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-rw-r--r--docs/dev/reference/saem.html527
1 files changed, 281 insertions, 246 deletions
diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html
index 59589378..620173b2 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">1.0.5</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'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:41:42 2021"
+#&gt; [1] "Wed Aug 4 16:22:05 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:41:43 2021"</div><div class='input'>
+#&gt; [1] "Wed Aug 4 16:22:06 2021"</div><div class='input'>
<span class='va'>f_mmkin_parent</span> <span class='op'>&lt;-</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'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:41:45 2021"
+#&gt; [1] "Wed Aug 4 16:22:08 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:41:46 2021"</div><div class='input'><span class='va'>f_saem_fomc</span> <span class='op'>&lt;-</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>
+#&gt; [1] "Wed Aug 4 16:22:10 2021"</div><div class='input'><span class='va'>f_saem_fomc</span> <span class='op'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:41:47 2021"
+#&gt; [1] "Wed Aug 4 16:22:10 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:41:49 2021"</div><div class='input'><span class='va'>f_saem_dfop</span> <span class='op'>&lt;-</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>
+#&gt; [1] "Wed Aug 4 16:22:12 2021"</div><div class='input'><span class='va'>f_saem_dfop</span> <span class='op'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:41:49 2021"
+#&gt; [1] "Wed Aug 4 16:22:12 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:41:52 2021"</div><div class='input'>
+#&gt; [1] "Wed Aug 4 16:22:16 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'>#&gt; <span class='message'>Package saemix, version 3.1.9000</span>
-#&gt; <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'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; <span class='error'>Error in compare.saemix(list(f_saem_sfo$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'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
+#&gt; <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='output co'>#&gt; <span class='message'></span>
+#&gt; <span class='message'>Attaching package: ‘saemix’</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:RxODE’:</span>
+#&gt; <span class='message'></span>
+#&gt; <span class='message'> phi</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='va'>f_saem_sfo</span><span class='op'>$</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'>#&gt; <span class='message'>Likelihoods calculated by importance sampling</span></div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 624.2484 622.2956
+#&gt; 2 467.7096 464.9757
+#&gt; 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'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Plotting convergence plots</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</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'>#&gt; 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'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"npde"</span><span class='op'>)</span>
</div><div class='img'><img src='saem-2.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Simulating data using nsim = 1000 simulated datasets
@@ -324,11 +357,13 @@ using <a href='mmkin.html'>mmkin</a>.</p>
<span class='va'>f_mmkin_parent_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span>
<span class='va'>f_saem_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:41:55 2021"
+#&gt; [1] "Wed Aug 4 16:22:19 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:42:00 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc_tc</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; <span class='error'>Error in compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)): 'compare.saemix' requires at least two models.</span></div><div class='input'>
