diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2016-11-18 15:01:53 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2016-11-18 15:22:42 +0100 |
| commit | c6086d1dd97ad2d6420625de7b8009b1b0f85d06 (patch) | |
| tree | 1a38fd690c94a556555ec71edff443bcfe609b7b /docs/reference/synthetic_data_for_UBA.html | |
| parent | 9a8dfa8bd52664929fd4197f3e9c4e65b62cad53 (diff) | |
Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE)
Using branch 'jranke' on jranke/pkgdown, fixing issues
hadley/pgkdown#178 and hadley/pkgdown#213
Remove plot=TRUE from mkinfit calls also in dontrun sections of examples
to avoid a flood png files documenting the progress of the fit.
Diffstat (limited to 'docs/reference/synthetic_data_for_UBA.html')
| -rw-r--r-- | docs/reference/synthetic_data_for_UBA.html | 872 |
1 files changed, 850 insertions, 22 deletions
diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html index c6f29582..97407402 100644 --- a/docs/reference/synthetic_data_for_UBA.html +++ b/docs/reference/synthetic_data_for_UBA.html @@ -121,28 +121,856 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'><span class='co'>## Not run: ------------------------------------</span> -<span class='co'># m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),</span> -<span class='co'># M1 = list(type = "SFO", to = "M2"),</span> -<span class='co'># M2 = list(type = "SFO"), use_of_ff = "max")</span> -<span class='co'># </span> -<span class='co'># </span> -<span class='co'># m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"),</span> -<span class='co'># sink = FALSE),</span> -<span class='co'># M1 = list(type = "SFO"),</span> -<span class='co'># M2 = list(type = "SFO"), use_of_ff = "max")</span> -<span class='co'># </span> -<span class='co'># m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"),</span> -<span class='co'># M1 = list(type = "SFO", to = "M2"),</span> -<span class='co'># M2 = list(type = "SFO"), use_of_ff = "max")</span> -<span class='co'># </span> -<span class='co'># m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"),</span> -<span class='co'># sink = FALSE),</span> -<span class='co'># M1 = list(type = "SFO"),</span> -<span class='co'># M2 = list(type = "SFO"), use_of_ff = "max")</span> -<span class='co'># </span> -<span class='co'># mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data)</span> -<span class='co'>## ---------------------------------------------</span></div></pre> + <pre class="examples"><div class='input'> +<span class='no'>m_synth_SFO_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> + +<span class='no'>m_synth_SFO_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>), + <span class='kw'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='no'>m_synth_DFOP_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"DFOP"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='no'>m_synth_DFOP_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"DFOP"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>), + <span class='kw'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_SFO_lin</span>, <span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>1</span>]]$<span class='no'>data</span>)</div><div class='output co'>#> Model cost at call 1 : 31054.59 +#> Model cost at call 3 : 31054.59 +#> Model cost at call 8 : 15089.57 +#> Model cost at call 9 : 11464.3 +#> Model cost at call 11 : 11464.1 +#> Model cost at call 16 : 5723.32 +#> Model cost at call 17 : 5723.318 +#> Model cost at call 19 : 5723.304 +#> Model cost at call 21 : 5723.304 +#> Model cost at call 24 : 3968.126 +#> Model cost at call 25 : 3968.124 +#> Model cost at call 28 : 3968.119 +#> Model cost at call 31 : 3416.421 +#> Model cost at call 32 : 3416.42 +#> Model cost at call 36 : 3416.418 +#> Model cost at call 38 : 866.5564 +#> Model cost at call 42 : 866.5557 +#> Model cost at call 45 : 670.4833 +#> Model cost at call 47 : 670.476 +#> Model cost at call 53 : 312.9905 +#> Model cost at call 57 : 312.9904 +#> Model cost at call 58 : 312.9904 +#> Model cost at call 61 : 287.8916 +#> Model cost at call 63 : 287.8916 +#> Model cost at call 66 : 287.8916 +#> Model cost at call 69 : 284.5441 +#> Model cost at call 71 : 284.5441 +#> Model cost at call 73 : 284.5441 +#> Model cost at call 76 : 283.4533 +#> Model cost at call 78 : 283.4533 +#> Model cost at call 83 : 282.1356 +#> Model cost at call 85 : 282.1356 +#> Model cost at call 88 : 282.1356 +#> Model cost at call 90 : 280.7846 +#> Model cost at call 92 : 280.7846 +#> Model cost at call 95 : 280.7846 +#> Model cost at call 97 : 278.4856 +#> Model cost at call 98 : 274.5025 +#> Model cost at call 99 : 269.2866 +#> Model cost at call 101 : 269.2866 +#> Model cost at call 102 : 269.2866 +#> Model cost at call 103 : 269.2866 +#> Model cost at call 106 : 254.1284 +#> Model cost at call 108 : 254.1283 +#> Model cost at call 109 : 254.1283 +#> Model cost at call 112 : 254.128 +#> Model cost at call 114 : 233.1376 +#> Model cost at call 116 : 233.1376 +#> Model cost at call 118 : 233.1375 +#> Model cost at call 121 : 227.5879 +#> Model cost at call 124 : 227.5879 +#> Model cost at call 125 : 227.5878 +#> Model cost at call 129 : 217.0041 +#> Model cost at call 133 : 217.0041 +#> Model cost at call 135 : 217.0041 +#> Model cost at call 136 : 215.1367 +#> Model cost at call 138 : 215.1367 +#> Model cost at call 143 : 213.3794 +#> Model cost at call 145 : 213.3794 +#> Model cost at call 150 : 211.0201 +#> Model cost at call 152 : 211.0201 +#> Model cost at call 154 : 211.0201 +#> Model cost at call 155 : 211.0201 +#> Model cost at call 157 : 210.6426 +#> Model cost at call 159 : 210.6426 +#> Model cost at call 160 : 210.6425 +#> Model cost at call 164 : 207.6331 +#> Model cost at call 167 : 207.6331 +#> Model cost at call 171 : 206.2366 +#> Model cost at call 173 : 206.2366 +#> Model cost at call 174 : 206.2366 +#> Model cost at call 178 : 204.8117 +#> Model cost at call 180 : 204.8117 +#> Model cost at call 185 : 204.7988 +#> Model cost at call 187 : 204.7988 +#> Model cost at call 190 : 204.7988 +#> Model cost at call 192 : 203.5122 +#> Model cost at call 194 : 203.5122 +#> Model cost at call 197 : 203.5122 +#> Model cost at call 198 : 203.5122 +#> Model cost at call 199 : 203.354 +#> Model cost at call 201 : 203.354 +#> Model cost at call 204 : 203.354 +#> Model cost at call 206 : 202.6825 +#> Model cost at call 208 : 202.6825 +#> Model cost at call 209 : 202.6825 +#> Model cost at call 212 : 202.6825 +#> Model cost at call 213 : 202.4582 +#> Model cost at call 215 : 202.4582 +#> Model cost at call 220 : 202.3261 +#> Model cost at call 222 : 202.3261 +#> Model cost at call 227 : 202.2306 +#> Model cost at call 229 : 202.2306 +#> Model cost at call 231 : 202.2306 +#> Model cost at call 234 : 202.115 +#> Model cost at call 236 : 202.115 +#> Model cost at call 238 : 202.115 +#> Model cost at call 241 : 202.0397 +#> Model cost at call 243 : 202.0397 +#> Model cost at call 248 : 201.8989 +#> Model cost at call 249 : 201.8551 +#> Model cost at call 252 : 201.8551 +#> Model cost at call 257 : 201.676 +#> Model cost at call 259 : 201.676 +#> Model cost at call 264 : 201.6285 +#> Model cost at call 266 : 201.6285 +#> Model cost at call 270 : 201.6284 +#> Model cost at call 271 : 201.5876 +#> Model cost at call 272 : 201.5876 +#> Model cost at call 278 : 201.5317 +#> Model cost at call 279 : 201.5317 +#> Model cost at call 286 : 201.5207 +#> Model cost at call 287 : 201.5207 +#> Model cost at call 289 : 201.5207 +#> Model cost at call 293 : 201.5207 +#> Model cost at call 294 : 201.5207 +#> Model cost at call 296 : 201.5174 +#> Model cost at call 301 : 201.5174 +#> Model cost at call 304 : 201.5169 +#> Model cost at call 305 : 201.5169 +#> Model cost at call 306 : 201.5169 +#> Model cost at call 309 : 201.5169 +#> Model cost at call 312 : 201.5169 +#> Model cost at call 314 : 201.5169 +#> Model cost at call 322 : 201.5169 +#> Model cost at call 325 : 201.5169 +#> Model cost at call 340 : 201.5169 +#> Optimisation by method Port successfully terminated.</div><div class='output co'>#> $par +#> parent_0 log_k_parent log_k_M1 log_k_M2 f_parent_ilr_1 +#> 102.0624835 -0.3020316 -1.2067882 -3.9007519 0.8491684 +#> f_M1_ilr_1 +#> 0.6780411 +#> +#> $ssr +#> [1] 201.5169 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 43 +#> +#> $evaluations +#> function gradient +#> 56 281 +#> +#> $counts +#> [1] "relative convergence (4)" +#> +#> $hessian +#> parent_0 log_k_parent log_k_M1 log_k_M2 f_parent_ilr_1 +#> parent_0 8.433594 -29.66715 -18.40708 -68.90161 115.9976 +#> log_k_parent -29.667146 10561.33531 675.33998 55.94284 1666.8940 +#> log_k_M1 -18.407082 675.33998 6274.11801 44.01714 -614.5674 +#> log_k_M2 -68.901614 55.94284 44.01714 5021.66991 -2300.4467 +#> f_parent_ilr_1 115.997604 1666.89403 -614.56735 -2300.44667 3872.8569 +#> f_M1_ilr_1 92.819176 604.06870 1483.45826 -2755.79082 3098.9947 +#> f_M1_ilr_1 +#> parent_0 92.81918 +#> log_k_parent 604.06870 +#> log_k_M1 1483.45826 +#> log_k_M2 -2755.79082 +#> f_parent_ilr_1 3098.99466 +#> f_M1_ilr_1 3712.39824 +#> +#> $residuals +#> parent parent parent parent parent parent +#> 0.56248353 0.86248353 -5.17118695 1.22881305 0.70772795 3.50772795 +#> parent parent parent parent parent parent +#> -0.52282962 0.27717038 -3.49673606 -3.19999990 -0.60000000 -3.50000000 +#> M1 M1 M1 M1 M1 M1 +#> -1.61088639 -2.61088639 5.07026619 -0.42973381 0.38714436 -2.31285564 +#> M1 M1 M1 M1 M1 M1 +#> -3.80468869 0.79531131 -0.49999789 -3.20000000 -1.50000000 -0.60000000 +#> M2 M2 M2 M2 M2 M2 +#> -0.34517017 0.62526794 2.22526794 -0.07941701 -1.17941701 -3.83353798 +#> M2 M2 M2 M2 M2 M2 +#> 1.26646202 0.87274743 2.47274743 -0.21837410 0.98162590 -0.47130583 +#> M2 M2 M2 +#> -0.67130583 -4.27893112 2.22106888 +#> +#> $ms +#> [1] 5.1671 +#> +#> $var_ms +#> parent M1 M2 +#> 6.461983 5.750942 3.664121 +#> +#> $var_ms_unscaled +#> parent M1 M2 +#> 6.461983 5.750942 3.664121 +#> +#> $var_ms_unweighted +#> parent M1 M2 +#> 6.461983 5.750942 3.664121 +#> +#> $rank +#> [1] 6 +#> +#> $df.residual +#> [1] 33 +#> +#> $solution_type +#> [1] "deSolve" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 351 +#> +#> $time +#> user system elapsed +#> 2.116 0.000 2.113 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: max +#> Specification $spec: +#> $parent +#> $type: SFO; $to: M1; $sink: TRUE +#> $M1 +#> $type: SFO; $to: M2; $sink: TRUE +#> $M2 +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> Compiled model $cf available +#> +#> $observed +#> name time value override err +#> 1 parent 0 101.5 NA 1 +#> 2 parent 0 101.2 NA 1 +#> 3 parent 1 53.9 NA 1 +#> 4 parent 1 47.5 NA 1 +#> 5 parent 3 10.4 NA 1 +#> 6 parent 3 7.6 NA 1 +#> 7 parent 7 1.1 NA 1 +#> 8 parent 7 0.3 