 -1.454858 1.884 -0.772223 +#> Dataset 7 A1 180 25.3 27.25486 -1.954858 1.884 -1.037617 +#> Dataset 8 parent 0 91.9 91.72652 0.173479 1.884 0.092081 +#> Dataset 8 parent 0 90.8 91.72652 -0.926521 1.884 -0.491787 +#> Dataset 8 parent 1 64.9 67.22810 -2.328104 1.884 -1.235732 +#> Dataset 8 parent 1 66.2 67.22810 -1.028104 1.884 -0.545706 +#> Dataset 8 parent 3 43.5 41.46375 2.036251 1.884 1.080820 +#> Dataset 8 parent 3 44.1 41.46375 2.636251 1.884 1.399293 +#> Dataset 8 parent 8 18.3 19.83597 -1.535968 1.884 -0.815275 +#> Dataset 8 parent 8 18.1 19.83597 -1.735968 1.884 -0.921433 +#> Dataset 8 parent 14 10.2 10.34793 -0.147927 1.884 -0.078518 +#> Dataset 8 parent 14 10.8 10.34793 0.452073 1.884 0.239956 +#> Dataset 8 parent 27 4.9 2.67641 2.223595 1.884 1.180260 +#> Dataset 8 parent 27 3.3 2.67641 0.623595 1.884 0.330997 +#> Dataset 8 parent 48 1.6 0.30218 1.297822 1.884 0.688870 +#> Dataset 8 parent 48 1.5 0.30218 1.197822 1.884 0.635791 +#> Dataset 8 parent 70 1.1 0.03075 1.069248 1.884 0.567545 +#> Dataset 8 parent 70 0.9 0.03075 0.869248 1.884 0.461388 +#> Dataset 8 A1 1 9.6 7.74066 1.859342 1.884 0.986918 +#> Dataset 8 A1 1 7.7 7.74066 -0.040658 1.884 -0.021581 +#> Dataset 8 A1 3 15.0 15.37549 -0.375495 1.884 -0.199309 +#> Dataset 8 A1 3 15.1 15.37549 -0.275495 1.884 -0.146230 +#> Dataset 8 A1 8 21.2 19.95900 1.241003 1.884 0.658711 +#> Dataset 8 A1 8 21.1 19.95900 1.141003 1.884 0.605632 +#> Dataset 8 A1 14 19.7 19.92898 -0.228978 1.884 -0.121539 +#> Dataset 8 A1 14 18.9 19.92898 -1.028978 1.884 -0.546170 +#> Dataset 8 A1 27 17.5 16.34046 1.159536 1.884 0.615469 +#> Dataset 8 A1 27 15.9 16.34046 -0.440464 1.884 -0.233793 +#> Dataset 8 A1 48 9.5 10.12131 -0.621313 1.884 -0.329786 +#> Dataset 8 A1 48 9.8 10.12131 -0.321313 1.884 -0.170550 +#> Dataset 8 A1 70 6.2 5.84753 0.352469 1.884 0.187087 +#> Dataset 8 A1 70 6.1 5.84753 0.252469 1.884 0.134008 +#> Dataset 9 parent 0 99.8 98.23600 1.564002 1.884 0.830155 +#> Dataset 9 parent 0 98.3 98.23600 0.064002 1.884 0.033972 +#> Dataset 9 parent 1 77.1 79.68007 -2.580074 1.884 -1.369475 +#> Dataset 9 parent 1 77.2 79.68007 -2.480074 1.884 -1.316396 +#> Dataset 9 parent 3 59.0 55.81142 3.188584 1.884 1.692465 +#> Dataset 9 parent 3 58.1 55.81142 2.288584 1.884 1.214755 +#> Dataset 9 parent 8 27.4 31.81995 -4.419948 1.884 -2.346060 +#> Dataset 9 parent 8 29.2 31.81995 -2.619948 1.884 -1.390640 +#> Dataset 9 parent 14 19.1 22.78328 -3.683282 1.884 -1.955046 +#> Dataset 9 parent 14 29.6 22.78328 6.816718 1.884 3.618240 +#> Dataset 9 parent 27 10.1 14.15172 -4.051720 1.884 -2.150609 +#> Dataset 9 parent 27 18.2 14.15172 4.048280 1.884 2.148783 +#> Dataset 9 parent 48 4.5 6.86094 -2.360941 1.884 -1.253162 +#> Dataset 9 parent 48 9.1 6.86094 2.239059 1.884 1.188468 +#> Dataset 9 parent 70 2.3 3.21580 -0.915798 1.884 -0.486096 +#> Dataset 9 parent 70 2.9 3.21580 -0.315798 1.884 -0.167622 +#> Dataset 9 parent 91 2.0 1.56010 0.439897 1.884 0.233492 +#> Dataset 9 parent 91 1.8 1.56010 0.239897 1.884 0.127335 +#> Dataset 9 parent 120 2.0 0.57458 1.425424 1.884 0.756600 +#> Dataset 9 parent 120 2.2 0.57458 1.625424 1.884 0.862757 +#> Dataset 9 A1 1 4.2 4.01796 0.182037 1.884 0.096623 +#> Dataset 9 A1 1 3.9 4.01796 -0.117963 1.884 -0.062613 +#> Dataset 9 A1 3 7.4 9.08527 -1.685270 1.884 -0.894523 +#> Dataset 9 A1 3 7.9 9.08527 -1.185270 1.884 -0.629129 +#> Dataset 9 A1 8 14.5 13.75054 0.749457 1.884 0.397804 +#> Dataset 9 A1 8 13.7 13.75054 -0.050543 1.884 -0.026827 +#> Dataset 9 A1 14 14.2 14.91180 -0.711804 1.884 -0.377818 +#> Dataset 9 A1 14 12.2 14.91180 -2.711804 1.884 -1.439396 +#> Dataset 9 A1 27 13.7 14.97813 -1.278129 1.884 -0.678417 +#> Dataset 9 A1 27 13.2 14.97813 -1.778129 1.884 -0.943812 +#> Dataset 9 A1 48 13.6 13.75574 -0.155745 1.884 -0.082668 +#> Dataset 9 A1 48 15.4 13.75574 1.644255 1.884 0.872753 +#> Dataset 9 A1 70 10.4 11.92861 -1.528608 1.884 -0.811369 +#> Dataset 9 A1 70 11.6 11.92861 -0.328608 1.884 -0.174422 +#> Dataset 9 A1 91 10.0 10.14395 -0.143947 1.884 -0.076405 +#> Dataset 9 A1 91 9.5 10.14395 -0.643947 1.884 -0.341800 +#> Dataset 9 A1 120 9.1 7.93869 1.161307 1.884 0.616409 +#> Dataset 9 A1 120 9.0 7.93869 1.061307 1.884 0.563330 +#> Dataset 10 parent 0 96.1 93.65914 2.440862 1.884 1.295583 +#> Dataset 10 parent 0 94.3 93.65914 0.640862 1.884 0.340163 +#> Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344 +#> Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344 +#> Dataset 10 parent 14 69.4 70.15862 -0.758619 1.884 -0.402667 +#> Dataset 10 parent 14 73.1 70.15862 2.941381 1.884 1.561253 +#> Dataset 10 parent 21 65.6 64.00840 1.591600 1.884 0.844804 +#> Dataset 10 parent 21 65.3 64.00840 1.291600 1.884 0.685567 +#> Dataset 10 parent 41 55.9 54.71192 1.188076 1.884 0.630618 +#> Dataset 10 parent 41 54.4 54.71192 -0.311924 1.884 -0.165566 +#> Dataset 10 parent 63 47.0 49.66775 -2.667747 1.884 -1.416011 +#> Dataset 10 parent 63 49.3 49.66775 -0.367747 1.884 -0.195196 +#> Dataset 10 parent 91 44.7 45.17119 -0.471186 1.884 -0.250101 +#> Dataset 10 parent 91 46.7 45.17119 1.528814 1.884 0.811478 +#> Dataset 10 parent 120 42.1 41.20430 0.895699 1.884 0.475427 +#> Dataset 10 parent 120 41.3 41.20430 0.095699 1.884 0.050796 +#> Dataset 10 A1 8 3.3 4.00920 -0.709204 1.884 -0.376438 +#> Dataset 10 A1 8 3.4 4.00920 -0.609204 1.884 -0.323359 +#> Dataset 10 A1 14 3.9 5.94267 -2.042668 1.884 -1.084226 +#> Dataset 10 A1 14 2.9 5.94267 -3.042668 1.884 -1.615015 +#> Dataset 10 A1 21 6.4 7.48222 -1.082219 1.884 -0.574430 +#> Dataset 10 A1 21 7.2 7.48222 -0.282219 1.884 -0.149799 +#> Dataset 10 A1 41 9.1 9.76246 -0.662460 1.884 -0.351626 +#> Dataset 10 A1 41 8.5 9.76246 -1.262460 1.884 -0.670100 +#> Dataset 10 A1 63 11.7 10.93972 0.760278 1.884 0.403547 +#> Dataset 10 A1 63 12.0 10.93972 1.060278 1.884 0.562784 +#> Dataset 10 A1 91 13.3 11.93666 1.363337 1.884 0.723645 +#> Dataset 10 A1 91 13.2 11.93666 1.263337 1.884 0.670566 +#> Dataset 10 A1 120 14.3 12.78218 1.517817 1.884 0.805641 +#> Dataset 10 A1 120 12.1 12.78218 -0.682183 1.884 -0.362095</div><div class='input'> <span class='co'># The following takes about 6 minutes</span> <span class='co'>#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span> <span class='co'># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span> diff --git a/docs/dev/reference/schaefer07_complex_case-1.png b/docs/dev/reference/schaefer07_complex_case-1.png Binary files differindex 16e657dd..96aab2dc 100644 --- a/docs/dev/reference/schaefer07_complex_case-1.png +++ b/docs/dev/reference/schaefer07_complex_case-1.png diff --git a/docs/dev/reference/schaefer07_complex_case.html b/docs/dev/reference/schaefer07_complex_case.html index 83555b99..4ccad5c4 100644 --- a/docs/dev/reference/schaefer07_complex_case.html +++ b/docs/dev/reference/schaefer07_complex_case.html @@ -74,7 +74,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -123,7 +123,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -186,15 +186,15 @@ </div><div class='img'><img src='schaefer07_complex_case-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> parent_A1 parent_B1 parent_C1 parent_sink A1_A2 A1_sink -#> 0.3809620 0.1954665 0.4235715 0.0000000 0.4479662 0.5520338 +#> 0.3809620 0.1954667 0.4235713 0.0000000 0.4479619 0.5520381 #> #> $distimes #> DT50 DT90 #> parent 13.95078 46.34350 -#> A1 49.75343 165.27731 -#> B1 37.26912 123.80533 -#> C1 11.23131 37.30959 -#> A2 28.50569 94.69386 +#> A1 49.75342 165.27728 +#> B1 37.26908 123.80520 +#> C1 11.23131 37.30961 +#> A2 28.50624 94.69567 #> </div><div class='input'> <span class='co'># }</span> <span class='co'># Compare with the results obtained in the original publication</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>schaefer07_complex_results</span><span class='op'>)</span> diff --git a/docs/dev/reference/sigma_twocomp-1.png b/docs/dev/reference/sigma_twocomp-1.png Binary files differindex 21db3145..6e61684e 100644 --- a/docs/dev/reference/sigma_twocomp-1.png +++ b/docs/dev/reference/sigma_twocomp-1.png diff --git a/docs/dev/reference/sigma_twocomp.html b/docs/dev/reference/sigma_twocomp.html index 8212e480..b7d295b2 100644 --- a/docs/dev/reference/sigma_twocomp.html +++ b/docs/dev/reference/sigma_twocomp.html @@ -73,7 +73,7 @@ dependence of the measured value \(y\):" /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ dependence of the measured value \(y\):" /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -188,6 +188,10 @@ Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry 24(11), 1895-1898.</p> <p>Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p> +<p>Ranke J and Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical +Degradation Data. <em>Environments</em> 6(12) 124 +doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6120124</a> +.</p> <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'><span class='va'>times</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span><span class='op'>)</span> diff --git a/docs/dev/reference/summary.mkinfit.html b/docs/dev/reference/summary.mkinfit.html index f314dfa8..494731e9 100644 --- a/docs/dev/reference/summary.mkinfit.html +++ b/docs/dev/reference/summary.mkinfit.html @@ -76,7 +76,7 @@ values." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ values." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -236,17 +236,17 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span>, <span class='va'>FOCUS_2006_A</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> mkin version used for fitting: 0.9.50.4 +</div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Nov 30 16:01:20 2020 -#> Date of summary: Mon Nov 30 16:01:20 2020 +#> Date of fit: Mon Feb 15 17:13:09 2021 +#> Date of summary: Mon Feb 15 17:13:09 2021 #> #> Equations: #> d_parent/dt = - k_parent * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.028 s +#> Fitted using 131 model solutions performed in 0.027 s #> #> Error model: Constant variance #> diff --git a/docs/dev/reference/summary.nlme.mmkin.html b/docs/dev/reference/summary.nlme.mmkin.html index 2aeadc46..b2f6624a 100644 --- a/docs/dev/reference/summary.nlme.mmkin.html +++ b/docs/dev/reference/summary.nlme.mmkin.html @@ -76,7 +76,7 @@ endpoints such as formation fractions and DT50 values. Optionally </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -125,7 +125,7 @@ endpoints such as formation fractions and DT50 values. Optionally <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -263,12 +263,12 @@ José Pinheiro and Douglas Bates for the components inherited from nlme</p> <span class='va'>f_mmkin</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>ds_sfo_syn</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span> </div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> #> <span class='warning'>iteration limit reached without convergence (10)</span></div><div class='input'><span class='va'>f_nlme</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Iteration 1, LME step: nlminb() did not converge (code = 1). Do increase 'msMaxIter'!