+#&gt; [1] "Wed Aug 4 16:22:24 2021"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</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'>#&gt; <span class='message'>Likelihoods calculated by importance sampling</span></div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 467.7096 464.9757
+#&gt; 2 469.6831 466.5586</div><div class='input'>
<span class='va'>sfo_sfo</span> <span class='op'>&lt;-</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'>#&gt; <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fomc_sfo</span> <span class='op'>&lt;-</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'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:42:02 2021"
+#&gt; [1] "Wed Aug 4 16:22:27 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [1] "Mon Jan 25 14:42:07 2021"</div><div class='input'><span class='va'>f_saem_dfop_sfo</span> <span class='op'>&lt;-</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>
+#&gt; [1] "Wed Aug 4 16:22:32 2021"</div><div class='input'><span class='va'>f_saem_dfop_sfo</span> <span class='op'>&lt;-</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'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Mon Jan 25 14:42:08 2021"
+#&gt; [1] "Wed Aug 4 16:22:33 2021"
#&gt; ....
#&gt; Minimisation finished
-#&gt; [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>
+#&gt; [1] "Wed Aug 4 16:22:42 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'>#&gt; Kinetic nonlinear mixed-effects model fit by SAEM
#&gt; Structural model:
@@ -370,35 +405,35 @@ using <a href='mmkin.html'>mmkin</a>.</p>
#&gt;
#&gt; Likelihood computed by importance sampling
#&gt; AIC BIC logLik
-#&gt; 841.6 836.5 -407.8
+#&gt; 839.6 834.6 -406.8
#&gt;
#&gt; Fitted parameters:
#&gt; estimate lower upper
-#&gt; parent_0 93.76647 91.15312 96.3798
-#&gt; log_k_A1 -6.13235 -8.45788 -3.8068
-#&gt; f_parent_qlogis -0.97364 -1.36940 -0.5779
-#&gt; log_k1 -2.53176 -3.80372 -1.2598
-#&gt; log_k2 -3.58667 -5.29524 -1.8781
-#&gt; g_qlogis 0.01238 -1.07968 1.1044
-#&gt; Var.parent_0 7.61106 -3.34955 18.5717
-#&gt; Var.log_k_A1 4.64679 -2.73133 12.0249
-#&gt; Var.f_parent_qlogis 0.19693 -0.05498 0.4488
-#&gt; Var.log_k1 2.01717 -0.51980 4.5542
-#&gt; Var.log_k2 3.63412 -0.92964 8.1979
-#&gt; Var.g_qlogis 0.20045 -0.97425 1.3751
-#&gt; a.1 1.88335 1.66636 2.1004
-#&gt; SD.parent_0 2.75881 0.77234 4.7453
-#&gt; SD.log_k_A1 2.15564 0.44429 3.8670
-#&gt; SD.f_parent_qlogis 0.44377 0.15994 0.7276
-#&gt; SD.log_k1 1.42027 0.52714 2.3134
-#&gt; SD.log_k2 1.90634 0.70934 3.1033
-#&gt; 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>
+#&gt; parent_0 93.80521 91.22487 96.3856
+#&gt; log_k_A1 -6.06244 -8.26517 -3.8597
+#&gt; f_parent_qlogis -0.97319 -1.37024 -0.5761
+#&gt; log_k1 -2.55394 -4.00815 -1.0997
+#&gt; log_k2 -3.47160 -5.18763 -1.7556
+#&gt; g_qlogis -0.09324 -1.42737 1.2409
+#&gt; Var.parent_0 7.42157 -3.25683 18.1000
+#&gt; Var.log_k_A1 4.22850 -2.46339 10.9204
+#&gt; Var.f_parent_qlogis 0.19803 -0.05541 0.4515
+#&gt; Var.log_k1 2.28644 -0.86079 5.4337
+#&gt; Var.log_k2 3.35626 -1.14639 7.8589
+#&gt; Var.g_qlogis 0.20084 -1.32516 1.7268
+#&gt; a.1 1.88399 1.66794 2.1000
+#&gt; SD.parent_0 2.72425 0.76438 4.6841
+#&gt; SD.log_k_A1 2.05633 0.42919 3.6835
+#&gt; SD.f_parent_qlogis 0.44501 0.16025 0.7298
+#&gt; SD.log_k1 1.51210 0.47142 2.5528
+#&gt; SD.log_k2 1.83201 0.60313 3.0609
+#&gt; 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'>#&gt; saemix version used for fitting: 3.1.9000
-#&gt; mkin version used for pre-fitting: 0.9.50.4
-#&gt; R version used for fitting: 4.0.3
-#&gt; Date of fit: Mon Jan 25 14:42:18 2021
-#&gt; Date of summary: Mon Jan 25 14:42:18 2021
+#&gt; mkin version used for pre-fitting: 1.0.5
+#&gt; R version used for fitting: 4.1.0
+#&gt; Date of fit: Wed Aug 4 16:22:43 2021
+#&gt; Date of summary: Wed Aug 4 16:22:43 2021
#&gt;
#&gt; Equations:
#&gt; 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>
#&gt;
#&gt; Model predictions using solution type analytical
#&gt;
-#&gt; Fitted in 9.954 s using 300, 100 iterations
+#&gt; Fitted in 10.143 s using 300, 100 iterations
#&gt;
#&gt; Variance model: Constant variance
#&gt;
#&gt; Mean of starting values for individual parameters:
#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2