NA 1 +#> 9 parent 14 NA NA 1 +#> 10 parent 14 3.5 NA 1 +#> 11 parent 28 NA NA 1 +#> 12 parent 28 3.2 NA 1 +#> 13 parent 60 NA NA 1 +#> 14 parent 60 NA NA 1 +#> 15 parent 90 0.6 NA 1 +#> 16 parent 90 NA NA 1 +#> 17 parent 120 NA NA 1 +#> 18 parent 120 3.5 NA 1 +#> 19 M1 0 NA NA 1 +#> 20 M1 0 NA NA 1 +#> 21 M1 1 36.4 NA 1 +#> 22 M1 1 37.4 NA 1 +#> 23 M1 3 34.3 NA 1 +#> 24 M1 3 39.8 NA 1 +#> 25 M1 7 15.1 NA 1 +#> 26 M1 7 17.8 NA 1 +#> 27 M1 14 5.8 NA 1 +#> 28 M1 14 1.2 NA 1 +#> 29 M1 28 NA NA 1 +#> 30 M1 28 NA NA 1 +#> 31 M1 60 0.5 NA 1 +#> 32 M1 60 NA NA 1 +#> 33 M1 90 NA NA 1 +#> 34 M1 90 3.2 NA 1 +#> 35 M1 120 1.5 NA 1 +#> 36 M1 120 0.6 NA 1 +#> 37 M2 0 NA NA 1 +#> 38 M2 0 NA NA 1 +#> 39 M2 1 NA NA 1 +#> 40 M2 1 4.8 NA 1 +#> 41 M2 3 20.9 NA 1 +#> 42 M2 3 19.3 NA 1 +#> 43 M2 7 42.0 NA 1 +#> 44 M2 7 43.1 NA 1 +#> 45 M2 14 49.4 NA 1 +#> 46 M2 14 44.3 NA 1 +#> 47 M2 28 34.6 NA 1 +#> 48 M2 28 33.0 NA 1 +#> 49 M2 60 18.8 NA 1 +#> 50 M2 60 17.6 NA 1 +#> 51 M2 90 10.6 NA 1 +#> 52 M2 90 10.8 NA 1 +#> 53 M2 120 9.8 NA 1 +#> 54 M2 120 3.3 NA 1 +#> +#> $obs_vars +#> [1] "parent" "M1" "M2" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 1.020625e+02 +#> 2 parent 1.000000 4.872881e+01 +#> 3 parent 1.212121 4.165603e+01 +#> 4 parent 2.424242 1.700159e+01 +#> 5 parent 3.000000 1.110773e+01 +#> 6 parent 3.636364 6.939072e+00 +#> 7 parent 4.848485 2.832130e+00 +#> 8 parent 6.060606 1.155912e+00 +#> 9 parent 7.000000 5.771704e-01 +#> 10 parent 7.272727 4.717769e-01 +#> 11 parent 8.484848 1.925522e-01 +#> 12 parent 9.696970 7.858872e-02 +#> 13 parent 10.909091 3.207539e-02 +#> 14 parent 12.121212 1.309133e-02 +#> 15 parent 13.333333 5.343128e-03 +#> 16 parent 14.000000 3.263939e-03 +#> 17 parent 14.545455 2.180757e-03 +#> 18 parent 15.757576 8.900590e-04 +#> 19 parent 16.969697 3.632705e-04 +#> 20 parent 18.181818 1.482660e-04 +#> 21 parent 19.393939 6.051327e-05 +#> 22 parent 20.606061 2.469808e-05 +#> 23 parent 21.818182 1.008035e-05 +#> 24 parent 23.030303 4.114467e-06 +#> 25 parent 24.242424 1.679140e-06 +#> 26 parent 25.454545 6.853728e-07 +#> 27 parent 26.666667 2.797450e-07 +#> 28 parent 27.878788 1.142138e-07 +#> 29 parent 28.000000 1.044512e-07 +#> 30 parent 29.090909 4.657425e-08 +#> 31 parent 30.303030 1.900245e-08 +#> 32 parent 31.515152 7.760238e-09 +#> 33 parent 32.727273 3.164577e-09 +#> 34 parent 33.939394 1.291779e-09 +#> 35 parent 35.151515 5.261577e-10 +#> 36 parent 36.363636 2.132915e-10 +#> 37 parent 37.575758 8.767818e-11 +#> 38 parent 38.787879 3.442792e-11 +#> 39 parent 40.000000 1.827291e-11 +#> 40 parent 41.212121 3.771071e-12 +#> 41 parent 42.424242 6.084856e-12 +#> 42 parent 43.636364 -3.377858e-12 +#> 43 parent 44.848485 5.870338e-12 +#> 44 parent 46.060606 -6.263257e-12 +#> 45 parent 47.272727 8.743492e-12 +#> 46 parent 48.484848 -9.381771e-12 +#> 47 parent 49.696970 1.403389e-11 +#> 48 parent 50.909091 -3.592528e-11 +#> 49 parent 52.121212 -8.487459e-11 +#> 50 parent 53.333333 -3.309153e-12 +#> 51 parent 54.545455 -2.966799e-11 +#> 52 parent 55.757576 -4.723329e-11 +#> 53 parent 56.969697 7.635833e-11 +#> 54 parent 58.181818 -1.887064e-11 +#> 55 parent 59.393939 -1.548352e-10 +#> 56 parent 60.000000 -1.053819e-10 +#> 57 parent 60.606061 5.780435e-12 +#> 58 parent 61.818182 9.056244e-11 +#> 59 parent 63.030303 -8.889581e-11 +#> 60 parent 64.242424 -6.653389e-11 +#> 61 parent 65.454545 1.181114e-10 +#> 62 parent 66.666667 -9.226329e-12 +#> 63 parent 67.878788 -8.897326e-11 +#> 64 parent 69.090909 1.984998e-10 +#> 65 parent 70.303030 3.255550e-11 +#> 66 parent 71.515152 -2.991002e-10 +#> 67 