</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_nlme</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> nlme version used for fitting: 3.1.150.1 -#> mkin version used for pre-fitting: 0.9.50.4 +</div><div class='output co'>#> <span class='warning'>Warning: Iteration 4, LME step: nlminb() did not converge (code = 1). PORT message: false convergence (8)</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_nlme</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +</div><div class='output co'>#> nlme version used for fitting: 3.1.152 +#> mkin version used for pre-fitting: 1.0.3.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Nov 30 16:01:23 2020 -#> Date of summary: Mon Nov 30 16:01:23 2020 +#> Date of fit: Mon Feb 15 17:13:12 2021 +#> Date of summary: Mon Feb 15 17:13:12 2021 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -278,148 +278,146 @@ José Pinheiro and Douglas Bates for the components inherited from nlme</p> #> #> Model predictions using solution type analytical #> -#> Fitted in 0.996 s using 6 iterations +#> Fitted in 0.544 s using 4 iterations #> #> Variance model: Two-component variance function #> #> Mean of starting values for individual parameters: #> parent_0 log_k_parent -#> 101.568773 -4.454103 +#> 101.569 -4.454 #> #> Fixed degradation parameter values: #> None #> #> Results: #> -#> AIC BIC logLik -#> 586.4159 603.9145 -286.2079 +#> AIC BIC logLik +#> 584.5 599.5 -286.2 #> #> Optimised, transformed parameters with symmetric confidence intervals: #> lower est. upper -#> parent_0 99.360 101.593 103.825 -#> log_k_parent -4.979 -4.451 -3.924 +#> parent_0 99.371 101.592 103.814 +#> log_k_parent -4.973 -4.449 -3.926 #> #> Correlation: #> prnt_0 -#> log_k_parent 0.155 +#> log_k_parent 0.051 #> #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent ~ 1) #> Level: ds -#> Structure: General positive-definite, Log-Cholesky parametrization -#> StdDev Corr -#> parent_0 0.2624248 prnt_0 -#> log_k_parent 0.5907146 0.999 -#> Residual 1.0000000 +#> Structure: Diagonal +#> parent_0 log_k_parent Residual +#> StdDev: 6.924e-05 0.5863 1 #> #> Variance function: #> Structure: Constant plus proportion of variance covariate #> Formula: ~fitted(.) #> Parameter estimates: -#> const prop -#> 6.56706e-24 7.89583e-02 +#> const prop +#> 0.0001208853 0.0789968036 #> #> Backtransformed parameters with asymmetric confidence intervals: #> lower est. upper -#> parent_0 99.360213 101.59280 103.82539 -#> k_parent 0.006883 0.01166 0.01976 +#> parent_0 99.370882 101.59243 103.81398 +#> k_parent 0.006923 0.01168 0.01972 #> #> Estimated disappearance times: #> DT50 DT90 -#> parent 59.44 197.4 +#> parent 59.32 197.1 #> #> Data: #> ds name time observed predicted residual std standardized -#> ds 1 parent 0 104.1 101.417 2.68283 8.0077 0.335030 -#> ds 1 parent 0 105.0 101.417 3.58283 8.0077 0.447422 -#> ds 1 parent 1 98.5 100.624 -2.12400 7.9451 -0.267334 -#> ds 1 parent 1 96.1 100.624 -4.52400 7.9451 -0.569407 -#> ds 1 parent 3 101.9 99.056 2.84379 7.8213 0.363595 -#> ds 1 parent 3 85.2 99.056 -13.85621 7.8213 -1.771597 -#> ds 1 parent 7 99.1 95.994 3.10646 7.5795 0.409850 -#> ds 1 parent 7 93.0 95.994 -2.99354 7.5795 -0.394953 -#> ds 1 parent 14 88.1 90.860 -2.75997 7.1741 -0.384710 -#> ds 1 parent 14 84.1 90.860 -6.75997 7.1741 -0.942268 -#> ds 1 parent 28 80.2 81.402 -1.20174 6.4273 -0.186973 -#> ds 1 parent 28 91.3 81.402 9.89826 6.4273 1.540024 -#> ds 1 parent 60 65.1 63.316 1.78361 4.9994 0.356767 -#> ds 1 parent 60 65.8 63.316 2.48361 4.9994 0.496785 -#> ds 1 parent 90 47.8 50.029 -2.22862 3.9502 -0.564182 -#> ds 1 parent 90 53.5 50.029 3.47138 3.9502 0.878792 -#> ds 1 parent 120 37.6 39.529 -1.92946 3.1212 -0.618182 -#> ds 1 parent 120 39.3 39.529 -0.22946 3.1212 -0.073516 -#> ds 2 parent 0 107.9 101.711 6.18875 8.0309 0.770613 -#> ds 2 parent 0 102.1 101.711 0.38875 8.0309 0.048406 -#> ds 2 parent 1 103.8 100.174 3.62597 7.9096 0.458428 -#> ds 2 parent 1 108.6 100.174 8.42597 7.9096 1.065287 -#> ds 2 parent 3 91.0 97.169 -6.16895 7.6723 -0.804055 -#> ds 2 parent 3 84.9 97.169 -12.26895 7.6723 -1.599124 -#> ds 2 parent 7 79.3 91.427 -12.12652 7.2189 -1.679833 -#> ds 2 parent 7 100.9 91.427 9.47348 7.2189 1.312320 -#> ds 2 parent 14 77.3 82.182 -4.88174 6.4889 -0.752318 -#> ds 2 parent 14 83.5 82.182 1.31826 6.4889 0.203155 -#> ds 2 parent 28 66.8 66.402 0.39792 5.2430 0.075895 -#> ds 2 parent 28 63.3 66.402 -3.10208 5.2430 -0.591662 -#> ds 2 parent 60 40.8 40.789 0.01138 3.2206 0.003532 -#> ds 2 parent 60 44.8 40.789 4.01138 3.2206 1.245537 -#> ds 2 parent 90 27.8 25.830 1.97002 2.0395 0.965937 -#> ds 2 parent 90 27.0 25.830 1.17002 2.0395 0.573682 -#> ds 2 parent 120 15.2 16.357 -1.15721 1.2915 -0.895991 -#> ds 2 parent 120 15.5 16.357 -0.85721 1.2915 -0.663710 -#> ds 3 parent 0 97.7 101.907 -4.20726 8.0464 -0.522873 -#> ds 3 parent 0 88.2 101.907 -13.70726 8.0464 -1.703521 -#> ds 3 parent 1 109.9 99.522 10.37805 7.8581 1.320685 -#> ds 3 parent 1 97.8 99.522 -1.72195 7.8581 -0.219130 -#> ds 3 parent 3 100.5 94.918 5.58248 7.4945 0.744875 -#> ds 3 parent 3 77.4 94.918 -17.51752 7.4945 -2.337375 -#> ds 3 parent 7 78.3 86.338 -8.03788 6.8171 -1.179077 -#> ds 3 parent 7 90.3 86.338 3.96212 6.8171 0.581204 -#> ds 3 parent 14 76.0 73.147 2.85281 5.7756 0.493944 -#> ds 3 parent 14 79.1 73.147 5.95281 5.7756 1.030687 -#> ds 3 parent 28 46.0 52.504 -6.50373 4.1456 -1.568826 -#> ds 3 parent 28 53.4 52.504 0.89627 4.1456 0.216197 -#> ds 3 parent 60 25.1 24.605 0.49461 1.9428 0.254586 -#> ds 3 parent 60 21.4 24.605 -3.20539 1.9428 -1.649882 -#> ds 3 parent 90 11.0 12.090 -1.09046 0.9546 -1.142271 -#> ds 3 parent 90 14.2 12.090 2.10954 0.9546 2.209770 -#> ds 3 parent 120 5.8 5.941 -0.14094 0.4691 -0.300464 -#> ds 3 parent 120 6.1 5.941 0.15906 0.4691 0.339077 -#> ds 4 parent 0 95.3 101.177 -5.87672 7.9887 -0.735625 -#> ds 4 parent 0 102.0 101.177 0.82328 7.9887 0.103056 -#> ds 4 parent 1 104.4 100.716 3.68438 7.9523 0.463307 -#> ds 4 parent 1 105.4 100.716 4.68438 7.9523 0.589057 -#> ds 4 parent 3 113.7 99.800 13.90026 7.8800 1.763989 -#> ds 4 parent 3 82.3 99.800 -17.49974 7.8800 -2.220774 -#> ds 4 parent 7 98.1 97.993 0.10713 7.7374 0.013846 -#> ds 4 parent 7 87.8 97.993 -10.19287 7.7374 -1.317359 -#> ds 4 parent 14 97.9 94.909 2.99079 7.4939 0.399098 -#> ds 4 parent 14 104.8 94.909 9.89079 7.4939 1.319851 -#> ds 4 parent 28 85.0 89.030 -4.02995 7.0297 -0.573279 -#> ds 4 parent 28 77.2 89.030 -11.82995 7.0297 -1.682864 -#> ds 4 parent 60 82.2 76.923 5.27690 6.0737 0.868808 -#> ds 4 parent 60 86.1 76.923 9.17690 6.0737 1.510919 -#> ds 4 parent 90 70.5 67.073 3.42743 5.2959 0.647182 -#> ds 4 parent 90 61.7 67.073 -5.37257 5.2959 -1.014470 -#> ds 4 parent 120 60.0 58.483 1.51654 4.6178 0.328416 -#> ds 4 parent 120 56.4 58.483 -2.08346 4.6178 -0.451184 -#> ds 5 parent 0 92.6 101.752 -9.15161 8.0341 -1.139091 -#> ds 5 parent 0 116.5 101.752 14.74839 8.0341 1.835716 -#> ds 5 parent 1 108.0 100.069 7.93112 7.9013 1.003778 -#> ds 5 parent 1 104.9 100.069 4.83112 7.9013 0.611436 -#> ds 5 parent 3 100.5 96.786 3.71355 7.6421 0.485934 -#> ds 5 parent 3 89.5 96.786 -7.28645 7.6421 -0.953462 -#> ds 5 parent 7 91.7 90.541 1.15895 7.1490 0.162114 -#> ds 5 parent 7 95.1 90.541 4.55895 7.1490 0.637707 -#> ds 5 parent 14 82.2 80.566 1.63437 6.3613 0.256923 -#> ds 5 parent 14 84.5 80.566 3.93437 6.3613 0.618483 -#> ds 5 parent 28 60.5 63.791 -3.29084 5.0368 -0.653357 -#> ds 5 parent 28 72.8 63.791 9.00916 5.0368 1.788662 -#> ds 5 parent 60 38.3 37.412 0.88840 2.9540 0.300748 -#> ds 5 parent 60 40.7 37.412 3.28840 2.9540 1.113217 -#> ds 5 parent 90 22.5 22.685 -0.18500 1.7912 -0.103287 -#> ds 5 parent 90 20.8 22.685 -1.88500 1.7912 -1.052387 -#> ds 5 parent 120 13.4 13.755 -0.35534 1.0861 -0.327173 -#> ds 5 parent 120 13.8 13.755 0.04466 1.0861 0.041118</div><div class='input'> +#> ds 1 parent 0 104.1 101.592 2.50757 8.0255 0.312451 +#> ds 1 parent 0 105.0 101.592 3.40757 8.0255 0.424594 +#> ds 1 parent 1 98.5 100.796 -2.29571 7.9625 -0.288313 +#> ds 1 parent 1 96.1 100.796 -4.69571 7.9625 -0.589725 +#> ds 1 parent 3 101.9 99.221 2.67904 7.8381 0.341796 +#> ds 1 parent 3 85.2 99.221 -14.02096 7.8381 -1.788812 +#> ds 1 parent 7 99.1 96.145 2.95512 7.5951 0.389081 +#> ds 1 parent 7 93.0 96.145 -3.14488 7.5951 -0.414065 +#> ds 1 parent 14 88.1 90.989 -2.88944 7.1879 -0.401987 +#> ds 1 parent 14 84.1 90.989 -6.88944 7.1879 -0.958480 +#> ds 1 parent 28 80.2 81.493 -1.29305 6.4377 -0.200857 +#> ds 1 parent 28 91.3 81.493 9.80695 6.4377 1.523364 +#> ds 1 parent 60 65.1 63.344 1.75642 5.0039 0.351008 +#> ds 1 parent 60 65.8 63.344 2.45642 5.0039 0.490898 +#> ds 1 parent 90 47.8 50.018 -2.21764 3.9512 -0.561252 +#> ds 1 parent 90 53.5 50.018 3.48236 3.9512 0.881335 +#> ds 1 parent 120 37.6 39.495 -1.89515 3.1200 -0.607423 +#> ds 1 parent 120 39.3 39.495 -0.19515 3.1200 -0.062549 +#> ds 2 parent 0 107.9 101.592 6.30757 8.0255 0.785943 +#> ds 2 parent 0 102.1 101.592 0.50757 8.0255 0.063245 +#> ds 2 parent 1 103.8 100.058 3.74159 7.9043 0.473361 +#> ds 2 parent 1 108.6 100.058 8.54159 7.9043 1.080626 +#> ds 2 parent 3 91.0 97.060 -6.05952 7.6674 -0.790297 +#> ds 2 parent 3 84.9 97.060 -12.15952 7.6674 -1.585874 +#> ds 2 parent 7 79.3 91.329 -12.02867 7.2147 -1.667251 +#> ds 2 parent 7 100.9 91.329 9.57133 7.2147 1.326647 +#> ds 2 parent 14 77.3 82.102 -4.80185 6.4858 -0.740366 +#> ds 2 parent 14 83.5 82.102 1.39815 6.4858 0.215571 +#> ds 2 parent 28 66.8 66.351 0.44945 5.2415 0.085748 +#> ds 2 parent 28 63.3 66.351 -3.05055 5.2415 -0.582002 +#> ds 2 parent 60 40.8 40.775 0.02474 3.2211 0.007679 +#> ds 2 parent 60 44.8 40.775 4.02474 3.2211 1.249485 +#> ds 2 parent 90 27.8 25.832 1.96762 2.0407 0.964198 +#> ds 2 parent 90 27.0 25.832 1.16762 2.0407 0.572171 +#> ds 2 parent 120 15.2 16.366 -1.16561 1.2928 -0.901595 +#> ds 2 parent 120 15.5 16.366 -0.86561 1.2928 -0.669547 +#> ds 3 parent 0 97.7 101.592 -3.89243 8.0255 -0.485009 +#> ds 3 parent 0 88.2 101.592 -13.39243 8.0255 -1.668739 +#> ds 3 parent 1 109.9 99.218 10.68196 7.8379 1.362858 +#> ds 3 parent 1 97.8 99.218 -1.41804 7.8379 -0.180921 +#> ds 3 parent 3 100.5 94.634 5.86555 7.4758 0.784603 +#> ds 3 parent 3 77.4 94.634 -17.23445 7.4758 -2.305360 +#> ds 3 parent 7 78.3 86.093 -7.79273 6.8011 -1.145813 +#> ds 3 parent 7 90.3 86.093 4.20727 6.8011 0.618620 +#> ds 3 parent 14 76.0 72.958 3.04222 5.7634 0.527848 +#> ds 3 parent 14 79.1 72.958 6.14222 5.7634 1.065722 +#> ds 3 parent 28 46.0 52.394 -6.39404 4.1390 -1.544842 +#> ds 3 parent 28 53.4 