-#&gt; 93.8102 -9.7647 -0.9711 -1.8799 -4.2708
+#&gt; 93.8102 -5.3734 -0.9711 -1.8799 -4.2708
#&gt; g_qlogis
#&gt; 0.1356
#&gt;
@@ -430,46 +465,46 @@ using <a href='mmkin.html'>mmkin</a>.</p>
#&gt;
#&gt; Likelihood computed by importance sampling
#&gt; AIC BIC logLik
-#&gt; 841.6 836.5 -407.8
+#&gt; 839.6 834.6 -406.8
#&gt;
#&gt; Optimised parameters:
#&gt; est. lower upper
-#&gt; parent_0 93.76647 91.153 96.3798
-#&gt; log_k_A1 -6.13235 -8.458 -3.8068
-#&gt; f_parent_qlogis -0.97364 -1.369 -0.5779
-#&gt; log_k1 -2.53176 -3.804 -1.2598
-#&gt; log_k2 -3.58667 -5.295 -1.8781
-#&gt; g_qlogis 0.01238 -1.080 1.1044
+#&gt; parent_0 93.80521 91.225 96.3856
+#&gt; log_k_A1 -6.06244 -8.265 -3.8597
+#&gt; f_parent_qlogis -0.97319 -1.370 -0.5761
+#&gt; log_k1 -2.55394 -4.008 -1.0997
+#&gt; log_k2 -3.47160 -5.188 -1.7556
+#&gt; g_qlogis -0.09324 -1.427 1.2409
#&gt;
#&gt; Correlation:
#&gt; prnt_0 lg__A1 f_prn_ log_k1 log_k2
-#&gt; log_k_A1 -0.013
-#&gt; f_parent_qlogis -0.025 0.050
-#&gt; log_k1 0.030 0.000 -0.005
-#&gt; log_k2 0.010 0.005 -0.003 0.032
-#&gt; g_qlogis -0.063 -0.015 0.010 -0.167 -0.177
+#&gt; log_k_A1 -0.014
+#&gt; f_parent_qlogis -0.025 0.054
+#&gt; log_k1 0.027 -0.003 -0.005
+#&gt; log_k2 0.011 0.005 -0.002 -0.070
+#&gt; g_qlogis -0.067 -0.009 0.011 -0.189 -0.171
#&gt;
#&gt; Random effects:
#&gt; est. lower upper
-#&gt; SD.parent_0 2.7588 0.7723 4.7453
-#&gt; SD.log_k_A1 2.1556 0.4443 3.8670
-#&gt; SD.f_parent_qlogis 0.4438 0.1599 0.7276
-#&gt; SD.log_k1 1.4203 0.5271 2.3134
-#&gt; SD.log_k2 1.9063 0.7093 3.1033
-#&gt; SD.g_qlogis 0.4477 -0.8642 1.7596
+#&gt; SD.parent_0 2.7243 0.7644 4.6841
+#&gt; SD.log_k_A1 2.0563 0.4292 3.6835
+#&gt; SD.f_parent_qlogis 0.4450 0.1602 0.7298
+#&gt; SD.log_k1 1.5121 0.4714 2.5528
+#&gt; SD.log_k2 1.8320 0.6031 3.0609
+#&gt; SD.g_qlogis 0.4482 -1.2544 2.1507
#&gt;
#&gt; Variance model:
#&gt; est. lower upper
-#&gt; a.1 1.883 1.666 2.1
+#&gt; a.1 1.884 1.668 2.1
#&gt;
#&gt; Backtransformed parameters:
#&gt; est. lower upper
-#&gt; parent_0 93.766473 9.115e+01 96.37983
-#&gt; k_A1 0.002171 2.122e-04 0.02222
-#&gt; f_parent_to_A1 0.274156 2.027e-01 0.35942
-#&gt; k1 0.079519 2.229e-02 0.28371
-#&gt; k2 0.027691 5.015e-03 0.15288
-#&gt; g 0.503095 2.536e-01 0.75109
+#&gt; parent_0 93.805214 9.122e+01 96.38556
+#&gt; k_A1 0.002329 2.573e-04 0.02107
+#&gt; f_parent_to_A1 0.274245 2.026e-01 0.35982
+#&gt; k1 0.077775 1.817e-02 0.33296
+#&gt; k2 0.031067 5.585e-03 0.17281
+#&gt; g 0.476707 1.935e-01 0.77572
#&gt;
#&gt; Resulting formation fractions:
#&gt; ff
@@ -477,182 +512,182 @@ using <a href='mmkin.html'>mmkin</a>.</p>
#&gt; parent_sink 0.7258
#&gt;
#&gt; Estimated disappearance times:
-#&gt; DT50 DT90 DT50back DT50_k1 DT50_k2
-#&gt; parent 14.11 59.53 17.92 8.717 25.03
-#&gt; A1 319.21 1060.38 NA NA NA
+#&gt; DT50 DT90 DT50back DT50_k1 DT50_k2
+#&gt; parent 13.96 55.4 16.68 8.912 22.31
+#&gt; A1 297.65 988.8 NA NA NA
#&gt;
#&gt; Data:
-#&gt; ds name time observed predicted residual std standardized
-#&gt; Dataset 6 parent 0 97.2 95.79523 -1.40477 1.883 -0.745888
-#&gt; Dataset 6 parent 0 96.4 95.79523 -0.60477 1.883 -0.321114
-#&gt; Dataset 6 parent 3 71.1 71.32042 0.22042 1.883 0.117035
-#&gt; Dataset 6 parent 3 69.2 71.32042 2.12042 1.883 1.125873
-#&gt; Dataset 6 parent 6 58.1 56.45256 -1.64744 1.883 -0.874739
-#&gt; Dataset 6 parent 6 56.6 56.45256 -0.14744 1.883 -0.078288
-#&gt; Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045256
-#&gt; Dataset 6 parent 10 43.4 44.48523 1.08523 1.883 0.576224
-#&gt; Dataset 6 parent 20 33.3 29.75774 -3.54226 1.883 -1.880826
-#&gt; Dataset 6 parent 20 29.2 29.75774 0.55774 1.883 0.296141
-#&gt; Dataset 6 parent 34 17.6 19.35710 1.75710 1.883 0.932966
-#&gt; Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720578
-#&gt; Dataset 6 parent 55 10.5 10.48443 -0.01557 1.883 -0.008266
-#&gt; Dataset 6 parent 55 9.3 10.48443 1.18443 1.883 0.628895
-#&gt; Dataset 6 parent 90 4.5 3.78622 -0.71378 1.883 -0.378995
-#&gt; Dataset 6 parent 90 4.7 3.78622 -0.91378 1.883 -0.485188
-#&gt; Dataset 6 parent 112 3.0 1.99608 -1.00392 1.883 -0.533048
-#&gt; Dataset 6 parent 112 3.4 1.99608 -1.40392 1.883 -0.745435