parent 72.727273 2.254268e-10 +#> 68 parent 73.939394 2.696039e-10 +#> 69 parent 75.151515 1.226806e-10 +#> 70 parent 76.363636 3.447399e-11 +#> 71 parent 77.575758 2.048902e-11 +#> 72 parent 78.787879 6.830755e-12 +#> 73 parent 80.000000 8.242171e-13 +#> 74 parent 81.212121 -5.357740e-12 +#> 75 parent 82.424242 2.198907e-11 +#> 76 parent 83.636364 3.739511e-11 +#> 77 parent 84.848485 -6.616091e-12 +#> 78 parent 86.060606 -2.562689e-12 +#> 79 parent 87.272727 4.089395e-11 +#> 80 parent 88.484848 -2.042159e-11 +#> 81 parent 89.696970 -4.088127e-11 +#> 82 parent 90.000000 -1.874889e-11 +#> 83 parent 90.909091 4.225747e-11 +#> 84 parent 92.121212 8.054402e-12 +#> 85 parent 93.333333 3.917595e-12 +#> 86 parent 94.545455 6.591454e-12 +#> 87 parent 95.757576 2.790958e-11 +#> 88 parent 96.969697 2.720721e-12 +#> 89 parent 98.181818 -1.304470e-12 +#> 90 parent 99.393939 1.345055e-11 +#> 91 parent 100.606061 -9.662077e-12 +#> 92 parent 101.818182 -2.086798e-11 +#> 93 parent 103.030303 9.332507e-12 +#> 94 parent 104.242424 -6.752606e-12 +#> 95 parent 105.454545 -3.326620e-11 +#> 96 parent 106.666667 2.500680e-11 +#> 97 parent 107.878788 2.184148e-11 +#> 98 parent 109.090909 -5.985657e-11 +#> 99 parent 110.303030 -8.750836e-14 +#> 100 parent 111.515152 1.820588e-12 +#> 101 parent 112.727273 -1.261472e-11 +#> 102 parent 113.939394 1.455439e-11 +#> 103 parent 115.151515 1.945812e-12 +#> 104 parent 116.363636 9.598249e-13 +#> 105 parent 117.575758 1.724679e-12 +#> 106 parent 118.787879 -1.334504e-12 +#> 107 parent 120.000000 -2.804801e-11 +#> 108 M1 0.000000 0.000000e+00 +#> 109 M1 1.000000 3.478911e+01 +#> 110 M1 1.212121 3.791354e+01 +#> 111 M1 2.424242 4.185645e+01 +#> 112 M1 3.000000 3.937027e+01 +#> 113 M1 3.636364 3.544167e+01 +#> 114 M1 4.848485 2.723995e+01 +#> 115 M1 6.060606 2.000711e+01 +#> 116 M1 7.000000 1.548714e+01 +#> 117 M1 7.272727 1.435144e+01 +#> 118 M1 8.484848 1.016177e+01 +#> 119 M1 9.696970 7.142649e+00 +#> 120 M1 10.909091 4.999441e+00 +#> 121 M1 12.121212 3.490801e+00 +#> 122 M1 13.333333 2.433954e+00 +#> 123 M1 14.000000 1.995311e+00 +#> 124 M1 14.545455 1.695664e+00 +#> 125 M1 15.757576 1.180746e+00 +#> 126 M1 16.969697 8.219589e-01 +#> 127 M1 18.181818 5.720991e-01 +#> 128 M1 19.393939 3.981531e-01 +#> 129 M1 20.606061 2.770793e-01 +#> 130 M1 21.818182 1.928162e-01 +#> 131 M1 23.030303 1.341758e-01 +#> 132 M1 24.242424 9.336844e-02 +#> 133 M1 25.454545 6.497152e-02 +#> 134 M1 26.666667 4.521101e-02 +#> 135 M1 27.878788 3.146041e-02 +#> 136 M1 28.000000 3.034005e-02 +#> 137 M1 29.090909 2.189192e-02 +#> 138 M1 30.303030 1.523362e-02 +#> 139 M1 31.515152 1.060040e-02 +#> 140 M1 32.727273 7.376345e-03 +#> 141 M1 33.939394 5.132870e-03 +#> 142 M1 35.151515 3.571730e-03 +#> 143 M1 36.363636 2.485406e-03 +#> 144 M1 37.575758 1.729482e-03 +#> 145 M1 38.787879 1.203467e-03 +#> 146 M1 40.000000 8.374380e-04 +#> 147 M1 41.212121 5.827347e-04 +#> 148 M1 42.424242 4.054989e-04 +#> 149 M1 43.636364 2.821681e-04 +#> 150 M1 44.848485 1.963481e-04 +#> 151 M1 46.060606 1.366297e-04 +#> 152 M1 47.272727 9.507439e-05 +#> 153 M1 48.484848 6.615797e-05 +#> 154 M1 49.696970 4.603629e-05 +#> 155 M1 50.909091 3.203434e-05 +#> 156 M1 52.121212 2.229196e-05 +#> 157 M1 53.333333 1.551223e-05 +#> 158 M1 54.545455 1.079420e-05 +#> 159 M1 55.757576 7.511255e-06 +#> 160 M1 56.969697 5.226640e-06 +#> 161 M1 58.181818 3.636450e-06 +#> 162 M1 59.393939 2.530191e-06 +#> 163 M1 60.000000 2.110651e-06 +#> 164 M1 60.606061 1.760625e-06 +#> 165 M1 61.818182 1.225095e-06 +#> 166 M1 63.030303 8.527010e-07 +#> 167 M1 64.242424 5.934161e-07 +#> 168 M1 65.454545 4.127474e-07 +#> 169 M1 66.666667 2.874114e-07 +#> 170 M1 67.878788 2.001921e-07 +#> 171 M1 69.090909 1.389331e-07 +#> 172 M1 70.303030 9.678549e-08 +#> 173 M1 71.515152 6.777214e-08 +#> 174 M1 72.727273 4.658761e-08 +#> 175 M1 73.939394 3.226837e-08 +#> 176 M1 75.151515 2.253752e-08 +#> 177 M1 76.363636 1.574843e-08 +#> 178 M1 77.575758 1.096303e-08 +#> 179 M1 78.787879 7.638209e-09 +#> 180 M1 80.000000 5.319996e-09 +#> 181 M1 81.212121 3.709993e-09 +#> 182 M1 82.424242 2.548810e-09 +#> 183 M1 83.636364 1.744629e-09 +#> 184 M1 84.848485 1.256081e-09 +#> 185 M1 86.060606 8.714672e-10 +#> 186 M1 87.272727 5.511830e-10 +#> 187 M1 88.484848 4.466725e-10 +#> 188 M1 89.696970 3.452654e-10 +#> 189 M1 90.000000 2.913252e-10 +#> 190 M1 90.909091 1.489262e-10 +#> 191 M1 92.121212 1.311985e-10 +#> 192 M1 93.333333 9.347248e-11 +#> 193 M1 94.545455 6.004640e-11 +#> 194 M1 95.757576 1.166926e-11 +#> 195 M1 96.969697 2.968203e-11 +#> 196 M1 98.181818 2.478228e-11 +#> 197 M1 99.393939 -1.291838e-12 +#> 198 M1 100.606061 2.366481e-11 +#> 199 M1 101.818182 3.472871e-11 +#> 200 M1 103.030303 -6.633877e-12 +#> 201 M1 104.242424 1.248743e-11 +#> 202 M1 105.454545 4.557313e-11 +#> 203 M1 106.666667 -3.046261e-11 +#> 204 M1 107.878788 -2.693037e-11 +#> 205 M1 109.090909 7.816593e-11 +#> 206 M1 110.303030 7.276098e-13 +#> 207 M1 111.515152 -1.922924e-12 +#> 208 M1 112.727273 1.658481e-11 +#> 209 M1 113.939394 -1.858452e-11 +#> 210 M1 115.151515 -2.368198e-12 +#> 211 M1 116.363636 -1.138989e-12 +#> 212 M1 117.575758 -2.157011e-12 +#> 213 M1 118.787879 1.771568e-12 +#> 214 M1 120.000000 3.624738e-11 +#> 215 M2 0.000000 0.000000e+00 +#> 216 M2 1.000000 4.454830e+00 +#> 217 M2 1.212121 6.103803e+00 +#> 218 M2 2.424242 1.667567e+01 +#> 219 M2 3.000000 2.152527e+01 +#> 220 M2 3.636364 2.637280e+01 +#> 221 M2 4.848485 3.384106e+01 +#> 222 M2 6.060606 3.910279e+01 +#> 223 M2 7.000000 4.192058e+01 +#> 224 M2 7.272727 4.256708e+01 +#> 225 M2 8.484848 4.467909e+01 +#> 226 M2 9.696970 4.581396e+01 +#> 227 M2 10.909091 4.625927e+01 +#> 228 M2 12.121212 4.622588e+01 +#> 229 M2 13.333333 4.586473e+01 +#> 230 M2 14.000000 4.556646e+01 +#> 231 M2 14.545455 4.528249e+01 +#> 232 M2 15.757576 4.455394e+01 +#> 233 M2 16.969697 4.373119e+01 +#> 234 M2 18.181818 4.285048e+01 +#> 235 M2 19.393939 4.193685e+01 +#> 236 M2 20.606061 4.100759e+01 +#> 237 M2 21.818182 4.007456e+01 +#> 238 M2 23.030303 3.914584e+01 +#> 239 M2 24.242424 3.822688e+01 +#> 240 M2 25.454545 3.732133e+01 +#> 241 M2 26.666667 3.643154e+01 +#> 242 M2 27.878788 3.555901e+01 +#> 243 M2 28.000000 3.547275e+01 +#> 244 M2 29.090909 3.470463e+01 +#> 245 M2 30.303030 3.386887e+01 +#> 246 M2 31.515152 3.305190e+01 +#> 247 M2 32.727273 3.225371e+01 +#> 248 M2 33.939394 3.147416e+01 +#> 249 M2 35.151515 3.071300e+01 +#> 250 M2 36.363636 2.996993e+01 +#> 251 M2 37.575758 2.924463e+01 +#> 252 M2 38.787879 2.853672e+01 +#> 253 M2 40.000000 2.784585e+01 +#> 254 M2 41.212121 2.717163e+01 +#> 255 M2 42.424242 2.651368e+01 +#> 256 M2 43.636364 2.587163e+01 +#> 257 M2 44.848485 2.524511e+01 +#> 258 M2 46.060606 2.463374e+01 +#> 259 M2 47.272727 2.403716e+01 +#> 260 M2 48.484848 2.345502e+01 +#> 261 M2 49.696970 2.288698e+01 +#> 262 M2 50.909091 2.233268e+01 +#> 263 M2 52.121212 2.179181e+01 +#> 264 M2 53.333333 2.126404e+01 +#> 265 M2 54.545455 2.074905e+01 +#> 266 M2 55.757576 2.024653e+01 +#> 267 M2 56.969697 1.975618e+01 +#> 268 M2 58.181818 1.927770e+01 +#> 269 M2 59.393939 1.881081e+01 +#> 270 M2 60.000000 1.858163e+01 +#> 271 M2 60.606061 1.835523e+01 +#> 272 M2 61.818182 