52.394 1.00596 4.1390 0.243046 +#> ds 3 parent 60 25.1 24.582 0.51786 1.9419 0.266676 +#> ds 3 parent 60 21.4 24.582 -3.18214 1.9419 -1.638664 +#> ds 3 parent 90 11.0 12.092 -1.09202 0.9552 -1.143199 +#> ds 3 parent 90 14.2 12.092 2.10798 0.9552 2.206776 +#> ds 3 parent 120 5.8 5.948 -0.14810 0.4699 -0.315178 +#> ds 3 parent 120 6.1 5.948 0.15190 0.4699 0.323282 +#> ds 4 parent 0 95.3 101.592 -6.29243 8.0255 -0.784057 +#> ds 4 parent 0 102.0 101.592 0.40757 8.0255 0.050784 +#> ds 4 parent 1 104.4 101.125 3.27549 7.9885 0.410025 +#> ds 4 parent 1 105.4 101.125 4.27549 7.9885 0.535205 +#> ds 4 parent 3 113.7 100.195 13.50487 7.9151 1.706218 +#> ds 4 parent 3 82.3 100.195 -17.89513 7.9151 -2.260886 +#> ds 4 parent 7 98.1 98.362 -0.26190 7.7703 -0.033706 +#> ds 4 parent 7 87.8 98.362 -10.56190 7.7703 -1.359270 +#> ds 4 parent 14 97.9 95.234 2.66590 7.5232 0.354357 +#> ds 4 parent 14 104.8 95.234 9.56590 7.5232 1.271521 +#> ds 4 parent 28 85.0 89.274 -4.27372 7.0523 -0.606001 +#> ds 4 parent 28 77.2 89.274 -12.07372 7.0523 -1.712017 +#> ds 4 parent 60 82.2 77.013 5.18661 6.0838 0.852526 +#> ds 4 parent 60 86.1 77.013 9.08661 6.0838 1.493571 +#> ds 4 parent 90 70.5 67.053 3.44692 5.2970 0.650733 +#> ds 4 parent 90 61.7 67.053 -5.35308 5.2970 -1.010591 +#> ds 4 parent 120 60.0 58.381 1.61905 4.6119 0.351058 +#> ds 4 parent 120 56.4 58.381 -1.98095 4.6119 -0.429530 +#> ds 5 parent 0 92.6 101.592 -8.99243 8.0255 -1.120485 +#> ds 5 parent 0 116.5 101.592 14.90757 8.0255 1.857531 +#> ds 5 parent 1 108.0 99.914 8.08560 7.8929 1.024413 +#> ds 5 parent 1 104.9 99.914 4.98560 7.8929 0.631655 +#> ds 5 parent 3 100.5 96.641 3.85898 7.6343 0.505477 +#> ds 5 parent 3 89.5 96.641 -7.14102 7.6343 -0.935382 +#> ds 5 parent 7 91.7 90.412 1.28752 7.1423 0.180267 +#> ds 5 parent 7 95.1 90.412 4.68752 7.1423 0.656304 +#> ds 5 parent 14 82.2 80.463 1.73715 6.3563 0.273295 +#> ds 5 parent 14 84.5 80.463 4.03715 6.3563 0.635141 +#> ds 5 parent 28 60.5 63.728 -3.22788 5.0343 -0.641178 +#> ds 5 parent 28 72.8 63.728 9.07212 5.0343 1.802062 +#> ds 5 parent 60 38.3 37.399 0.90061 2.9544 0.304835 +#> ds 5 parent 60 40.7 37.399 3.30061 2.9544 1.117174 +#> ds 5 parent 90 22.5 22.692 -0.19165 1.7926 -0.106913 +#> ds 5 parent 90 20.8 22.692 -1.89165 1.7926 -1.055273 +#> ds 5 parent 120 13.4 13.768 -0.36790 1.0876 -0.338259 +#> ds 5 parent 120 13.8 13.768 0.03210 1.0876 0.029517</div><div class='input'> </div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> diff --git a/docs/dev/reference/summary.nlmixr.mmkin.html b/docs/dev/reference/summary.nlmixr.mmkin.html new file mode 100644 index 00000000..373ce75f --- 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Optionally +(default is FALSE), the data are listed in full.</p> + </div> + + <pre class="usage"><span class='co'># S3 method for nlmixr.mmkin</span> +<span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>object</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span>, verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, distimes <span class='op'>=</span> <span class='cn'>TRUE</span>, <span class='va'>...</span><span class='op'>)</span> + +<span class='co'># S3 method for summary.nlmixr.mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, digits <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"digits"</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>3</span><span class='op'>)</span>, verbose <span class='op'>=</span> <span class='va'>x</span><span class='op'>$</span><span class='va'>verbose</span>, <span class='va'>...</span><span class='op'>)</span></pre> + + <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>object</th> + <td><p>an object of class <a href='nlmixr.mmkin.html'>nlmixr.mmkin</a></p></td> + </tr> + <tr> + <th>data</th> + <td><p>logical, indicating whether the full data should be included in +the summary.</p></td> + </tr> + <tr> + <th>verbose</th> + <td><p>Should the summary be verbose?</p></td> + </tr> + <tr> + <th>distimes</th> + <td><p>logical, indicating whether DT50 and DT90 values should be +included.</p></td> + </tr> + <tr> + <th>...</th> + <td><p>optional arguments passed to methods like <code>print</code>.</p></td> + </tr> + <tr> + <th>x</th> + <td><p>an object of class summary.nlmixr.mmkin</p></td> + </tr> + <tr> + <th>digits</th> + <td><p>Number of digits to use for printing</p></td> + </tr> + </table> + + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>The summary function returns a list obtained in the fit, with at +least the following additional components</p> +<dt>nlmixrversion, mkinversion, Rversion</dt><dd><p>The nlmixr, mkin and R versions used</p></dd> +<dt>date.fit, date.summary</dt><dd><p>The dates where the fit and the summary were +produced</p></dd> +<dt>diffs</dt><dd><p>The differential equations used in the degradation model</p></dd> +<dt>use_of_ff</dt><dd><p>Was maximum or minimum use made of formation fractions</p></dd> +<dt>data</dt><dd><p>The data</p></dd> +<dt>confint_back</dt><dd><p>Backtransformed parameters, with confidence intervals if available</p></dd> +<dt>ff</dt><dd><p>The estimated formation fractions derived from the fitted +model.</p></dd> +<dt>distimes</dt><dd><p>The DT50 and DT90 values for each observed variable.</p></dd> +<dt>SFORB</dt><dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> +The print method is called for its side effect, i.e. printing the summary. + + <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> + + <p>Johannes Ranke for the mkin specific parts +nlmixr authors for the parts inherited from nlmixr.</p> + + <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> + <pre class="examples"><div class='input'><span class='co'># Generate five datasets following DFOP-SFO kinetics</span> +<span class='va'>sampling_times</span> <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span><span class='op'>)</span> +<span class='va'>dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, + m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span><span class='op'>(</span><span class='fl'>1234</span><span class='op'>)</span> +<span class='va'>k1_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Lognormal.html'>rlnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>0.1</span><span class='op'>)</span>, <span class='fl'>0.3</span><span class='op'>)</span> +<span class='va'>k2_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Lognormal.html'>rlnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>0.02</span><span class='op'>)</span>, <span class='fl'>0.3</span><span class='op'>)</span> +<span class='va'>g_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Logistic.html'>plogis</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/stats/Logistic.html'>qlogis</a></span><span class='op'>(</span><span class='fl'>0.5</span><span class='op'>)</span>, <span class='fl'>0.3</span><span class='op'>)</span><span class='op'>)</span> +<span class='va'>f_parent_to_m1_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Logistic.html'>plogis</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/stats/Logistic.html'>qlogis</a></span><span class='op'>(</span><span class='fl'>0.3</span><span class='op'>)</span>, <span class='fl'>0.3</span><span class='op'>)</span><span class='op'>)</span> +<span class='va'>k_m1_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Lognormal.html'>rlnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>0.02</span><span class='op'>)</span>, <span class='fl'>0.3</span><span class='op'>)</span> + +<span class='va'>pred_dfop_sfo</span> <span class='op'><-</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>k1</span>, <span class='va'>k2</span>, <span class='va'>g</span>, <span class='va'>f_parent_to_m1</span>, <span class='va'>k_m1</span><span class='op'>)</span> <span class='op'>{</span> + <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>dfop_sfo</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k1 <span class='op'>=</span> <span class='va'>k1</span>, k2 <span class='op'>=</span> <span class='va'>k2</span>, g <span class='op'>=</span> <span class='va'>g</span>, f_parent_to_m1 <span class='op'>=</span> <span class='va'>f_parent_to_m1</span>, k_m1 <span class='op'>=</span> <span class='va'>k_m1</span><span class='op'>)</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span>, m1 <span class='op'>=</span> <span class='fl'>0</span><span class='op'>)</span>, + <span class='va'>sampling_times</span><span class='op'>)</span> +<span class='op'>}</span> + +<span class='va'>ds_mean_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>:</span><span class='fl'>5</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='op'>{</span> + <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>dfop_sfo</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k1 <span class='op'>=</span> <span class='va'>k1_in</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span>, k2 <span class='op'>=</span> <span class='va'>k2_in</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span>, g <span class='op'>=</span> <span class='va'>g_in</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span>, + f_parent_to_m1 <span class='op'>=</span> <span class='va'>f_parent_to_m1_in</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span>, k_m1 <span class='op'>=</span> <span class='va'>k_m1_in</span><span class='op'>[</span><span class='va'>i</span><span class='op'>]</span><span class='op'>)</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span>, m1 <span class='op'>=</span> <span class='fl'>0</span><span class='op'>)</span>, + <span class='va'>sampling_times</span><span class='op'>)</span> +<span class='op'>}</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds_mean_dfop_sfo</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"ds"</span>, <span class='fl'>1</span><span class='op'>:</span><span class='fl'>5</span><span class='op'>)</span> + +<span class='va'>ds_syn_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>ds_mean_dfop_sfo</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>{</span> + <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>ds</span>, + sdfunc <span class='op'>=</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>sqrt</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>+</span> <span class='va'>value</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>*</span> <span class='fl'>0.07</span><span class='op'>^</span><span class='fl'>2</span><span class='op'>)</span>, + n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span> +<span class='op'>}</span><span class='op'>)</span> + +<span class='co'># \dontrun{</span> +<span class='co'># Evaluate using mmkin and nlmixr</span> +<span class='va'>f_mmkin_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>dfop_sfo</span><span