-#&gt; Dataset 6 parent 132 2.3 1.11539 -1.18461 1.883 -0.628990
-#&gt; Dataset 6 parent 132 2.7 1.11539 -1.58461 1.883 -0.841377
-#&gt; Dataset 6 A1 3 4.3 4.66132 0.36132 1.883 0.191849
-#&gt; Dataset 6 A1 3 4.6 4.66132 0.06132 1.883 0.032559
-#&gt; Dataset 6 A1 6 7.0 7.41087 0.41087 1.883 0.218157
-#&gt; Dataset 6 A1 6 7.2 7.41087 0.21087 1.883 0.111964
-#&gt; Dataset 6 A1 10 8.2 9.50878 1.30878 1.883 0.694921
-#&gt; Dataset 6 A1 10 8.0 9.50878 1.50878 1.883 0.801114
-#&gt; Dataset 6 A1 20 11.0 11.69902 0.69902 1.883 0.371157
-#&gt; Dataset 6 A1 20 13.7 11.69902 -2.00098 1.883 -1.062455
-#&gt; Dataset 6 A1 34 11.5 12.67784 1.17784 1.883 0.625396
-#&gt; Dataset 6 A1 34 12.7 12.67784 -0.02216 1.883 -0.011765
-#&gt; Dataset 6 A1 55 14.9 12.78556 -2.11444 1.883 -1.122701
-#&gt; Dataset 6 A1 55 14.5 12.78556 -1.71444 1.883 -0.910314
-#&gt; Dataset 6 A1 90 12.1 11.52954 -0.57046 1.883 -0.302898
-#&gt; Dataset 6 A1 90 12.3 11.52954 -0.77046 1.883 -0.409092
-#&gt; Dataset 6 A1 112 9.9 10.43825 0.53825 1.883 0.285793
-#&gt; Dataset 6 A1 112 10.2 10.43825 0.23825 1.883 0.126503
-#&gt; Dataset 6 A1 132 8.8 9.42830 0.62830 1.883 0.333609
-#&gt; Dataset 6 A1 132 7.8 9.42830 1.62830 1.883 0.864577
-#&gt; Dataset 7 parent 0 93.6 90.91477 -2.68523 1.883 -1.425772
-#&gt; Dataset 7 parent 0 92.3 90.91477 -1.38523 1.883 -0.735514
-#&gt; Dataset 7 parent 3 87.0 84.76874 -2.23126 1.883 -1.184726
-#&gt; Dataset 7 parent 3 82.2 84.76874 2.56874 1.883 1.363919
-#&gt; Dataset 7 parent 7 74.0 77.62735 3.62735 1.883 1.926003
-#&gt; Dataset 7 parent 7 73.9 77.62735 3.72735 1.883 1.979100
-#&gt; Dataset 7 parent 14 64.2 67.52266 3.32266 1.883 1.764224
-#&gt; Dataset 7 parent 14 69.5 67.52266 -1.97734 1.883 -1.049904
-#&gt; Dataset 7 parent 30 54.0 52.41949 -1.58051 1.883 -0.839202
-#&gt; Dataset 7 parent 30 54.6 52.41949 -2.18051 1.883 -1.157783
-#&gt; Dataset 7 parent 60 41.1 39.36582 -1.73418 1.883 -0.920794
-#&gt; Dataset 7 parent 60 38.4 39.36582 0.96582 1.883 0.512818
-#&gt; Dataset 7 parent 90 32.5 33.75388 1.25388 1.883 0.665771
-#&gt; Dataset 7 parent 90 35.5 33.75388 -1.74612 1.883 -0.927132
-#&gt; Dataset 7 parent 120 28.1 30.41716 2.31716 1.883 1.230335
-#&gt; Dataset 7 parent 120 29.0 30.41716 1.41716 1.883 0.752464
-#&gt; Dataset 7 parent 180 26.5 25.66046 -0.83954 1.883 -0.445767
-#&gt; Dataset 7 parent 180 27.6 25.66046 -1.93954 1.883 -1.029832
-#&gt; Dataset 7 A1 3 3.9 2.69355 -1.20645 1.883 -0.640585
-#&gt; Dataset 7 A1 3 3.1 2.69355 -0.40645 1.883 -0.215811
-#&gt; Dataset 7 A1 7 6.9 5.81807 -1.08193 1.883 -0.574470
-#&gt; Dataset 7 A1 7 6.6 5.81807 -0.78193 1.883 -0.415180
-#&gt; Dataset 7 A1 14 10.4 10.22529 -0.17471 1.883 -0.092767
-#&gt; Dataset 7 A1 14 8.3 10.22529 1.92529 1.883 1.022265
-#&gt; Dataset 7 A1 30 14.4 16.75484 2.35484 1.883 1.250345
-#&gt; Dataset 7 A1 30 13.7 16.75484 3.05484 1.883 1.622022
-#&gt; Dataset 7 A1 60 22.1 22.22540 0.12540 1.883 0.066583
-#&gt; Dataset 7 A1 60 22.3 22.22540 -0.07460 1.883 -0.039610
-#&gt; Dataset 7 A1 90 27.5 24.38799 -3.11201 1.883 -1.652376
-#&gt; Dataset 7 A1 90 25.4 24.38799 -1.01201 1.883 -0.537344
-#&gt; Dataset 7 A1 120 28.0 25.53294 -2.46706 1.883 -1.309927
-#&gt; Dataset 7 A1 120 26.6 25.53294 -1.06706 1.883 -0.566572
-#&gt; Dataset 7 A1 180 25.8 26.94943 1.14943 1.883 0.610309
-#&gt; Dataset 7 A1 180 25.3 26.94943 1.64943 1.883 0.875793
-#&gt; Dataset 8 parent 0 91.9 91.53246 -0.36754 1.883 -0.195151
-#&gt; Dataset 8 parent 0 90.8 91.53246 0.73246 1.883 0.388914
-#&gt; Dataset 8 parent 1 64.9 67.73197 2.83197 1.883 1.503686
-#&gt; Dataset 8 parent 1 66.2 67.73197 1.53197 1.883 0.813428
-#&gt; Dataset 8 parent 3 43.5 41.58448 -1.91552 1.883 -1.017081
-#&gt; Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335661
-#&gt; Dataset 8 parent 8 18.3 19.62286 1.32286 1.883 0.702395
-#&gt; Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808589
-#&gt; Dataset 8 parent 14 10.2 10.77819 0.57819 1.883 0.306999
-#&gt; Dataset 8 parent 14 10.8 10.77819 -0.02181 1.883 -0.011582
-#&gt; Dataset 8 parent 27 4.9 3.26977 -1.63023 1.883 -0.865599
-#&gt; Dataset 8 parent 27 3.3 3.26977 -0.03023 1.883 -0.016051