1.791068e+01 +#> 273 M2 63.030303 1.747690e+01 +#> 274 M2 64.242424 1.705363e+01 +#> 275 M2 65.454545 1.664061e+01 +#> 276 M2 66.666667 1.623759e+01 +#> 277 M2 67.878788 1.584433e+01 +#> 278 M2 69.090909 1.546059e+01 +#> 279 M2 70.303030 1.508615e+01 +#> 280 M2 71.515152 1.472078e+01 +#> 281 M2 72.727273 1.436425e+01 +#> 282 M2 73.939394 1.401636e+01 +#> 283 M2 75.151515 1.367690e+01 +#> 284 M2 76.363636 1.334566e+01 +#> 285 M2 77.575758 1.302244e+01 +#> 286 M2 78.787879 1.270705e+01 +#> 287 M2 80.000000 1.239929e+01 +#> 288 M2 81.212121 1.209899e+01 +#> 289 M2 82.424242 1.180597e+01 +#> 290 M2 83.636364 1.152004e+01 +#> 291 M2 84.848485 1.124103e+01 +#> 292 M2 86.060606 1.096878e+01 +#> 293 M2 87.272727 1.070313e+01 +#> 294 M2 88.484848 1.044391e+01 +#> 295 M2 89.696970 1.019097e+01 +#> 296 M2 90.000000 1.012869e+01 +#> 297 M2 90.909091 9.944151e+00 +#> 298 M2 92.121212 9.703312e+00 +#> 299 M2 93.333333 9.468307e+00 +#> 300 M2 94.545455 9.238993e+00 +#> 301 M2 95.757576 9.015233e+00 +#> 302 M2 96.969697 8.796892e+00 +#> 303 M2 98.181818 8.583839e+00 +#> 304 M2 99.393939 8.375946e+00 +#> 305 M2 100.606061 8.173088e+00 +#> 306 M2 101.818182 7.975143e+00 +#> 307 M2 103.030303 7.781992e+00 +#> 308 M2 104.242424 7.593520e+00 +#> 309 M2 105.454545 7.409611e+00 +#> 310 M2 106.666667 7.230157e+00 +#> 311 M2 107.878788 7.055049e+00 +#> 312 M2 109.090909 6.884182e+00 +#> 313 M2 110.303030 6.717454e+00 +#> 314 M2 111.515152 6.554763e+00 +#> 315 M2 112.727273 6.396012e+00 +#> 316 M2 113.939394 6.241107e+00 +#> 317 M2 115.151515 6.089953e+00 +#> 318 M2 116.363636 5.942460e+00 +#> 319 M2 117.575758 5.798538e+00 +#> 320 M2 118.787879 5.658103e+00 +#> 321 M2 120.000000 5.521069e+00 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$model < cost.old) { +#> if (!quiet) +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") +#> if (plot) { +#> outtimes_plot = seq(min(observed$time), max(observed$time), +#> length.out = 100) +#> out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, +#> solution_type = solution_type, use_compiled = use_compiled, +#> method.ode = method.ode, atol = atol, rtol = rtol, +#> ...) +#> plot(0, type = "n", xlim = range(observed$time), +#> ylim = c(0, max(observed$value, na.rm = TRUE)), +#> xlab = "Time", ylab = "Observed") +#> col_obs <- pch_obs <- 1:length(obs_vars) +#> lty_obs <- rep(1, length(obs_vars)) +#> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars +#> for (obs_var in obs_vars) { +#> points(subset(observed, name == obs_var, c(time, +#> value)), pch = pch_obs[obs_var], col = col_obs[obs_var]) +#> } +#> matlines(out_plot$time, out_plot[-1], col = col_obs, +#> lty = lty_obs) +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) +#> } +#> assign("cost.old", mC$model, inherits = TRUE) +#> } +#> return(mC) +#> } +#> <environment: 0x3ff8420> +#> +#> $cost_notrans +#> function (P) +#> { +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> parms.fixed) +#> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> return(mC) +#> } +#> <environment: 0x3ff8420> +#> +#> $hessian_notrans +#> parent_0 k_parent k_M1 k_M2 f_parent_to_M1 +#> parent_0 8.433594 -40.12785 -61.53042 -3406.469 461.2995 +#> k_parent -40.127847 19322.43697 3053.54654 3740.691 8966.4055 +#> k_M1 -61.530424 3053.54654 70106.05907 7274.316 -8169.6841 +#> k_M2 -3406.468786 3740.69112 7274.31610 12274341.595 -452294.7998 +#> f_parent_to_M1 461.299501 8966.40549 -8169.68407 -452294.800 61249.1755 +#> f_M1_to_M2 327.648696 2884.22668 17504.38651 -480941.198 43503.6440 +#> f_M1_to_M2 +#> parent_0 327.6487 +#> k_parent 