class='op'>)</span>, <span class='va'>ds_syn_dfop_sfo</span>, + quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, cores <span class='op'>=</span> <span class='fl'>5</span><span class='op'>)</span> +<span class='va'>f_saemix_dfop_sfo</span> <span class='op'><-</span> <span class='fu'>mkin</span><span class='fu'>::</span><span class='fu'><a href='saem.html'>saem</a></span><span class='op'>(</span><span class='va'>f_mmkin_dfop_sfo</span><span class='op'>)</span> +</div><div class='output co'>#> Running main SAEM algorithm +#> [1] "Tue Jul 27 16:31:43 2021" +#> .... +#> Minimisation finished +#> [1] "Tue Jul 27 16:31:55 2021"</div><div class='input'><span class='va'>f_nlme_dfop_sfo</span> <span class='op'><-</span> <span class='fu'>mkin</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_mmkin_dfop_sfo</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='warning'>Warning: Iteration 4, LME step: nlminb() did not converge (code = 1). PORT message: false convergence (8)</span></div><div class='output co'>#> <span class='warning'>Warning: Iteration 6, LME step: nlminb() did not converge (code = 1). PORT message: false convergence (8)</span></div><div class='input'><span class='va'>f_nlmixr_dfop_sfo_saem</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_dfop_sfo</span>, est <span class='op'>=</span> <span class='st'>"saem"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'>→ generate SAEM model</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='error'>Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_m1</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 1.281 0.142 1.422</span></div><div class='input'><span class='co'># The following takes a very long time but gives</span> +<span class='va'>f_nlmixr_dfop_sfo_focei</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlmixr/man/nlmixr.html'>nlmixr</a></span><span class='op'>(</span><span class='va'>f_mmkin_dfop_sfo</span>, est <span class='op'>=</span> <span class='st'>"focei"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span></div><div class='output co'>#> <span class='message'><span style='color: #00BBBB;'>ℹ</span> Need to run with the source intact to parse comments</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ creating full model...</span></div><div class='output co'>#> <span class='message'>→ pruning branches (<span style='color: #262626; background-color: #DADADA;'>`if`</span>/<span style='color: #262626; background-color: #DADADA;'>`else`</span>)...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ loading into <span style='color: #0000BB;'>symengine</span> environment...</span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ calculate jacobian</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate sensitivities</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(f)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ calculate ∂(R²)/∂(η)</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in inner model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in EBE model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling inner model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ finding duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ optimizing duplicate expressions in FD model...</span></div><div class='output co'>#> </div><div class='output co'>#> <span class='message'>→ compiling EBE model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>→ compiling events FD model...</span></div><div class='output co'>#> <span class='message'> </span></div><div class='output co'>#> <span class='message'><span style='color: #00BB00;'>✔</span> done</span></div><div class='output co'>#> <span class='message'>Model:</span></div><div class='output co'>#> <span class='message'>cmt(parent);</span> +#> <span class='message'>cmt(m1);</span> +#> <span class='message'>rx_expr_6~ETA[1]+THETA[1];</span> +#> <span class='message'>parent(0)=rx_expr_6;</span> +#> <span class='message'>rx_expr_7~ETA[4]+THETA[4];</span> +#> <span class='message'>rx_expr_8~ETA[6]+THETA[6];</span> +#> <span class='message'>rx_expr_9~ETA[5]+THETA[5];</span> +#> <span class='message'>rx_expr_12~exp(rx_expr_7);</span> +#> <span class='message'>rx_expr_13~exp(rx_expr_9);</span> +#> <span class='message'>rx_expr_15~t*rx_expr_12;</span> +#> <span class='message'>rx_expr_16~t*rx_expr_13;</span> +#> <span class='message'>rx_expr_19~exp(-(rx_expr_8));</span> +#> <span class='message'>rx_expr_21~1+rx_expr_19;</span> +#> <span class='message'>rx_expr_26~1/(rx_expr_21);</span> +#> <span class='message'>rx_expr_28~(rx_expr_26);</span> +#> <span class='message'>rx_expr_29~1-rx_expr_28;</span> +#> <span class='message'>d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));</span> +#> <span class='message'>rx_expr_10~ETA[2]+THETA[2];</span> +#> <span class='message'>rx_expr_14~exp(rx_expr_10);</span> +#> <span class='message'>d/dt(m1)=-rx_expr_14*m1+parent*f_parent_to_m1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));</span> +#> <span class='message'>rx_expr_0~CMT==2;</span> +#> <span class='message'>rx_expr_1~CMT==1;</span> +#> <span class='message'>rx_expr_2~1-(rx_expr_0);</span> +#> <span class='message'>rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);</span> +#> <span class='message'>rx_expr_3~(rx_expr_0);</span> +#> <span class='message'>rx_expr_5~(rx_expr_2);</span> +#> <span class='message'>rx_expr_20~rx_expr_5*(rx_expr_1);</span> +#> <span class='message'>rx_lambda_~rx_expr_20+rx_expr_3;</span> +#> <span class='message'>rx_hi_~rx_expr_20+rx_expr_3;</span> +#> <span class='message'>rx_low_~0;</span> +#> <span class='message'>rx_expr_4~m1*(rx_expr_0);</span> +#> <span class='message'>rx_expr_11~parent*(rx_expr_2);</span> +#> <span class='message'>rx_expr_24~rx_expr_11*(rx_expr_1);</span> +#> <span class='message'>rx_pred_=(rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>rx_expr_17~Rx_pow_di(THETA[8],2);</span> +#> <span class='message'>rx_expr_18~Rx_pow_di(THETA[7],2);</span> +#> <span class='message'>rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1)),2)*rx_expr_17+rx_expr_18)*(rx_expr_0)+(Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_1)),2)*rx_expr_17+rx_expr_18)*(rx_expr_2)*(rx_expr_1);</span> +#> <span class='message'>parent_0=THETA[1];</span> +#> <span class='message'>log_k_m1=THETA[2];</span> +#> <span class='message'>f_parent_qlogis=THETA[3];</span> +#> <span class='message'>log_k1=THETA[4];</span> +#> <span class='message'>log_k2=THETA[5];</span> +#> <span class='message'>g_qlogis=THETA[6];</span> +#> <span class='message'>sigma_low=THETA[7];</span> +#> <span class='message'>rsd_high=THETA[8];</span> +#> <span class='message'>eta.parent_0=ETA[1];</span> +#> <span class='message'>eta.log_k_m1=ETA[2];</span> +#> <span class='message'>eta.f_parent_qlogis=ETA[3];</span> +#> <span class='message'>eta.log_k1=ETA[4];</span> +#> <span class='message'>eta.log_k2=ETA[5];</span> +#> <span class='message'>eta.g_qlogis=ETA[6];</span> +#> <span class='message'>parent_0_model=rx_expr_6;</span> +#> <span class='message'>k_m1=rx_expr_14;</span> +#> <span class='message'>k1=rx_expr_12;</span> +#> <span class='message'>k2=rx_expr_13;</span> +#> <span class='message'>f_parent=1/(1+exp(-(ETA[3]+THETA[3])));</span> +#> <span class='message'>g=1/(rx_expr_21);</span> +#> <span class='message'>tad=tad();</span> +#> <span class='message'>dosenum=dosenum();</span></div><div class='output co'>#> <span class='message'>Needed Covariates:</span></div><div class='output co'>#> <span class='message'>[1] "f_parent_to_m1" "CMT" </span></div><div class='output co'>#> <span class='error'>Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 19.01 0.403 19.42</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nlmixr_dfop_sfo_saem</span><span class='op'>$</span><span class='va'>nm</span>, <span class='va'>f_nlmixr_dfop_sfo_focei</span><span class='op'>$</span><span class='va'>nm</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in AIC(f_nlmixr_dfop_sfo_saem$nm, f_nlmixr_dfop_sfo_focei$nm): object 'f_nlmixr_dfop_sfo_saem' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_nlmixr_dfop_sfo_sfo</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='error'>Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_nlmixr_dfop_sfo_sfo' not found</span></div><div class='input'><span class='co'># }</span> + +</div></pre> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"> + <h2 data-toc-skip>Contents</h2> + </nav> + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html index 722415fb..fdfdaf4b 100644 --- a/docs/dev/reference/summary.saem.mmkin.html +++ b/docs/dev/reference/summary.saem.mmkin.html @@ -76,7 +76,7 @@ endpoints such as formation fractions and DT50 values. Optionally </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.5</span> </span> </div> @@ -260,15 +260,15 @@ saemix authors for the parts inherited from saemix.</p> quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, cores <span class='op'>=</span> <span class='fl'>5</span><span class='op'>)</span> <span class='va'>f_saem_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='saem.html'>saem</a></span><span class='op'>(</span><span class='va'>f_mmkin_dfop_sfo</span><span class='op'>)</span> </div><div class='output co'>#> Running main SAEM algorithm -#> [1] "Mon Jan 11 12:42:40 2021" +#> [1] "Fri Jun 11 10:58:28 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 11 12:42:53 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +#> [1] "Fri Jun 11 10:58:40 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> </div><div class='output co'>#> saemix version used for fitting: 3.1.9000 -#> mkin version used for pre-fitting: 0.9.50.4 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Jan 11 12:42:54 2021 -#> Date of summary: Mon Jan 11 12:42:54 2021 +#> mkin version used for pre-fitting: 1.0.5 +#> R version used for fitting: 4.1.0 +#> Date of fit: Fri Jun 11 10:58:41 2021 +#> Date of summary: Fri Jun 11 10:58:41 2021 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -283,7 +283,7 @@ saemix authors for the parts inherited from saemix.</p> #> #> Model predictions using solution type analytical #> -#> Fitted in 13.298 s using 300, 100 iterations +#> Fitted in 12.75 s using 300, 100 iterations #> #> Variance model: Two-component variance function #> @@ -291,7 +291,7 @@ saemix authors for the parts inherited from saemix.</p> #> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 #> 101.65645 -4.05368 -0.94311 -2.35943 -4.07006 #> g_qlogis -#> -0.01133 +#> -0.01132 #> #> Fixed degradation parameter values: #> None @@ -299,232 +299,232 @@ saemix authors for the parts inherited from saemix.