-#&gt; Dataset 8 parent 48 1.6 0.48024 -1.11976 1.883 -0.594557
-#&gt; Dataset 8 parent 48 1.5 0.48024 -1.01976 1.883 -0.541460
-#&gt; Dataset 8 parent 70 1.1 0.06438 -1.03562 1.883 -0.549881
-#&gt; Dataset 8 parent 70 0.9 0.06438 -0.83562 1.883 -0.443688
-#&gt; Dataset 8 A1 1 9.6 7.61539 -1.98461 1.883 -1.053761
-#&gt; Dataset 8 A1 1 7.7 7.61539 -0.08461 1.883 -0.044923
-#&gt; Dataset 8 A1 3 15.0 15.47954 0.47954 1.883 0.254622
-#&gt; Dataset 8 A1 3 15.1 15.47954 0.37954 1.883 0.201525
-#&gt; Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517076
-#&gt; Dataset 8 A1 8 21.1 20.22616 -0.87384 1.883 -0.463979
-#&gt; Dataset 8 A1 14 19.7 20.00067 0.30067 1.883 0.159645
-#&gt; Dataset 8 A1 14 18.9 20.00067 1.10067 1.883 0.584419
-#&gt; Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593929
-#&gt; Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255619
-#&gt; Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400123
-#&gt; Dataset 8 A1 48 9.8 10.25357 0.45357 1.883 0.240833
-#&gt; Dataset 8 A1 70 6.2 5.95728 -0.24272 1.883 -0.128878
-#&gt; Dataset 8 A1 70 6.1 5.95728 -0.14272 1.883 -0.075781
-#&gt; Dataset 9 parent 0 99.8 97.47274 -2.32726 1.883 -1.235697
-#&gt; Dataset 9 parent 0 98.3 97.47274 -0.82726 1.883 -0.439246
-#&gt; Dataset 9 parent 1 77.1 79.72257 2.62257 1.883 1.392500
-#&gt; Dataset 9 parent 1 77.2 79.72257 2.52257 1.883 1.339404
-#&gt; Dataset 9 parent 3 59.0 56.26497 -2.73503 1.883 -1.452212
-#&gt; Dataset 9 parent 3 58.1 56.26497 -1.83503 1.883 -0.974342
-#&gt; Dataset 9 parent 8 27.4 31.66985 4.26985 1.883 2.267151
-#&gt; Dataset 9 parent 8 29.2 31.66985 2.46985 1.883 1.311410
-#&gt; Dataset 9 parent 14 19.1 22.39789 3.29789 1.883 1.751071
-#&gt; Dataset 9 parent 14 29.6 22.39789 -7.20211 1.883 -3.824090
-#&gt; Dataset 9 parent 27 10.1 14.21758 4.11758 1.883 2.186301
-#&gt; Dataset 9 parent 27 18.2 14.21758 -3.98242 1.883 -2.114537
-#&gt; Dataset 9 parent 48 4.5 7.27921 2.77921 1.883 1.475671
-#&gt; Dataset 9 parent 48 9.1 7.27921 -1.82079 1.883 -0.966780
-#&gt; Dataset 9 parent 70 2.3 3.61470 1.31470 1.883 0.698065
-#&gt; Dataset 9 parent 70 2.9 3.61470 0.71470 1.883 0.379485
-#&gt; Dataset 9 parent 91 2.0 1.85303 -0.14697 1.883 -0.078038
-#&gt; Dataset 9 parent 91 1.8 1.85303 0.05303 1.883 0.028155
-#&gt; Dataset 9 parent 120 2.0 0.73645 -1.26355 1.883 -0.670906
-#&gt; Dataset 9 parent 120 2.2 0.73645 -1.46355 1.883 -0.777099
-#&gt; Dataset 9 A1 1 4.2 3.87843 -0.32157 1.883 -0.170743
-#&gt; Dataset 9 A1 1 3.9 3.87843 -0.02157 1.883 -0.011453
-#&gt; Dataset 9 A1 3 7.4 8.90535 1.50535 1.883 0.799291
-#&gt; Dataset 9 A1 3 7.9 8.90535 1.00535 1.883 0.533807
-#&gt; Dataset 9 A1 8 14.5 13.75172 -0.74828 1.883 -0.397312
-#&gt; Dataset 9 A1 8 13.7 13.75172 0.05172 1.883 0.027462
-#&gt; Dataset 9 A1 14 14.2 14.97541 0.77541 1.883 0.411715
-#&gt; Dataset 9 A1 14 12.2 14.97541 2.77541 1.883 1.473650
-#&gt; Dataset 9 A1 27 13.7 14.94728 1.24728 1.883 0.662266
-#&gt; Dataset 9 A1 27 13.2 14.94728 1.74728 1.883 0.927750
-#&gt; Dataset 9 A1 48 13.6 13.66078 0.06078 1.883 0.032272
-#&gt; Dataset 9 A1 48 15.4 13.66078 -1.73922 1.883 -0.923470
-#&gt; Dataset 9 A1 70 10.4 11.84899 1.44899 1.883 0.769365
-#&gt; Dataset 9 A1 70 11.6 11.84899 0.24899 1.883 0.132204
-#&gt; Dataset 9 A1 91 10.0 10.09177 0.09177 1.883 0.048727
-#&gt; Dataset 9 A1 91 9.5 10.09177 0.59177 1.883 0.314211
-#&gt; Dataset 9 A1 120 9.1 7.91379 -1.18621 1.883 -0.629841
-#&gt; Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576745
-#&gt; Dataset 10 parent 0 96.1 93.65257 -2.44743 1.883 -1.299505
-#&gt; Dataset 10 parent 0 94.3 93.65257 -0.64743 1.883 -0.343763
-#&gt; Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132
-#&gt; Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132
-#&gt; Dataset 10 parent 14 69.4 70.17143 0.77143 1.883 0.409606
-#&gt; Dataset 10 parent 14 73.1 70.17143 -2.92857 1.883 -1.554974
-#&gt; Dataset 10 parent 21 65.6 63.99188 -1.60812 1.883 -0.853862
-#&gt; Dataset 10 parent 21 65.3 63.99188 -1.30812 1.883 -0.694572
-#&gt; Dataset 10 parent 41 55.9 54.64292 -1.25708 1.883 -0.667467