2884.2267 +#> k_M1 17504.3865 +#> k_M2 -480941.1983 +#> f_parent_to_M1 43503.6440 +#> f_M1_to_M2 46258.9775 +#> +#> $start +#> value type +#> parent_0 101.3500 state +#> k_parent 0.1000 deparm +#> k_M1 0.1001 deparm +#> k_M2 0.1002 deparm +#> f_parent_to_M1 0.5000 deparm +#> f_M1_to_M2 0.5000 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 101.350000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_M1 -2.301586 -Inf Inf +#> log_k_M2 -2.300587 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> f_M1_ilr_1 0.000000 -Inf Inf +#> +#> $fixed +#> value type +#> M1_0 0 state +#> M2_0 0 state +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 101.5 1.020625e+02 -0.56248353 +#> 2 0 parent 101.2 1.020625e+02 -0.86248353 +#> 3 1 parent 53.9 4.872881e+01 5.17118695 +#> 4 1 parent 47.5 4.872881e+01 -1.22881305 +#> 5 3 parent 10.4 1.110773e+01 -0.70772795 +#> 6 3 parent 7.6 1.110773e+01 -3.50772795 +#> 7 7 parent 1.1 5.771704e-01 0.52282962 +#> 8 7 parent 0.3 5.771704e-01 -0.27717038 +#> 9 14 parent NA 3.263939e-03 NA +#> 10 14 parent 3.5 3.263939e-03 3.49673606 +#> 11 28 parent NA 1.044512e-07 NA +#> 12 28 parent 3.2 1.044512e-07 3.19999990 +#> 13 60 parent NA -1.053819e-10 NA +#> 14 60 parent NA -1.053819e-10 NA +#> 15 90 parent 0.6 -1.874889e-11 0.60000000 +#> 16 90 parent NA -1.874889e-11 NA +#> 17 120 parent NA -2.804801e-11 NA +#> 18 120 parent 3.5 -2.804801e-11 3.50000000 +#> 19 0 M1 NA 0.000000e+00 NA +#> 20 0 M1 NA 0.000000e+00 NA +#> 21 1 M1 36.4 3.478911e+01 1.61088639 +#> 22 1 M1 37.4 3.478911e+01 2.61088639 +#> 23 3 M1 34.3 3.937027e+01 -5.07026619 +#> 24 3 M1 39.8 3.937027e+01 0.42973381 +#> 25 7 M1 15.1 1.548714e+01 -0.38714436 +#> 26 7 M1 17.8 1.548714e+01 2.31285564 +#> 27 14 M1 5.8 1.995311e+00 3.80468869 +#> 28 14 M1 1.2 1.995311e+00 -0.79531131 +#> 29 28 M1 NA 3.034005e-02 NA +#> 30 28 M1 NA 3.034005e-02 NA +#> 31 60 M1 0.5 2.110651e-06 0.49999789 +#> 32 60 M1 NA 2.110651e-06 NA +#> 33 90 M1 NA 2.913252e-10 NA +#> 34 90 M1 3.2 2.913252e-10 3.20000000 +#> 35 120 M1 1.5 3.624738e-11 1.50000000 +#> 36 120 M1 0.6 3.624738e-11 0.60000000 +#> 37 0 M2 NA 0.000000e+00 NA +#> 38 0 M2 NA 0.000000e+00 NA +#> 39 1 M2 NA 4.454830e+00 NA +#> 40 1 M2 4.8 4.454830e+00 0.34517017 +#> 41 3 M2 20.9 2.152527e+01 -0.62526794 +#> 42 3 M2 19.3 2.152527e+01 -2.22526794 +#> 43 7 M2 42.0 4.192058e+01 0.07941701 +#> 44 7 M2 43.1 4.192058e+01 1.17941701 +#> 45 14 M2 49.4 4.556646e+01 3.83353798 +#> 46 14 M2 44.3 4.556646e+01 -1.26646202 +#> 47 28 M2 34.6 3.547275e+01 -0.87274743 +#> 48 28 M2 33.0 3.547275e+01 -2.47274743 +#> 49 60 M2 18.8 1.858163e+01 0.21837410 +#> 50 60 M2 17.6 1.858163e+01 -0.98162590 +#> 51 90 M2 10.6 1.012869e+01 0.47130583 +#> 52 90 M2 10.8 1.012869e+01 0.67130583 +#> 53 120 M2 9.8 5.521069e+00 4.27893112 +#> 54 120 M2 3.3 5.521069e+00 -2.22106888 +#> +#> $atol +#> [1] 1e-08 +#> +#> $rtol +#> [1] 1e-10 +#> +#> $weight.ini +#> [1] "none" +#> +#> $reweight.tol +#> [1] 1e-08 +#> +#> $reweight.max.iter +#> [1] 10 +#> +#> $bparms.optim +#> parent_0 k_parent k_M1 k_M2 f_parent_to_M1 +#> 102.0624835 0.7393147 0.2991566 0.0202267 0.7686858 +#> f_M1_to_M2 +#> 0.7229005 +#> +#> $bparms.fixed +#> M1_0 M2_0 +#> 0 0 +#> +#> $bparms.ode +#> k_parent f_parent_to_M1 k_M1 f_M1_to_M2 k_M2 +#> 0.7393147 0.7686858 0.2991566 0.7229005 0.0202267 +#> +#> $bparms.state +#> parent M1 M2 +#> 102.0625 0.0000 0.0000 +#> +#> $date +#> [1] "Fri Nov 18 15:20:48 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit" </div><div class='input'> +</div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> <h2>Contents</h2> |