</p> #> Results: #> #> Likelihood computed by importance sampling -#> AIC BIC logLik -#> 830 824.5 -401 +#> AIC BIC logLik +#> 825.9 820.4 -398.9 #> #> Optimised parameters: -#> est. lower upper -#> parent_0 101.4423 97.862 105.0224 -#> log_k_m1 -4.0703 -4.191 -3.9495 -#> f_parent_qlogis -0.9539 -1.313 -0.5949 -#> log_k1 -2.9724 -3.811 -2.1342 -#> log_k2 -3.4977 -4.206 -2.7895 -#> g_qlogis -0.0449 -1.116 1.0262 +#> est. lower upper +#> parent_0 101.118986 97.368 104.8695 +#> log_k_m1 -4.057591 -4.177 -3.9379 +#> f_parent_qlogis -0.933087 -1.290 -0.5763 +#> log_k1 -2.945520 -3.833 -2.0576 +#> log_k2 -3.531954 -4.310 -2.7542 +#> g_qlogis -0.009584 -1.688 1.6687 #> #> Correlation: #> prnt_0 lg_k_1 f_prn_ log_k1 log_k2 -#> log_k_m1 -0.207 -#> f_parent_qlogis -0.148 0.202 -#> log_k1 0.040 -0.038 -0.022 -#> log_k2 0.022 -0.015 -0.009 0.001 -#> g_qlogis -0.012 0.005 0.011 -0.173 -0.130 +#> log_k_m1 -0.198 +#> f_parent_qlogis -0.153 0.184 +#> log_k1 0.080 -0.077 -0.045 +#> log_k2 0.005 0.008 -0.003 -0.019 +#> g_qlogis -0.059 0.048 0.041 -0.334 -0.253 #> #> Random effects: -#> est. lower upper -#> SD.parent_0 2.88564 -0.5163 6.2876 -#> SD.log_k_m1 0.08502 -0.0427 0.2127 -#> SD.f_parent_qlogis 0.38857 0.1350 0.6421 -#> SD.log_k1 0.92338 0.3296 1.5172 -#> SD.log_k2 0.78644 0.2817 1.2912 -#> SD.g_qlogis 0.34614 -0.8727 1.5650 +#> est. lower upper +#> SD.parent_0 2.97797 -0.62927 6.5852 +#> SD.log_k_m1 0.09235 -0.02448 0.2092 +#> SD.f_parent_qlogis 0.38712 0.13469 0.6396 +#> SD.log_k1 0.88671 0.27052 1.5029 +#> SD.log_k2 0.80497 0.25587 1.3541 +#> SD.g_qlogis 0.36812 -3.56188 4.2981 #> #> Variance model: #> est. lower upper -#> a.1 0.65859 0.49250 0.82469 -#> b.1 0.06411 0.05006 0.07817 +#> a.1 0.85879 0.68143 1.03615 +#> b.1 0.07787 0.06288 0.09286 #> #> Backtransformed parameters: #> est. lower upper -#> parent_0 101.44231 97.86220 105.02241 -#> k_m1 0.01707 0.01513 0.01926 -#> f_parent_to_m1 0.27811 0.21201 0.35551 -#> k1 0.05118 0.02213 0.11834 -#> k2 0.03027 0.01491 0.06145 -#> g 0.48878 0.24675 0.73618 +#> parent_0 101.11899 97.36850 104.86947 +#> k_m1 0.01729 0.01534 0.01949 +#> f_parent_to_m1 0.28230 0.21587 0.35979 +#> k1 0.05257 0.02163 0.12776 +#> k2 0.02925 0.01344 0.06366 +#> g 0.49760 0.15606 0.84140 #> #> Resulting formation fractions: #> ff -#> parent_m1 0.2781 -#> parent_sink 0.7219 +#> parent_m1 0.2823 +#> parent_sink 0.7177 #> #> Estimated disappearance times: #> DT50 DT90 DT50back DT50_k1 DT50_k2 -#> parent 17.53 61.64 18.55 13.54 22.9 -#> m1 40.60 134.88 NA NA NA +#> parent 17.47 62.31 18.76 13.18 23.7 +#> m1 40.09 133.17 NA NA NA #> #> Data: -#> ds name time observed predicted residual std standardized -#> ds 1 parent 0 89.8 9.869e+01 8.894553 6.3618 1.398124 -#> ds 1 parent 0 104.1 9.869e+01 -5.405447 6.3618 -0.849676 -#> ds 1 parent 1 88.7 9.413e+01 5.426448 6.0706 0.893897 -#> ds 1 parent 1 95.5 9.413e+01 -1.373552 6.0706 -0.226265 -#> ds 1 parent 3 81.8 8.576e+01 3.961821 5.5377 0.715422 -#> ds 1 parent 3 94.5 8.576e+01 -8.738179 5.5377 -1.577932 -#> ds 1 parent 7 71.5 7.168e+01 0.184828 4.6429 0.039809 -#> ds 1 parent 7 70.3 7.168e+01 1.384828 4.6429 0.298270 -#> ds 1 parent 14 54.2 5.351e+01 -0.688235 3.4934 -0.197008 -#> ds 1 parent 14 49.6 5.351e+01 3.911765 3.4934 1.119747 -#> ds 1 parent 28 31.5 3.209e+01 0.590445 2.1603 0.273322 -#> ds 1 parent 28 28.8 3.209e+01 3.290445 2.1603 1.523177 -#> ds 1 parent 60 12.1 1.272e+01 0.618158 1.0481 0.589761 -#> ds 1 parent 60 13.6 1.272e+01 -0.881842 1.0481 -0.841332 -#> ds 1 parent 90 6.2 6.085e+00 -0.115212 0.7655 -0.150512 -#> ds 1 parent 90 8.3 6.085e+00 -2.215212 0.7655 -2.893953 -#> ds 1 parent 120 2.2 3.009e+00 0.809439 0.6863 1.179470 -#> ds 1 parent 120 2.4 3.009e+00 0.609439 0.6863 0.888041 -#> ds 1 m1 1 0.3 1.129e+00 0.828817 0.6626 1.250938 -#> ds 1 m1 1 0.2 1.129e+00 0.928817 0.6626 1.401869 -#> ds 1 m1 3 2.2 3.141e+00 0.940880 0.6887 1.366187 -#> ds 1 m1 3 3.0 3.141e+00 0.140880 0.6887 0.204562 -#> ds 1 m1 7 6.5 6.326e+00 -0.174162 0.7735 -0.225175 -#> ds 1 m1 7 5.0 6.326e+00 1.325838 0.7735 1.714181 -#> ds 1 m1 14 10.2 9.883e+00 -0.317417 0.9139 -0.347326 -#> ds 1 m1 14 9.5 9.883e+00 0.382583 0.9139 0.418631 -#> ds 1 m1 28 12.2 1.251e+01 0.309856 1.0378 0.298572 -#> ds 1 m1 28 13.4 1.251e+01 -0.890144 1.0378 -0.857726 -#> ds 1 m1 60 11.8 1.086e+01 -0.940009 0.9584 -0.980812 -#> ds 1 m1 60 13.2 1.086e+01 -2.340009 0.9584 -2.441581 -#> ds 1 m1 90 6.6 7.823e+00 1.222977 0.8278 1.477332 -#> ds 1 m1 90 9.3 7.823e+00 -1.477023 0.8278 -1.784214 -#> ds 1 m1 120 3.5 5.315e+00 1.815201 0.7415 2.447906 -#> ds 1 m1 120 5.4 5.315e+00 -0.084799 0.7415 -0.114356 -#> ds 2 parent 0 118.0 1.031e+02 -14.876736 6.6443 -2.239038 -#> ds 2 parent 0 99.8 1.031e+02 3.323264 6.6443 0.500171 -#> ds 2 parent 1 90.2 9.757e+01 7.371379 6.2902 1.171891 -#> ds 2 parent 1 94.6 9.757e+01 2.971379 6.2902 0.472386 -#> ds 2 parent 3 96.1 8.788e+01 -8.222746 5.6724 -1.449599 -#> ds 2 parent 3 78.4 8.788e+01 9.477254 5.6724 1.670758 -#> ds 2 parent 7 77.9 7.293e+01 -4.972272 4.7218 -1.053054 -#> ds 2 parent 7 77.7 7.293e+01 -4.772272 4.7218 -1.010697 -#> ds 2 parent 14 56.0 5.602e+01 0.016773 3.6513 0.004594 -#> ds 2 parent 14 54.7 5.602e+01 1.316773 3.6513 0.360633 -#> ds 2 parent 28 36.6 3.855e+01 1.945779 2.5575 0.760803 -#> ds 2 parent 28 36.8 3.855e+01 1.745779 2.5575 0.682603 -#> ds 2 parent 60 22.1 2.101e+01 -1.086693 1.4996 -0.724663 -#> ds 2 parent 60 24.7 2.101e+01 -3.686693 1.4996 -2.458475 -#> ds 2 parent 90 12.4 1.246e+01 0.058759 1.0353 0.056757 -#> ds 2 parent 90 10.8 1.246e+01 1.658759 1.0353 1.602256 -#> ds 2 parent 120 6.8 7.406e+00 0.606226 0.8119 0.746659 -#> ds 2 parent 120 7.9 7.406e+00 -0.493774 0.8119 -0.608157 -#> ds 2 m1 1 1.3 1.438e+00 0.138236 0.6650 0.207869 -#> ds 2 m1 3 3.7 3.879e+00 0.178617 0.7040 0.253726 -#> ds 2 m1 3 4.7 3.879e+00 -0.821383 0.7040 -1.166780 -#> ds 2 m1 7 8.1 7.389e+00 -0.710951 0.8113 -0.876337 -#> ds 2 m1 7 7.9 7.389e+00 -0.510951 0.8113 -0.629812 -#> ds 2 m1 14 10.1 1.069e+01 0.593533 0.9507 0.624328 -#> ds 2 m1 14 10.3 1.069e+01 0.393533 0.9507 0.413951 -#> ds 2 m1 28 10.7 1.240e+01 1.703647 1.0325 1.649956 -#> ds 2 m1 28 12.2 1.240e+01 0.203647 1.0325 0.197229 -#> ds 2 m1 60 10.7 1.055e+01 -0.147672 0.9442 -0.156405 -#> ds 2 m1 60 12.5 1.055e+01 -1.947672 0.9442 -2.062848 -#> ds 2 m1 90 9.1 8.010e+00 -1.090041 0.8351 -1.305210 -#> ds 2 m1 90 7.4 8.010e+00 0.609959 0.8351 0.730362 -#> ds 2 m1 120 6.1 5.793e+00 -0.306797 0.7561 -0.405759 -#> ds 2 m1 120 4.5 5.793e+00 1.293203 0.7561 1.710347 -#> ds 3 parent 0 106.2 1.035e+02 -2.712344 6.6675 -0.406801 -#> ds 3 parent 0 106.9 1.035e+02 -3.412344 6.6675 -0.511788 -#> ds 3 parent 1 107.4 9.548e+01 -11.924044 6.1566 -1.936801 -#> ds 3 parent 1 96.1 9.548e+01 -0.624044 6.1566 -0.101362 -#> ds 3 parent 3 79.4 8.246e+01 3.056105 5.3274 0.573662 -#> ds 3 parent 3 82.6 8.246e+01 -0.143895 5.3274 -0.027010 -#> ds 3 parent 7 63.9 6.489e+01 0.991141 4.2122 0.235304 -#> ds 3 parent 7 62.4 6.489e+01 2.491141 4.2122 0.591416 -#> ds 3 parent 14 51.0 4.869e+01 -2.306824 3.1906 -0.723013 -#> ds 3 parent 14 47.1 4.869e+01 1.593176 3.1906 0.499338 -#> ds 3 parent 28 36.1 3.480e+01 -1.304261 2.3260 -0.560722 -#> ds 3 parent 28 36.6 3.480e+01 -1.804261 2.3260 -0.775679 -#> ds 3 parent 60 20.1 1.988e+01 -0.221952 1.4346 -0.154719 -#> ds 3 parent 60 19.8 1.988e+01 0.078048 1.4346 0.054406 -#> ds 3 parent 90 11.3 1.194e+01 0.642458 1.0099 0.636132 -#> ds 3 parent 90 10.7 1.194e+01 1.242458 1.0099 1.230224 -#> ds 3 parent 120 8.2 7.176e+00 -1.023847 0.8034 -1.274423 -#> ds 3 parent 120 7.3 7.176e+00 -0.123847 0.8034 -0.154158 -#> ds 3 m1 0 0.8 8.527e-13 -0.800000 0.6586 -1.214712 -#> ds 3 m1 1 1.8 1.856e+00 0.055925 0.6693 0.083562 -#> ds 3 m1 1 2.3 1.856e+00 -0.444075 0.6693 -0.663537 -#> ds 3 m1 3 4.2 4.780e+00 0.580164 0.7264 0.798676 -#> ds 3 m1 3 4.1 4.780e+00 0.680164 0.7264 0.936340 -#> ds 3 m1 7 6.8 8.410e+00 1.609920 0.8512 1.891455 -#> ds 3 m1 7 10.1 8.410e+00 -1.690080 0.8512 -1.985633 -#> ds 3 m1 14 11.4 1.098e+01 -0.424444 0.9638 -0.440389 -#> ds 3 m1 14 12.8 1.098e+01 -1.824444 0.9638 -1.892979 -#> ds 3 m1 28 11.5 1.142e+01 -0.079336 0.9848 -0.080558 -#> ds 3 m1 28 10.6 1.142e+01 0.820664 0.9848 0.833311 -#> ds 3 m1 60 7.5 9.110e+00 1.610231 0.8803 1.829222 -#> ds 3 m1 60 8.6 9.110e+00 0.510231 0.8803 0.579622 -#> ds 3 m1 90 7.3 6.799e+00 -0.501085 0.7898 -0.634463 -#> ds 3 m1 90 8.1 6.799e+00 -1.301085 0.7898 -1.647404 -#> ds 3 m1 120 5.3 4.868e+00 -0.431505 0.7288 -0.592064 -#> ds 3 m1 120 3.8 4.868e+00 1.068495 0.7288 1.466073 -#> ds 4 parent 0 104.7 9.926e+01 -5.444622 6.3975 -0.851049 -#> ds 4 parent 0 88.3 9.926e+01 10.955378 6.3975 1.712436 -#> ds 4 parent 1 94.2 9.618e+01 1.978413 6.2013 0.319030 -#> ds 4 parent 1 94.6 9.618e+01 1.578413 6.2013 0.254527 -#> ds 4 parent 3 78.1 9.037e+01 12.268550 5.8311 2.103985 -#> ds 4 parent 3 96.5 9.037e+01 -6.131450 5.8311 -1.051508 -#> ds 4 parent 7 76.2 7.999e+01 3.794958 5.1708 0.733918 -#> ds 4 parent 7 77.8 7.999e+01 2.194958 5.1708 0.424489 -#> ds 4 parent 14 70.8 6.518e+01 -5.624996 4.2301 -1.329742 -#> ds 4 parent 14 67.3 6.518e+01 -2.124996 4.2301 -0.502346 -#> ds 4 parent 28 43.1 4.462e+01 1.517860 2.9354 0.517085 -#> ds 4 parent 28 45.1 4.462e+01 -0.482140 2.9354 -0.164249 -#> ds 4 parent 60 21.3 2.130e+01 -0.003305 1.5159 -0.002180 -#> ds 4 parent 60 23.5 2.130e+01 -2.203305 1.5159 -1.453435 -#> ds 4 parent 90 11.8 1.180e+01 0.002834 1.0032 0.002825 -#> ds 4 parent 90 12.1 1.180e+01 -0.297166 1.0032 -0.296226 -#> ds 4 parent 120 7.0 6.868e+00 -0.132251 0.7922 -0.166937 -#> ds 4 parent 120 6.2 6.868e+00 0.667749 0.7922 0.842879 -#> ds 4 m1 0 1.6 0.000e+00 -1.600000 0.6586 -2.429424 -#> ds 4 m1 1 0.9 6.826e-01 -0.217363 0.6600 -0.329315 -#> ds 4 m1 3 3.7 1.935e+00 -1.765082 0.6702 -2.633768 -#> ds 4 m1 3 2.0 1.935e+00 -0.065082 0.6702 -0.097112 -#> ds 4 m1 7 3.6 4.035e+00 0.434805 0.7076 0.614501 -#> ds 4 m1 7 3.8 4.035e+00 0.234805 0.7076 0.331845 -#> ds 4 m1 14 7.1 6.652e+00 -0.448187 0.7846 -0.571220 -#> ds 4 m1 14 6.6 6.652e+00 0.051813 0.7846 0.066036 -#> ds 4 m1 28 9.5 9.156e+00 -0.343805 0.8822 -0.389696 -#> ds 4 m1 28 9.3 9.156e+00 -0.143805 0.8822 -0.163000 -#> ds 4 m1 60 8.3 8.848e+00 0.547762 0.8692 0.630185 -#> ds 4 m1 60 9.0 8.848e+00 -0.152238 0.8692 -0.175146 -#> ds 4 m1 90 6.6 6.674e+00 0.073979 0.7854 0.094194 -#> ds 4 m1 90 7.7 6.674e+00 -1.026021 0.7854 -1.306390 -#> ds 4 m1 120 3.7 4.668e+00 0.967537 0.7234 1.337503 -#> ds 4 m1 120 3.5 4.668e+00 1.167537 0.7234 1.613979 -#> ds 5 parent 0 110.4 1.022e+02 -8.170986 6.5872 -1.240433 -#> ds 5 parent 0 112.1 1.022e+02 -9.870986 6.5872 -1.498509 -#> ds 5 parent 1 93.5 9.513e+01 1.630764 6.1346 0.265832 -#> ds 5 parent 1 91.0 9.513e+01 4.130764 6.1346 0.673359 -#> ds 5 parent 3 71.0 8.296e+01 11.964279 5.3597 