-#&gt; Dataset 10 parent 41 54.4 54.64292 0.24292 1.883 0.128985
-#&gt; Dataset 10 parent 63 47.0 49.61303 2.61303 1.883 1.387433
-#&gt; Dataset 10 parent 63 49.3 49.61303 0.31303 1.883 0.166207
-#&gt; Dataset 10 parent 91 44.7 45.17807 0.47807 1.883 0.253839
-#&gt; Dataset 10 parent 91 46.7 45.17807 -1.52193 1.883 -0.808096
-#&gt; Dataset 10 parent 120 42.1 41.27970 -0.82030 1.883 -0.435552
-#&gt; Dataset 10 parent 120 41.3 41.27970 -0.02030 1.883 -0.010778
-#&gt; Dataset 10 A1 8 3.3 3.99294 0.69294 1.883 0.367929
-#&gt; Dataset 10 A1 8 3.4 3.99294 0.59294 1.883 0.314832
-#&gt; Dataset 10 A1 14 3.9 5.92756 2.02756 1.883 1.076570
-#&gt; Dataset 10 A1 14 2.9 5.92756 3.02756 1.883 1.607538
-#&gt; Dataset 10 A1 21 6.4 7.47313 1.07313 1.883 0.569799
-#&gt; Dataset 10 A1 21 7.2 7.47313 0.27313 1.883 0.145025
-#&gt; Dataset 10 A1 41 9.1 9.76819 0.66819 1.883 0.354786
-#&gt; Dataset 10 A1 41 8.5 9.76819 1.26819 1.883 0.673367
-#&gt; Dataset 10 A1 63 11.7 10.94733 -0.75267 1.883 -0.399643
-#&gt; Dataset 10 A1 63 12.0 10.94733 -1.05267 1.883 -0.558933
-#&gt; Dataset 10 A1 91 13.3 11.93773 -1.36227 1.883 -0.723321
-#&gt; Dataset 10 A1 91 13.2 11.93773 -1.26227 1.883 -0.670224
-#&gt; Dataset 10 A1 120 14.3 12.77666 -1.52334 1.883 -0.808847
-#&gt; Dataset 10 A1 120 12.1 12.77666 0.67666 1.883 0.359282</div><div class='input'>
+#&gt; ds name time observed predicted residual std standardized
+#&gt; Dataset 6 parent 0 97.2 95.75408 1.445920 1.884 0.767479
+#&gt; Dataset 6 parent 0 96.4 95.75408 0.645920 1.884 0.342847
+#&gt; Dataset 6 parent 3 71.1 71.22466 -0.124662 1.884 -0.066169
+#&gt; Dataset 6 parent 3 69.2 71.22466 -2.024662 1.884 -1.074669
+#&gt; Dataset 6 parent 6 58.1 56.42290 1.677100 1.884 0.890187
+#&gt; Dataset 6 parent 6 56.6 56.42290 0.177100 1.884 0.094003
+#&gt; Dataset 6 parent 10 44.4 44.55255 -0.152554 1.884 -0.080974
+#&gt; Dataset 6 parent 10 43.4 44.55255 -1.152554 1.884 -0.611763
+#&gt; Dataset 6 parent 20 33.3 29.88846 3.411537 1.884 1.810807
+#&gt; Dataset 6 parent 20 29.2 29.88846 -0.688463 1.884 -0.365429
+#&gt; Dataset 6 parent 34 17.6 19.40826 -1.808260 1.884 -0.959805
+#&gt; Dataset 6 parent 34 18.0 19.40826 -1.408260 1.884 -0.747489
+#&gt; Dataset 6 parent 55 10.5 10.45560 0.044398 1.884 0.023566
+#&gt; Dataset 6 parent 55 9.3 10.45560 -1.155602 1.884 -0.613381
+#&gt; Dataset 6 parent 90 4.5 3.74026 0.759744 1.884 0.403264
+#&gt; Dataset 6 parent 90 4.7 3.74026 0.959744 1.884 0.509421
+#&gt; Dataset 6 parent 112 3.0 1.96015 1.039853 1.884 0.551943
+#&gt; Dataset 6 parent 112 3.4 1.96015 1.439853 1.884 0.764258
+#&gt; Dataset 6 parent 132 2.3 1.08940 1.210603 1.884 0.642575
+#&gt; Dataset 6 parent 132 2.7 1.08940 1.610603 1.884 0.854890
+#&gt; Dataset 6 A1 3 4.3 4.75601 -0.456009 1.884 -0.242045
+#&gt; Dataset 6 A1 3 4.6 4.75601 -0.156009 1.884 -0.082808
+#&gt; Dataset 6 A1 6 7.0 7.53839 -0.538391 1.884 -0.285772
+#&gt; Dataset 6 A1 6 7.2 7.53839 -0.338391 1.884 -0.179614
+#&gt; Dataset 6 A1 10 8.2 9.64728 -1.447276 1.884 -0.768198
+#&gt; Dataset 6 A1 10 8.0 9.64728 -1.647276 1.884 -0.874356
+#&gt; Dataset 6 A1 20 11.0 11.83954 -0.839545 1.884 -0.445621
+#&gt; Dataset 6 A1 20 13.7 11.83954 1.860455 1.884 0.987509
+#&gt; Dataset 6 A1 34 11.5 12.81233 -1.312327 1.884 -0.696569
+#&gt; Dataset 6 A1 34 12.7 12.81233 -0.112327 1.884 -0.059622
+#&gt; Dataset 6 A1 55 14.9 12.87919 2.020809 1.884 1.072624
+#&gt; Dataset 6 A1 55 14.5 12.87919 1.620809 1.884 0.860308
+#&gt; Dataset 6 A1 90 12.1 11.52464 0.575364 1.884 0.305397
+#&gt; Dataset 6 A1 90 12.3 11.52464 0.775364 1.884 0.411555
+#&gt; Dataset 6 A1 112 9.9 10.37694 -0.476938 1.884 -0.253153
+#&gt; Dataset 6 A1 112 10.2 10.37694 -0.176938 1.884 -0.093917
+#&gt; Dataset 6 A1 132 8.8 9.32474 -0.524742 1.884 -0.278528
+#&gt; Dataset 6 A1 132 7.8 9.32474 -1.524742 1.884 -0.809317
+#&gt; Dataset 7 parent 0 93.6 90.16918 3.430816 1.884 1.821040
+#&gt; Dataset 7 parent 0 92.3 90.16918 2.130816 1.884 1.131014
+#&gt; Dataset 7 parent 3 87.0 84.05442 2.945583 1.884 1.563483
+#&gt; Dataset 7 parent 3 82.2 84.05442 -1.854417 1.884 -0.984304
+#&gt; Dataset 7 parent 7 74.0 77.00960 -3.009596 1.884 -1.597461