2.232268 -#> ds 5 parent 3 89.7 8.296e+01 -6.735721 5.3597 -1.256735 -#> ds 5 parent 7 60.4 6.495e+01 4.547441 4.2157 1.078684 -#> ds 5 parent 7 59.1 6.495e+01 5.847441 4.2157 1.387053 -#> ds 5 parent 14 56.5 4.626e+01 -10.241319 3.0380 -3.371047 -#> ds 5 parent 14 47.0 4.626e+01 -0.741319 3.0380 -0.244014 -#> ds 5 parent 28 30.2 3.026e+01 0.058478 2.0487 0.028544 -#> ds 5 parent 28 23.9 3.026e+01 6.358478 2.0487 3.103661 -#> ds 5 parent 60 17.0 1.792e+01 0.919046 1.3242 0.694024 -#> ds 5 parent 60 18.7 1.792e+01 -0.780954 1.3242 -0.589742 -#> ds 5 parent 90 11.3 1.187e+01 0.573917 1.0066 0.570144 -#> ds 5 parent 90 11.9 1.187e+01 -0.026083 1.0066 -0.025912 -#> ds 5 parent 120 9.0 7.898e+00 -1.102089 0.8307 -1.326622 -#> ds 5 parent 120 8.1 7.898e+00 -0.202089 0.8307 -0.243261 -#> ds 5 m1 0 0.7 -1.421e-14 -0.700000 0.6586 -1.062873 -#> ds 5 m1 1 3.0 3.144e+00 0.143526 0.6887 0.208390 -#> ds 5 m1 1 2.6 3.144e+00 0.543526 0.6887 0.789161 -#> ds 5 m1 3 5.1 8.390e+00 3.290265 0.8504 3.869277 -#> ds 5 m1 3 7.5 8.390e+00 0.890265 0.8504 1.046932 -#> ds 5 m1 7 16.5 1.566e+01 -0.841368 1.2007 -0.700751 -#> ds 5 m1 7 19.0 1.566e+01 -3.341368 1.2007 -2.782928 -#> ds 5 m1 14 22.9 2.188e+01 -1.017753 1.5498 -0.656687 -#> ds 5 m1 14 23.2 2.188e+01 -1.317753 1.5498 -0.850257 -#> ds 5 m1 28 22.2 2.386e+01 1.655914 1.6652 0.994399 -#> ds 5 m1 28 24.4 2.386e+01 -0.544086 1.6652 -0.326731 -#> ds 5 m1 60 15.5 1.859e+01 3.091124 1.3618 2.269915 -#> ds 5 m1 60 19.8 1.859e+01 -1.208876 1.3618 -0.887718 -#> ds 5 m1 90 14.9 1.372e+01 -1.176815 1.0990 -1.070784 -#> ds 5 m1 90 14.2 1.372e+01 -0.476815 1.0990 -0.433854 -#> ds 5 m1 120 10.9 9.961e+00 -0.938796 0.9174 -1.023332 -#> ds 5 m1 120 10.4 9.961e+00 -0.438796 0.9174 -0.478308</div><div class='input'><span class='co'># }</span> +#> ds name time observed predicted residual std standardized +#> ds 1 parent 0 89.8 9.838e+01 -8.584661 7.7094 -1.113536 +#> ds 1 parent 0 104.1 9.838e+01 5.715339 7.7094 0.741350 +#> ds 1 parent 1 88.7 9.388e+01 -5.182489 7.3611 -0.704041 +#> ds 1 parent 1 95.5 9.388e+01 1.617511 7.3611 0.219739 +#> ds 1 parent 3 81.8 8.563e+01 -3.825382 6.7229 -0.569010 +#> ds 1 parent 3 94.5 8.563e+01 8.874618 6.7229 1.320062 +#> ds 1 parent 7 71.5 7.169e+01 -0.188290 5.6482 -0.033336 +#> ds 1 parent 7 70.3 7.169e+01 -1.388290 5.6482 -0.245795 +#> ds 1 parent 14 54.2 5.361e+01 0.586595 4.2624 0.137621 +#> ds 1 parent 14 49.6 5.361e+01 -4.013405 4.2624 -0.941587 +#> ds 1 parent 28 31.5 3.219e+01 -0.688936 2.6496 -0.260011 +#> ds 1 parent 28 28.8 3.219e+01 -3.388936 2.6496 -1.279016 +#> ds 1 parent 60 12.1 1.278e+01 -0.678998 1.3145 -0.516562 +#> ds 1 parent 60 13.6 1.278e+01 0.821002 1.3145 0.624595 +#> ds 1 parent 90 6.2 6.157e+00 0.043461 0.9835 0.044188 +#> ds 1 parent 90 8.3 6.157e+00 2.143461 0.9835 2.179316 +#> ds 1 parent 120 2.2 3.076e+00 -0.876218 0.8916 -0.982775 +#> ds 1 parent 120 2.4 3.076e+00 -0.676218 0.8916 -0.758453 +#> ds 1 m1 1 0.3 1.134e+00 -0.833749 0.8633 -0.965750 +#> ds 1 m1 1 0.2 1.134e+00 -0.933749 0.8633 -1.081583 +#> ds 1 m1 3 2.2 3.157e+00 -0.957400 0.8933 -1.071763 +#> ds 1 m1 3 3.0 3.157e+00 -0.157400 0.8933 -0.176202 +#> ds 1 m1 7 6.5 6.369e+00 0.130995 0.9917 0.132090 +#> ds 1 m1 7 5.0 6.369e+00 -1.369005 0.9917 -1.380438 +#> ds 1 m1 14 10.2 9.971e+00 0.229362 1.1577 0.198112 +#> ds 1 m1 14 9.5 9.971e+00 -0.470638 1.1577 -0.406513 +#> ds 1 m1 28 12.2 1.265e+01 -0.447735 1.3067 -0.342637 +#> ds 1 m1 28 13.4 1.265e+01 0.752265 1.3067 0.575683 +#> ds 1 m1 60 11.8 1.097e+01 0.832027 1.2112 0.686945 +#> ds 1 m1 60 13.2 1.097e+01 2.232027 1.2112 1.842825 +#> ds 1 m1 90 6.6 7.876e+00 -1.275985 1.0553 -1.209109 +#> ds 1 m1 90 9.3 7.876e+00 1.424015 1.0553 1.349381 +#> ds 1 m1 120 3.5 5.336e+00 -1.835829 0.9540 -1.924292 +#> ds 1 m1 120 5.4 5.336e+00 0.064171 0.9540 0.067263 +#> ds 2 parent 0 118.0 1.092e+02 8.812058 8.5459 1.031142 +#> ds 2 parent 0 99.8 1.092e+02 -9.387942 8.5459 -1.098529 +#> ds 2 parent 1 90.2 1.023e+02 -12.114268 8.0135 -1.511724 +#> ds 2 parent 1 94.6 1.023e+02 -7.714268 8.0135 -0.962654 +#> ds 2 parent 3 96.1 9.066e+01 5.436165 7.1122 0.764344 +#> ds 2 parent 3 78.4 9.066e+01 -12.263835 7.1122 -1.724339 +#> ds 2 parent 7 77.9 7.365e+01 4.245773 5.7995 0.732090 +#> ds 2 parent 7 77.7 7.365e+01 4.045773 5.7995 0.697604 +#> ds 2 parent 14 56.0 5.593e+01 0.073803 4.4389 0.016626 +#> ds 2 parent 14 54.7 5.593e+01 -1.226197 4.4389 -0.276236 +#> ds 2 parent 28 36.6 3.892e+01 -2.320837 3.1502 -0.736737 +#> ds 2 parent 28 36.8 3.892e+01 -2.120837 3.1502 -0.673248 +#> ds 2 parent 60 22.1 2.136e+01 0.741020 1.8719 0.395868 +#> ds 2 parent 60 24.7 2.136e+01 3.341020 1.8719 1.784841 +#> ds 2 parent 90 12.4 1.251e+01 -0.113999 1.2989 -0.087765 +#> ds 2 parent 90 10.8 1.251e+01 -1.713999 1.2989 -1.319575 +#> ds 2 parent 120 6.8 7.338e+00 -0.537708 1.0315 -0.521281 +#> ds 2 parent 120 7.9 7.338e+00 0.562292 1.0315 0.545113 +#> ds 2 m1 1 1.3 1.576e+00 -0.276176 0.8675 -0.318352 +#> ds 2 m1 3 3.7 4.177e+00 -0.476741 0.9183 -0.519146 +#> ds 2 m1 3 4.7 4.177e+00 0.523259 0.9183 0.569801 +#> ds 2 m1 7 8.1 7.724e+00 0.376365 1.0485 0.358970 +#> ds 2 m1 7 7.9 7.724e+00 0.176365 1.0485 0.168214 +#> ds 2 m1 14 10.1 1.077e+01 -0.674433 1.2006 -0.561738 +#> ds 2 m1 14 10.3 1.077e+01 -0.474433 1.2006 -0.395158 +#> ds 2 m1 28 10.7 1.212e+01 -1.416179 1.2758 -1.110010 +#> ds 2 m1 28 12.2 1.212e+01 0.083821 1.2758 0.065699 +#> ds 2 m1 60 10.7 1.041e+01 0.294930 1.1807 0.249793 +#> ds 2 m1 60 12.5 1.041e+01 2.094930 1.1807 1.774316 +#> ds 2 m1 90 9.1 8.079e+00 1.020859 1.0646 0.958929 +#> ds 2 m1 90 7.4 8.079e+00 -0.679141 1.0646 -0.637941 +#> ds 2 m1 120 6.1 5.968e+00 0.131673 0.9765 0.134843 +#> ds 2 m1 120 4.5 5.968e+00 -1.468327 0.9765 -1.503683 +#> ds 3 parent 0 106.2 1.036e+02 2.638248 8.1101 0.325303 +#> ds 3 parent 0 106.9 1.036e+02 3.338248 8.1101 0.411614 +#> ds 3 parent 1 107.4 9.580e+01 11.600063 7.5094 1.544743 +#> ds 3 parent 1 96.1 9.580e+01 0.300063 7.5094 0.039958 +#> ds 3 parent 3 79.4 8.297e+01 -3.574516 6.5182 -0.548391 +#> ds 3 parent 3 82.6 8.297e+01 -0.374516 6.5182 -0.057457 +#> ds 3 parent 7 63.9 6.517e+01 -1.272397 5.1472 -0.247200 +#> ds 3 parent 7 62.4 6.517e+01 -2.772397 5.1472 -0.538618 +#> ds 3 parent 14 51.0 4.821e+01 2.790075 3.8512 0.724475 +#> ds 3 parent 14 47.1 4.821e+01 -1.109925 3.8512 -0.288205 +#> ds 3 parent 28 36.1 3.385e+01 2.250573 2.7723 0.811811 +#> ds 3 parent 28 36.6 3.385e+01 2.750573 2.7723 0.992168 +#> ds 3 parent 60 20.1 1.964e+01 0.455700 1.7543 0.259760 +#> ds 3 parent 60 19.8 1.964e+01 0.155700 1.7543 0.088753 +#> ds 3 parent 90 11.3 1.210e+01 -0.795458 1.2746 -0.624068 +#> ds 3 parent 90 10.7 1.210e+01 -1.395458 1.2746 -1.094792 +#> ds 3 parent 120 8.2 7.451e+00 0.749141 1.0364 0.722816 +#> ds 3 parent 120 7.3 7.451e+00 -0.150859 1.0364 -0.145558 +#> ds 3 m1 0 0.8 3.695e-13 0.800000 0.8588 0.931542 +#> ds 3 m1 1 1.8 1.740e+00 0.059741 0.8694 0.068714 +#> ds 3 m1 1 2.3 1.740e+00 0.559741 0.8694 0.643812 +#> ds 3 m1 3 4.2 4.531e+00 -0.331379 0.9285 -0.356913 +#> ds 3 m1 3 4.1 4.531e+00 -0.431379 0.9285 -0.464618 +#> ds 3 m1 7 6.8 8.113e+00 -1.312762 1.0661 -1.231333 +#> ds 3 m1 7 10.1 8.113e+00 1.987238 1.0661 1.863971 +#> ds 3 m1 14 11.4 1.079e+01 0.613266 1.2013 0.510507 +#> ds 3 m1 14 12.8 1.079e+01 2.013266 1.2013 1.675923 +#> ds 3 m1 28 11.5 1.133e+01 0.174252 1.2310 0.141553 +#> ds 3 m1 28 10.6 1.133e+01 -0.725748 1.2310 -0.589558 +#> ds 3 m1 60 7.5 8.948e+00 -1.448281 1.1059 -1.309561 +#> ds 3 m1 60 8.6 8.948e+00 -0.348281 1.1059 -0.314922 +#> ds 3 m1 90 7.3 6.665e+00 0.634932 1.0034 0.632752 +#> ds 3 m1 90 8.1 6.665e+00 1.434932 1.0034 1.430004 +#> ds 3 m1 120 5.3 4.795e+00 0.504936 0.9365 0.539199 +#> ds 3 m1 120 3.8 4.795e+00 -0.995064 0.9365 -1.062586 +#> ds 4 parent 0 104.7 9.985e+01 4.850494 7.8227 0.620050 +#> ds 4 parent 0 88.3 9.985e+01 -11.549506 7.8227 -1.476402 +#> ds 4 parent 1 94.2 9.676e+01 -2.556304 7.5834 -0.337093 +#> ds 4 parent 1 94.6 9.676e+01 -2.156304 7.5834 -0.284346 +#> ds 4 parent 3 78.1 9.092e+01 -12.817485 7.1318 -1.797230 +#> ds 4 parent 3 96.5 9.092e+01 5.582515 7.1318 0.782764 +#> ds 4 parent 7 76.2 8.050e+01 -4.297338 6.3270 -0.679204 +#> ds 4 parent 7 77.8 8.050e+01 -2.697338 6.3270 -0.426320 +#> ds 4 parent 14 70.8 6.562e+01 5.179989 5.1816 0.999687 +#> ds 4 parent 14 67.3 6.562e+01 1.679989 5.1816 0.324222 +#> ds 4 parent 28 43.1 4.499e+01 -1.886936 3.6069 -0.523140 +#> ds 4 parent 28 45.1 4.499e+01 0.113064 3.6069 0.031346 +#> ds 4 parent 60 21.3 2.151e+01 -0.214840 1.8827 -0.114114 +#> ds 4 parent 60 23.5 2.151e+01 1.985160 1.8827 1.054433 +#> ds 4 parent 90 11.8 1.190e+01 -0.098528 1.2633 -0.077990 +#> ds 4 parent 90 12.1 1.190e+01 0.201472 1.2633 0.159475 +#> ds 4 parent 120 7.0 6.886e+00 0.113832 1.0125 0.112431 +#> ds 4 parent 120 6.2 6.886e+00 -0.686168 1.0125 -0.677724 +#> ds 4 m1 0 1.6 4.263e-14 1.600000 0.8588 1.863085 +#> ds 4 m1 1 0.9 7.140e-01 0.185984 0.8606 0.216112 +#> ds 4 m1 3 3.7 2.022e+00 1.678243 0.8731 1.922160 +#> ds 4 m1 3 2.0 2.022e+00 -0.021757 0.8731 -0.024919 +#> ds 4 m1 7 3.6 4.207e+00 -0.607229 0.9192 -0.660633 +#> ds 4 m1 7 3.8 4.207e+00 -0.407229 0.9192 -0.443044 +#> ds 4 m1 14 7.1 6.912e+00 0.188339 1.0135 0.185828 +#> ds 4 m1 14 6.6 6.912e+00 -0.311661 1.0135 -0.307506 +#> ds 4 m1 28 9.5 9.449e+00 0.050714 1.1309 0.044843 +#> ds 4 m1 28 9.3 9.449e+00 -0.149286 1.1309 -0.132004 +#> ds 4 m1 60 8.3 8.997e+00 -0.697403 1.1083 -0.629230 +#> ds 4 m1 60 9.0 8.997e+00 0.002597 1.1083 0.002343 +#> ds 4 m1 90 6.6 6.697e+00 -0.096928 1.0047 -0.096472 +#> ds 4 m1 90 7.7 6.697e+00 1.003072 1.0047 0.998348 +#> ds 4 m1 120 3.7 4.622e+00 -0.921607 0.9312 -0.989749 +#> ds 4 m1 120 3.5 4.622e+00 -1.121607 0.9312 -1.204537 +#> ds 5 parent 0 110.4 1.045e+02 5.942426 8.1795 0.726502 +#> ds 5 parent 0 112.1 1.045e+02 7.642426 8.1795 0.934338 +#> ds 5 parent 1 93.5 9.739e+01 -3.893915 7.6327 -0.510162 +#> ds 5 parent 1 91.0 9.739e+01 -6.393915 7.6327 -0.837700 +#> ds 5 parent 3 71.0 8.519e+01 -14.188275 6.6891 -2.121098 +#> ds 5 parent 3 89.7 8.519e+01 4.511725 6.6891 0.674487 +#> ds 5 parent 7 60.4 6.684e+01 -6.439546 5.2753 -1.220701 +#> ds 5 parent 7 59.1 6.684e+01 -7.739546 5.2753 -1.467133 +#> ds 5 parent 14 56.5 4.736e+01 9.138979 3.7868 2.413407 +#> ds 5 parent 14 47.0 4.736e+01 -0.361021 3.7868 -0.095338 +#> ds 5 parent 28 30.2 3.033e+01 -0.131178 2.5132 -0.052195 +#> ds 5 parent 28 23.9 3.033e+01 -6.431178 2.5132 -2.558936 +#> ds 5 parent 60 17.0 1.771e+01 -0.705246 1.6243 -0.434177 +#> ds 5 parent 60 18.7 1.771e+01 0.994754 1.6243 0.612409 +#> ds 5 parent 90 11.3 1.180e+01 -0.504856 1.2580 -0.401315 +#> ds 5 parent 90 11.9 1.180e+01 0.095144 1.2580 0.075631 +#> ds 5 parent 120 9.0 7.917e+00 1.083499 1.0571 1.024928 +#> ds 5 parent 120 8.1 7.917e+00 0.183499 1.0571 0.173579 +#> ds 5 m1 0 0.7 3.553e-15 0.700000 0.8588 0.815100 +#> ds 5 m1 1 3.0 3.204e+00 -0.204414 0.8943 -0.228572 +#> ds 5 m1 1 2.6 3.204e+00 -0.604414 0.8943 -0.675845 +#> ds 5 m1 3 5.1 8.586e+00 -3.485889 1.0884 -3.202858 +#> ds 5 m1 3 7.5 8.586e+00 -1.085889 1.0884 -0.997722 +#> ds 5 m1 7 16.5 1.612e+01 0.376855 1.5211 0.247743 +#> ds 5 m1 7 19.0 1.612e+01 2.876855 1.5211 1.891237 +#> ds 5 m1 14 22.9 2.267e+01 0.228264 1.9633 0.116267 +#> ds 5 m1 14 23.2 2.267e+01 0.528264 1.9633 0.269072 +#> ds 5 m1 28 22.2 2.468e+01 -2.480178 2.1050 -1.178211 +#> ds 5 m1 28 24.4 2.468e+01 -0.280178 2.1050 -0.133099 +#> ds 5 m1 60 15.5 1.860e+01 -3.099615 1.6838 -1.840794 +#> ds 5 m1 60 19.8 1.860e+01 1.200385 1.6838 0.712883 +#> ds 5 m1 90 14.9 1.326e+01 1.636345 1.3433 1.218195 +#> ds 5 m1 90 14.2 1.326e+01 0.936345 1.3433 0.697072 +#> ds 5 m1 120 10.9 9.348e+00 1.551535 1.1258 1.378133 +#> ds 5 m1 120 10.4 9.348e+00 1.051535 1.1258 0.934014</div><div class='input'><span class='co'># }</span> </div></pre> </div> diff --git a/docs/dev/reference/synthetic_data_for_UBA_2014-1.png b/docs/dev/reference/synthetic_data_for_UBA_2014-1.png Binary files differindex 351b21aa..89975db5 100644 --- a/docs/dev/reference/synthetic_data_for_UBA_2014-1.png +++ b/docs/dev/reference/synthetic_data_for_UBA_2014-1.png diff --git a/docs/dev/reference/synthetic_data_for_UBA_2014.html b/docs/dev/reference/synthetic_data_for_UBA_2014.html index 1edc7c1e..33a0ace2 100644 --- a/docs/dev/reference/synthetic_data_for_UBA_2014.html +++ b/docs/dev/reference/synthetic_data_for_UBA_2014.html @@ -87,7 +87,7 @@ Compare also the code in the example section to see the degradation models." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -136,7 +136,7 @@ Compare also the code in the example section to see the degradation models." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -297,10 +297,10 @@ Compare also the code in the example section to see the degradation models." /> quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> </div><div class='img'><img src='synthetic_data_for_UBA_2014-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='output co'>#> mkin version used for fitting: 0.9.50.4 +</div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Nov 30 16:01:42 2020 -#> Date of summary: Mon Nov 30 16:01:42 2020 +#> Date of fit: Mon Feb 15 17:13:29 2021 +#> Date of summary: Mon Feb 15 17:13:29 2021 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -309,7 +309,7 @@ Compare also the code in the example section to see the degradation models." /> #> #> Model predictions using solution type deSolve #> -#> Fitted using 822 model solutions performed in 0.652 s +#> Fitted using 833 model solutions performed in 0.649 s #> #> Error model: Constant variance #> @@ -361,15 +361,15 @@ Compare also the code in the example section to see the degradation models." /> #> log_k_M2 2.819e-02 7.166e-02 -3.929e-01 1.000e+00 -2.658e-01 #> f_parent_qlogis -4.624e-01 -5.682e-01 7.478e-01 -2.658e-01 1.000e+00 #> f_M1_qlogis 1.614e-01 4.102e-01 -8.109e-01 5.419e-01 -8.605e-01 -#> sigma -7.941e-08 -9.143e-09 -1.268e-08 5.947e-08 5.657e-08 +#> sigma -2.900e-08 -8.030e-09 -2.741e-08 3.938e-08 -2.681e-08 #> f_M1_qlogis sigma -#> parent_0 1.614e-01 -7.941e-08 -#> log_k_parent 4.102e-01 -9.143e-09 -#> log_k_M1 -8.109e-01 -1.268e-08 -#> log_k_M2 5.419e-01 5.947e-08 -#> f_parent_qlogis -8.605e-01 5.657e-08 -#> f_M1_qlogis 1.000e+00 -2.382e-10 -#> sigma -2.382e-10 1.000e+00 +#> parent_0 1.614e-01 -2.900e-08 +#> log_k_parent 4.102e-01 -8.030e-09 +#> log_k_M1 -8.109e-01 -2.741e-08 +#> log_k_M2 5.419e-01 3.938e-08 +#> f_parent_qlogis -8.605e-01 -2.681e-08 +#> f_M1_qlogis 1.000e+00 4.971e-08 +#> sigma 4.971e-08 1.000e+00 #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. @@ -416,7 +416,7 @@ Compare also the code in the example section to see the degradation models." /> #> 7 parent 0.3 5.772e-01 -0.27717 #> 14 parent 3.5 3.264e-03 3.49674 #> 28 parent 3.2 1.045e-07 3.20000 -#> 90 parent 0.6 9.532e-10 0.60000 +#> 90 parent 0.6 9.530e-10 0.60000 #> 120 parent 3.5 -5.940e-10 3.50000 #> 1 M1 36.4 3.479e+01 1.61088 #> 1 M1 37.4 3.479e+01 2.61088 @@ -427,7 +427,7 @@ Compare also the code in the example section to see the degradation models." /> #> 14 M1 5.8 1.995e+00 3.80469 #> 14 M1 1.2 1.995e+00 -0.79531 #> 60 M1 0.5 2.111e-06 0.50000 -#> 90 M1 3.2 -9.671e-10 3.20000 +#> 90 M1 3.2 -9.670e-10 3.20000 #> 120 M1 1.5 7.670e-10 1.50000 #> 120 M1 0.6 7.670e-10 0.60000 #> 1 M2 4.8 4.455e+00 0.34517 diff --git a/docs/dev/reference/test_data_from_UBA_2014-1.png b/docs/dev/reference/test_data_from_UBA_2014-1.png Binary files differindex 9e0afad2..7bf0bd0f 100644 --- a/docs/dev/reference/test_data_from_UBA_2014-1.png +++ b/docs/dev/reference/test_data_from_UBA_2014-1.png diff --git a/docs/dev/reference/test_data_from_UBA_2014-2.png b/docs/dev/reference/test_data_from_UBA_2014-2.png Binary files differindex e889efde..fc1f77e0 100644 --- a/docs/dev/reference/test_data_from_UBA_2014-2.png +++ b/docs/dev/reference/test_data_from_UBA_2014-2.png diff --git a/docs/dev/reference/test_data_from_UBA_2014.html b/docs/dev/reference/test_data_from_UBA_2014.html index 89ec3480..539b8287 100644 --- a/docs/dev/reference/test_data_from_UBA_2014.html +++ b/docs/dev/reference/test_data_from_UBA_2014.html @@ -73,7 +73,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -122,7 +122,7 @@ <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -203,25 +203,25 @@ </div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>f_soil</span>, lpos <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"topright"</span>, <span class='st'>"topright"</span>, <span class='st'>"topright"</span>, <span class='st'>"bottomright"</span><span class='op'>)</span><span class='op'>)</span> </div><div class='img'><img src='test_data_from_UBA_2014-2.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_soil</span><span class='op'>)</span><span class='op'>$</span><span class='va'>bpar</span> </div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower -#> parent_0 76.55425649 0.859186399 89.1008710 1.113861e-26 74.755959406 +#> parent_0 76.55425650 0.859186399 89.1008710 1.113861e-26 74.755959418 #> k_parent 0.12081956 0.004601918 26.2541722 1.077359e-16 0.111561575 -#> k_M1 0.84258614 0.806159820 1.0451850 1.545267e-01 0.113779670 -#> k_M2 0.04210880 0.017083035 2.4649483 1.170188e-02 0.018013857 -#> k_M3 0.01122918 0.007245855 1.5497385 6.885052e-02 0.002909431 -#> f_parent_to_M1 0.32240200 0.240783909 1.3389682 9.819073e-02 NA -#> f_parent_to_M2 0.16099855 0.033691953 4.7785463 6.531137e-05 NA -#> f_M1_to_M3 0.27921507 0.269423745 1.0363417 1.565266e-01 0.022978220 -#> f_M2_to_M3 0.55641253 0.595119954 0.9349586 1.807707e-01 0.008002509 +#> k_M1 0.84258615 0.806160102 1.0451846 1.545268e-01 0.113779609 +#> k_M2 0.04210880 0.017083034 2.4649483 1.170188e-02 0.018013857 +#> k_M3 0.01122918 0.007245856 1.5497385 6.885052e-02 0.002909431 +#> f_parent_to_M1 0.32240200 0.240783943 1.3389680 9.819076e-02 NA +#> f_parent_to_M2 0.16099855 0.033691952 4.7785464 6.531136e-05 NA +#> f_M1_to_M3 0.27921507 0.269423780 1.0363416 1.565267e-01 0.022978205 +#> f_M2_to_M3 0.55641252 0.595119966 0.9349586 1.807707e-01 0.008002509 #> sigma 1.14005399 0.149696423 7.6157731 1.727024e-07 0.826735778 #> Upper -#> parent_0 78.35255357 +#> parent_0 78.35255358 #> k_parent 0.13084582 -#> k_M1 6.23970352 +#> k_M1 6.23970702 #> k_M2 0.09843260 #> k_M3 0.04333992 #> f_parent_to_M1 NA #> f_parent_to_M2 NA -#> f_M1_to_M3 0.86450768 +#> f_M1_to_M3 0.86450775 #> f_M2_to_M3 0.99489895 #> sigma 1.45337221</div><div class='input'> <span class='fu'><a href='mkinerrmin.html'>mkinerrmin</a></span><span class='op'>(</span><span class='va'>f_soil</span><span class='op'>)</span> </div><div class='output co'>#> err.min n.optim df diff --git a/docs/dev/reference/tffm0.html b/docs/dev/reference/tffm0.html new file mode 100644 index 00000000..67f26b85 --- /dev/null +++ b/docs/dev/reference/tffm0.html @@ -0,0 +1,226 @@ +<!-- Generated by pkgdown: do not edit by hand --> +<!DOCTYPE html> +<html lang="en"> + <head> + <meta charset="utf-8"> +<meta http-equiv="X-UA-Compatible" content="IE=edge"> +<meta name="viewport" content="width=device-width, initial-scale=1.0"> + +<title>Transform formation fractions as in the first published mkin version — tffm0 • mkin</title> + + +<!-- jquery --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script> +<!-- Bootstrap --> + +<link rel="stylesheet" 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Therefore this transformation was used originally in mkin. It +was later replaced by the ilr transformation because the ilr transformed +fractions can assumed to follow normal distribution. As the ilr +transformation is not available in RxODE and can therefore not be used in +the nlmixr modelling language, this transformation is currently used for +translating mkin models with formation fractions to more than one target +compartment for fitting with nlmixr in nlmixr_model. However, +this implementation cannot be used there, as it is not accessible +from RxODE." /> + + +<meta name="robots" content="noindex"> + +<!-- mathjax --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> + +<!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--> + + + + </head> + + <body data-spy="scroll" data-target="#toc"> + <div class="container template-reference-topic"> + <header> + <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"> + <li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"> + <li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul> +</li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul> + <ul class="nav navbar-nav navbar-right"> + <li> + <a href="https://github.com/jranke/mkin/"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul> + + </div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header> + +<div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Transform formation fractions as in the first published mkin version</h1> + <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/tffm0.R'><code>R/tffm0.R</code></a></small> + <div class="hidden name"><code>tffm0.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The transformed fractions can be restricted between 0 and 1 in model +optimisations. Therefore this transformation was used originally in mkin. It +was later replaced by the <a href='ilr.html'>ilr</a> transformation because the ilr transformed +fractions can assumed to follow normal distribution. As the ilr +transformation is not available in RxODE and can therefore not be used in +the nlmixr modelling language, this transformation is currently used for +translating mkin models with formation fractions to more than one target +compartment for fitting with nlmixr in <a href='nlmixr.mmkin.html'>nlmixr_model</a>. However, +this implementation cannot be used there, as it is not accessible +from RxODE.