+#&gt; Dataset 7 parent 7 73.9 77.00960 -3.109596 1.884 -1.650540
+#&gt; Dataset 7 parent 14 64.2 67.15684 -2.956840 1.884 -1.569459
+#&gt; Dataset 7 parent 14 69.5 67.15684 2.343160 1.884 1.243724
+#&gt; Dataset 7 parent 30 54.0 52.66290 1.337101 1.884 0.709719
+#&gt; Dataset 7 parent 30 54.6 52.66290 1.937101 1.884 1.028192
+#&gt; Dataset 7 parent 60 41.1 40.04995 1.050050 1.884 0.557355
+#&gt; Dataset 7 parent 60 38.4 40.04995 -1.649950 1.884 -0.875775
+#&gt; Dataset 7 parent 90 32.5 34.09675 -1.596746 1.884 -0.847535
+#&gt; Dataset 7 parent 90 35.5 34.09675 1.403254 1.884 0.744832
+#&gt; Dataset 7 parent 120 28.1 30.12281 -2.022814 1.884 -1.073688
+#&gt; Dataset 7 parent 120 29.0 30.12281 -1.122814 1.884 -0.595977
+#&gt; Dataset 7 parent 180 26.5 24.10888 2.391123 1.884 1.269182
+#&gt; Dataset 7 parent 180 27.6 24.10888 3.491123 1.884 1.853050
+#&gt; Dataset 7 A1 3 3.9 2.77684 1.123161 1.884 0.596161
+#&gt; Dataset 7 A1 3 3.1 2.77684 0.323161 1.884 0.171530
+#&gt; Dataset 7 A1 7 6.9 5.96705 0.932950 1.884 0.495200
+#&gt; Dataset 7 A1 7 6.6 5.96705 0.632950 1.884 0.335963
+#&gt; Dataset 7 A1 14 10.4 10.40535 -0.005348 1.884 -0.002839
+#&gt; Dataset 7 A1 14 8.3 10.40535 -2.105348 1.884 -1.117496
+#&gt; Dataset 7 A1 30 14.4 16.83722 -2.437216 1.884 -1.293648
+#&gt; Dataset 7 A1 30 13.7 16.83722 -3.137216 1.884 -1.665200
+#&gt; Dataset 7 A1 60 22.1 22.15018 -0.050179 1.884 -0.026635
+#&gt; Dataset 7 A1 60 22.3 22.15018 0.149821 1.884 0.079523
+#&gt; Dataset 7 A1 90 27.5 24.36286 3.137143 1.884 1.665161
+#&gt; Dataset 7 A1 90 25.4 24.36286 1.037143 1.884 0.550504
+#&gt; Dataset 7 A1 120 28.0 25.64064 2.359361 1.884 1.252323
+#&gt; Dataset 7 A1 120 26.6 25.64064 0.959361 1.884 0.509218
+#&gt; Dataset 7 A1 180 25.8 27.25486 -1.454858 1.884 -0.772223
+#&gt; Dataset 7 A1 180 25.3 27.25486 -1.954858 1.884 -1.037617
+#&gt; Dataset 8 parent 0 91.9 91.72652 0.173479 1.884 0.092081
+#&gt; Dataset 8 parent 0 90.8 91.72652 -0.926521 1.884 -0.491787
+#&gt; Dataset 8 parent 1 64.9 67.22810 -2.328104 1.884 -1.235732
+#&gt; Dataset 8 parent 1 66.2 67.22810 -1.028104 1.884 -0.545706
+#&gt; Dataset 8 parent 3 43.5 41.46375 2.036251 1.884 1.080820
+#&gt; Dataset 8 parent 3 44.1 41.46375 2.636251 1.884 1.399293
+#&gt; Dataset 8 parent 8 18.3 19.83597 -1.535968 1.884 -0.815275
+#&gt; Dataset 8 parent 8 18.1 19.83597 -1.735968 1.884 -0.921433
+#&gt; Dataset 8 parent 14 10.2 10.34793 -0.147927 1.884 -0.078518
+#&gt; Dataset 8 parent 14 10.8 10.34793 0.452073 1.884 0.239956
+#&gt; Dataset 8 parent 27 4.9 2.67641 2.223595 1.884 1.180260
+#&gt; Dataset 8 parent 27 3.3 2.67641 0.623595 1.884 0.330997
+#&gt; Dataset 8 parent 48 1.6 0.30218 1.297822 1.884 0.688870
+#&gt; Dataset 8 parent 48 1.5 0.30218 1.197822 1.884 0.635791
+#&gt; Dataset 8 parent 70 1.1 0.03075 1.069248 1.884 0.567545
+#&gt; Dataset 8 parent 70 0.9 0.03075 0.869248 1.884 0.461388
+#&gt; Dataset 8 A1 1 9.6 7.74066 1.859342 1.884 0.986918
+#&gt; Dataset 8 A1 1 7.7 7.74066 -0.040658 1.884 -0.021581
+#&gt; Dataset 8 A1 3 15.0 15.37549 -0.375495 1.884 -0.199309
+#&gt; Dataset 8 A1 3 15.1 15.37549 -0.275495 1.884 -0.146230
+#&gt; Dataset 8 A1 8 21.2 19.95900 1.241003 1.884 0.658711
+#&gt; Dataset 8 A1 8 21.1 19.95900 1.141003 1.884 0.605632
+#&gt; Dataset 8 A1 14 19.7 19.92898 -0.228978 1.884 -0.121539
+#&gt; Dataset 8 A1 14 18.9 19.92898 -1.028978 1.884 -0.546170
+#&gt; Dataset 8 A1 27 17.5 16.34046 1.159536 1.884 0.615469
+#&gt; Dataset 8 A1 27 15.9 16.34046 -0.440464 1.884 -0.233793
+#&gt; Dataset 8 A1 48 9.5 10.12131 -0.621313 1.884 -0.329786
+#&gt; Dataset 8 A1 48 9.8 10.12131 -0.321313 1.884 -0.170550
+#&gt; Dataset 8 A1 70 6.2 5.84753 0.352469 1.884 0.187087
+#&gt; Dataset 8 A1 70 6.1 5.84753 0.252469 1.884 0.134008
+#&gt; Dataset 9 parent 0 99.8 98.23600 1.564002 1.884 0.830155
+#&gt; Dataset 9 parent 0 98.3 98.23600 0.064002 1.884 0.033972
+#&gt; Dataset 9 parent 1 77.1 79.68007 -2.580074 1.884 -1.369475
+#&gt; Dataset 9 parent 1 77.2 79.68007 -2.480074 1.884 -1.316396
+#&gt; Dataset 9 parent 3 59.0 55.81142 3.188584 1.884 1.692465
+#&gt; Dataset 9 parent 3 58.1 55.81142 2.288584 1.884 1.214755
+#&gt; Dataset 9 parent 8 27.4 31.81995 -4.419948 1.884 -2.346060
+#&gt; Dataset 9 parent 8 29.2 31.81995 -2.619948 1.884 -1.390640
+#&gt; Dataset 9 parent 14 19.1 22.78328 -3.683282 1.884 -1.955046
+#&gt; Dataset 9 parent 14 29.6 22.78328 6.816718 1.884 3.618240
+#&gt; Dataset 9 parent 27 10.1 14.15172 -4.051720 1.884 -2.150609
+#&gt; Dataset 9 parent 27 18.2 14.15172 4.048280 1.884 2.148783
+#&gt; Dataset 9 parent 48 4.5 6.86094 -2.360941 1.884 -1.253162
+#&gt; Dataset 9 parent 48 9.1 6.86094 2.239059 1.884 1.188468
+#&gt; Dataset 9 parent 70 2.3 3.21580 -0.915798 1.884 -0.486096
+#&gt; Dataset 9 parent 70 2.9 3.21580 -0.315798 1.884 -0.167622
+#&gt; Dataset 9 parent 91 2.0 1.56010 0.439897 1.884 0.233492
+#&gt; Dataset 9 parent 91 1.8 1.56010 0.239897 1.884 0.127335
+#&gt; Dataset 9 parent 120 2.0 0.57458 1.425424 1.884 0.756600
+#&gt; Dataset 9 parent 120 2.2 0.57458 1.625424 1.884 0.862757
+#&gt; Dataset 9 A1 1 4.2 4.01796 0.182037 1.884 0.096623
+#&gt; Dataset 9 A1 1 3.9 4.01796 -0.117963 1.884 -0.062613
+#&gt; Dataset 9 A1 3 7.4 9.08527 -1.685270 1.884 -0.894523
+#&gt; Dataset 9 A1 3 7.9 9.08527 -1.185270 1.884 -0.629129
+#&gt; Dataset 9 A1 8 14.5 13.75054 0.749457 1.884 0.397804
+#&gt; Dataset 9 A1 8 13.7 13.75054 -0.050543 1.884 -0.026827
+#&gt; Dataset 9 A1 14 14.2 14.91180 -0.711804 1.884 -0.377818
+#&gt; Dataset 9 A1 14 12.2 14.91180 -2.711804 1.884 -1.439396
+#&gt; Dataset 9 A1 27 13.7 14.97813 -1.278129 1.884 -0.678417
+#&gt; Dataset 9 A1 27 13.2 14.97813 -1.778129 1.884 -0.943812
+#&gt; Dataset 9 A1 48 13.6 13.75574 -0.155745 1.884 -0.082668
+#&gt; Dataset 9 A1 48 15.4 13.75574 1.644255 1.884 0.872753
+#&gt; Dataset 9 A1 70 10.4 11.92861 -1.528608 1.884 -0.811369
+#&gt; Dataset 9 A1 70 11.6 11.92861 -0.328608 1.884 -0.174422
+#&gt; Dataset 9 A1 91 10.0 10.14395 -0.143947 1.884 -0.076405
+#&gt; Dataset 9 A1 91 9.5 10.14395 -0.643947 1.884 -0.341800
+#&gt; Dataset 9 A1 120 9.1 7.93869 1.161307 1.884 0.616409
+#&gt; Dataset 9 A1 120 9.0 7.93869 1.061307 1.884 0.563330
+#&gt; Dataset 10 parent 0 96.1 93.65914 2.440862 1.884 1.295583
+#&gt; Dataset 10 parent 0 94.3 93.65914 0.640862 1.884 0.340163
+#&gt; Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344
+#&gt; Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344
+#&gt; Dataset 10 parent 14 69.4 70.15862 -0.758619 1.884 -0.402667
+#&gt; Dataset 10 parent 14 73.1 70.15862 2.941381 1.884 1.561253
+#&gt; Dataset 10 parent 21 65.6 64.00840 1.591600 1.884 0.844804
+#&gt; Dataset 10 parent 21 65.3 64.00840 1.291600 1.884 0.685567
+#&gt; Dataset 10 parent 41 55.9 54.71192 1.188076 1.884 0.630618
+#&gt; Dataset 10 parent 41 54.4 54.71192 -0.311924 1.884 -0.165566
+#&gt; Dataset 10 parent 63 47.0 49.66775 -2.667747 1.884 -1.416011
+#&gt; Dataset 10 parent 63 49.3 49.66775 -0.367747 1.884 -0.195196
+#&gt; Dataset 10 parent 91 44.7 45.17119 -0.471186 1.884 -0.250101
+#&gt; Dataset 10 parent 91 46.7 45.17119 1.528814 1.884 0.811478
+#&gt; Dataset 10 parent 120 42.1 41.20430 0.895699 1.884 0.475427
+#&gt; Dataset 10 parent 120 41.3 41.20430 0.095699 1.884 0.050796
+#&gt; Dataset 10 A1 8 3.3 4.00920 -0.709204 1.884 -0.376438
+#&gt; Dataset 10 A1 8 3.4 4.00920 -0.609204 1.884 -0.323359
+#&gt; Dataset 10 A1 14 3.9 5.94267 -2.042668 1.884 -1.084226
+#&gt; Dataset 10 A1 14 2.9 5.94267 -3.042668 1.884 -1.615015
+#&gt; Dataset 10 A1 21 6.4 7.48222 -1.082219 1.884 -0.574430
+#&gt; Dataset 10 A1 21 7.2 7.48222 -0.282219 1.884 -0.149799
+#&gt; Dataset 10 A1 41 9.1 9.76246 -0.662460 1.884 -0.351626
+#&gt; Dataset 10 A1 41 8.5 9.76246 -1.262460 1.884 -0.670100
+#&gt; Dataset 10 A1 63 11.7 10.93972 0.760278 1.884 0.403547
+#&gt; Dataset 10 A1 63 12.0 10.93972 1.060278 1.884 0.562784
+#&gt; Dataset 10 A1 91 13.3 11.93666 1.363337 1.884 0.723645
+#&gt; Dataset 10 A1 91 13.2 11.93666 1.263337 1.884 0.670566
+#&gt; Dataset 10 A1 120 14.3 12.78218 1.517817 1.884 0.805641
+#&gt; 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 &lt;- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span>
<span class='co'># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span>

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