</p> + </div> + + <pre class="usage"><span class='fu'>tffm0</span><span class='op'>(</span><span class='va'>ff</span><span class='op'>)</span> + +<span class='fu'>invtffm0</span><span class='op'>(</span><span class='va'>ff_trans</span><span class='op'>)</span></pre> + + <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>ff</th> + <td><p>Vector of untransformed formation fractions. The sum +must be smaller or equal to one</p></td> + </tr> + <tr> + <th>ff_trans</th> + <td><p>Vector of transformed formation fractions that can be +restricted to the interval from 0 to 1</p></td> + </tr> + </table> + + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>A vector of the transformed formation fractions</p> +<p>A vector of backtransformed formation fractions for natural use in degradation models</p> + + <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> + <pre class="examples"><div class='input'><span class='va'>ff_example</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span> + <span class='fl'>0.10983681</span>, <span class='fl'>0.09035905</span>, <span class='fl'>0.08399383</span> +<span class='op'>)</span> +<span class='va'>ff_example_trans</span> <span class='op'><-</span> <span class='fu'>tffm0</span><span class='op'>(</span><span class='va'>ff_example</span><span class='op'>)</span> +<span class='fu'>invtffm0</span><span class='op'>(</span><span class='va'>ff_example_trans</span><span class='op'>)</span> +</div><div class='output co'>#> [1] 0.10983681 0.09035905 0.08399383</div></pre> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"> + <h2 data-toc-skip>Contents</h2> + </nav> + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + diff --git a/docs/dev/reference/transform_odeparms.html b/docs/dev/reference/transform_odeparms.html index 46b66073..75d6a1f9 100644 --- a/docs/dev/reference/transform_odeparms.html +++ b/docs/dev/reference/transform_odeparms.html @@ -77,7 +77,7 @@ the ilr transformation is used." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -126,7 +126,7 @@ the ilr transformation is used." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> @@ -231,50 +231,64 @@ This is no problem for the internal use in <a href='mkinfit.html'>mkinfit</a>.</ <pre class="examples"><div class='input'> <span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span>, sink <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='co'># Fit the model to the FOCUS example dataset D using defaults</span> -<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> + m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"min"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> +<span class='co'># Fit the model to the FOCUS example dataset D using defaults</span> +<span class='va'>FOCUS_D</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='co'># remove zero values to avoid warning</span> +<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> <span class='co'># Transformed and backtransformed parameters</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> Estimate Std. Error Lower Upper -#> parent_0 99.5985 1.5702 96.404 102.79 -#> log_k_parent -2.3157 0.0409 -2.399 -2.23 -#> log_k_m1 -5.2475 0.1332 -5.518 -4.98 -#> f_parent_qlogis 0.0579 0.0893 -0.124 0.24 -#> sigma 3.1255 0.3585 2.396 3.85</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper -#> parent_0 99.59848 1.57022 63.43 2.30e-36 96.40383 102.7931 -#> k_parent 0.09870 0.00403 24.47 4.96e-23 0.09082 0.1073 -#> k_m1 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069 -#> f_parent_to_m1 0.51448 0.02230 23.07 3.10e-22 0.46912 0.5596 -#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'> +</div><div class='output co'>#> Estimate Std. Error Lower Upper +#> parent_0 99.60 1.5702 96.40 102.79 +#> log_k_parent_sink -3.04 0.0763 -3.19 -2.88 +#> log_k_parent_m1 -2.98 0.0403 -3.06 -2.90 +#> log_k_m1_sink -5.25 0.1332 -5.52 -4.98 +#> sigma 3.13 0.3585 2.40 3.85</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper +#> parent_0 99.59848 1.57022 63.43 2.30e-36 96.40384 102.7931 +#> k_parent_sink 0.04792 0.00365 13.11 6.13e-15 0.04103 0.0560 +#> k_parent_m1 0.05078 0.00205 24.80 3.27e-23 0.04678 0.0551 +#> k_m1_sink 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069 +#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'> <span class='co'># \dontrun{</span> -<span class='co'># Compare to the version without transforming rate parameters</span> -<span class='va'>fit.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, transform_rates <span class='op'>=</span> <span class='cn'>FALSE</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#> <span class='error'>Error in if (cost < cost.current) { assign("cost.current", cost, inherits = TRUE) if (!quiet) cat(ifelse(OLS, "Sum of squared residuals", "Negative log-likelihood"), " at call ", calls, ": ", signif(cost.current, 6), "\n", sep = "")}: missing value where TRUE/FALSE needed</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.006 0 0.005</span></div><div class='input'><span class='va'>fit.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'fit.2' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found</span></div><div class='input'><span class='co'># }</span> +<span class='co'># Compare to the version without transforming rate parameters (does not work</span> +<span class='co'># with analytical solution, we get NA values for m1 in predictions)</span> +<span class='va'>fit.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, transform_rates <span class='op'>=</span> <span class='cn'>FALSE</span>, + solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate Std. Error Lower Upper +#> parent_0 99.59848 1.57022 96.40384 1.03e+02 +#> k_parent_sink 0.04792 0.00365 0.04049 5.54e-02 +#> k_parent_m1 0.05078 0.00205 0.04661 5.49e-02 +#> k_m1_sink 0.00526 0.00070 0.00384 6.69e-03 +#> sigma 3.12550 0.35852 2.39609 3.85e+00</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper +#> parent_0 99.59848 1.57022 63.43 2.30e-36 96.40384 1.03e+02 +#> k_parent_sink 0.04792 0.00365 13.11 6.13e-15 0.04049 5.54e-02 +#> k_parent_m1 0.05078 0.00205 24.80 3.27e-23 0.04661 5.49e-02 +#> k_m1_sink 0.00526 0.00070 7.51 6.16e-09 0.00384 6.69e-03 +#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.85e+00</div><div class='input'><span class='co'># }</span> <span class='va'>initials</span> <span class='op'><-</span> <span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>$</span><span class='va'>value</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>initials</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>)</span> <span class='va'>transformed</span> <span class='op'><-</span> <span class='va'>fit</span><span class='op'>$</span><span class='va'>start_transformed</span><span class='op'>$</span><span class='va'>value</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>transformed</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>start_transformed</span><span class='op'>)</span> <span class='fu'>transform_odeparms</span><span class='op'>(</span><span class='va'>initials</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 log_k_parent log_k_m1 f_parent_qlogis -#> 100.750000 -2.302585 -2.301586 0.000000 </div><div class='input'><span class='fu'>backtransform_odeparms</span><span class='op'>(</span><span class='va'>transformed</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 k_parent k_m1 f_parent_to_m1 -#> 100.7500 0.1000 0.1001 0.5000 </div><div class='input'> +</div><div class='output co'>#> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink +#> 100.750000 -2.302585 -2.301586 -2.300587 </div><div class='input'><span class='fu'>backtransform_odeparms</span><span class='op'>(</span><span class='va'>transformed</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> +</div><div class='output co'>#> parent_0 k_parent_sink k_parent_m1 k_m1_sink +#> 100.7500 0.1000 0.1001 0.1002 </div><div class='input'> <span class='co'># \dontrun{</span> -<span class='co'># The case of formation fractions</span> +<span class='co'># The case of formation fractions (this is now the default)</span> <span class='va'>SFO_SFO.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span>, sink <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> -<span class='va'>fit.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.ff.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff</span><span class='op'>)</span> +<span class='va'>fit.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.ff.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.ff.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> </div><div class='output co'>#> Estimate Std. Error Lower Upper #> parent_0 99.5985 1.5702 96.404 102.79 @@ -299,8 +313,8 @@ This is no problem for the internal use in <a href='mkinfit.html'>mkinfit</a>.</ use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> -<span class='va'>fit.ff.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff.2</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.ff.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff.2</span><span class='op'>)</span> +<span class='va'>fit.ff.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff.2</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.ff.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff.2</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.ff.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> </div><div class='output co'>#> Estimate Std. Error Lower Upper #> parent_0 84.79 3.012 78.67 90.91 diff --git a/docs/dev/reference/update.mkinfit-1.png b/docs/dev/reference/update.mkinfit-1.png Binary files differindex 7d2f1bdb..df8473c1 100644 --- a/docs/dev/reference/update.mkinfit-1.png +++ b/docs/dev/reference/update.mkinfit-1.png diff --git a/docs/dev/reference/update.mkinfit-2.png b/docs/dev/reference/update.mkinfit-2.png Binary files differindex 8dcabcdc..13c99b44 100644 --- a/docs/dev/reference/update.mkinfit-2.png +++ b/docs/dev/reference/update.mkinfit-2.png diff --git a/docs/dev/reference/update.mkinfit.html b/docs/dev/reference/update.mkinfit.html index 10a93373..83f45028 100644 --- a/docs/dev/reference/update.mkinfit.html +++ b/docs/dev/reference/update.mkinfit.html @@ -75,7 +75,7 @@ override these starting values." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> </span> </div> @@ -124,7 +124,7 @@ override these starting values." /> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin/"> - <span class="fab fa fab fa-github fa-lg"></span> + <span class="fab fa-github fa-lg"></span> </a> </li> |
