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-rw-r--r--docs/dev/pkgdown.yml2
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-rw-r--r--docs/dev/reference/transform_odeparms.html159
40 files changed, 972 insertions, 406 deletions
diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html
index 4e31f4b7..3980ea88 100644
--- a/docs/dev/news/index.html
+++ b/docs/dev/news/index.html
@@ -146,6 +146,8 @@
<a href="#mkin-0-9-50-4-unreleased" class="anchor"></a>mkin 0.9.50.4 (unreleased)<small> Unreleased </small>
</h1>
<ul>
+<li><p>‘transform_odeparms’, ‘backtransform_odeparms’: Use logit transformation for solitary fractions like the g parameter of the DFOP model, or formation fractions for a pathway to only one target variable</p></li>
+<li><p>‘update’ method for ‘mmkin’ objects</p></li>
<li><p>‘plot’, ‘summary’ and ‘print’ methods for ‘nlme.mmkin’ objects</p></li>
<li><p>‘saemix_model’, ‘saemix_data’: Helper functions to fit nonlinear mixed-effects models for mmkin row objects using the saemix package</p></li>
</ul>
diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml
index 6d59c7cb..7b186c37 100644
--- a/docs/dev/pkgdown.yml
+++ b/docs/dev/pkgdown.yml
@@ -10,7 +10,7 @@ articles:
web_only/NAFTA_examples: NAFTA_examples.html
web_only/benchmarks: benchmarks.html
web_only/compiled_models: compiled_models.html
-last_built: 2020-11-05T07:25Z
+last_built: 2020-11-05T22:53Z
urls:
reference: https://pkgdown.jrwb.de/mkin/reference
article: https://pkgdown.jrwb.de/mkin/articles
diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png
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diff --git a/docs/dev/reference/mkinfit-1.png b/docs/dev/reference/mkinfit-1.png
new file mode 100644
index 00000000..eed9064f
--- /dev/null
+++ b/docs/dev/reference/mkinfit-1.png
Binary files differ
diff --git a/docs/dev/reference/mkinfit.html b/docs/dev/reference/mkinfit.html
index 39bd12cb..b46c2cce 100644
--- a/docs/dev/reference/mkinfit.html
+++ b/docs/dev/reference/mkinfit.html
@@ -307,12 +307,11 @@ a lower bound for the rates in the optimisation.</p></td>
<tr>
<th>transform_fractions</th>
<td><p>Boolean specifying if formation fractions
-constants should be transformed in the model specification used in the
-fitting for better compliance with the assumption of normal distribution
-of the estimator. The default (TRUE) is to do transformations. If TRUE,
-the g parameter of the DFOP and HS models are also transformed, as they
-can also be seen as compositional data. The transformation used for these
-transformations is the <code><a href='ilr.html'>ilr()</a></code> transformation.</p></td>
+should be transformed in the model specification used in the fitting for
+better compliance with the assumption of normal distribution of the
+estimator. The default (TRUE) is to do transformations. If TRUE,
+the g parameter of the DFOP model is also transformed. Transformations
+are described in <a href='transform_odeparms.html'>transform_odeparms</a>.</p></td>
</tr>
<tr>
<th>quiet</th>
@@ -433,15 +432,15 @@ Degradation Data. <em>Environments</em> 6(12) 124
<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'>#&gt; mkin version used for fitting: 0.9.50.4
#&gt; R version used for fitting: 4.0.3
-#&gt; Date of fit: Thu Nov 5 08:25:42 2020
-#&gt; Date of summary: Thu Nov 5 08:25:42 2020
+#&gt; Date of fit: Thu Nov 5 23:14:40 2020
+#&gt; Date of summary: Thu Nov 5 23:14:40 2020
#&gt;
#&gt; Equations:
#&gt; d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
#&gt;
#&gt; Model predictions using solution type analytical
#&gt;
-#&gt; Fitted using 222 model solutions performed in 0.049 s
+#&gt; Fitted using 222 model solutions performed in 0.05 s
#&gt;
#&gt; Error model: Constant variance
#&gt;
@@ -521,8 +520,8 @@ Degradation Data. <em>Environments</em> 6(12) 124
</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
<span class='co'># Fit the model quietly to the FOCUS example dataset D using defaults</span>
<span class='va'>fit</span> <span class='op'>&lt;-</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><span class='op'>)</span>
-<span class='co'># Since mkin 0.9.50.3, we get a warning about non-normality of residuals,</span>
-<span class='co'># so we try an alternative error model</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='mkinfit-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># As lower parent values appear to have lower variance, we try an alternative error model</span>
<span class='va'>fit.tc</span> <span class='op'>&lt;-</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><span class='op'>)</span>
<span class='co'># This avoids the warning, and the likelihood ratio test confirms it is preferable</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</span><span class='op'>)</span>
@@ -536,8 +535,7 @@ Degradation Data. <em>Environments</em> 6(12) 124
#&gt; ---
#&gt; Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'># We can also allow for different variances of parent and metabolite as error model</span>
<span class='va'>fit.obs</span> <span class='op'>&lt;-</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'>"obs"</span><span class='op'>)</span>
-<span class='co'># This also avoids the warning about non-normality, but the two-component error model</span>
-<span class='co'># has significantly higher likelihood</span>
+<span class='co'># The two-component error model has significantly higher likelihood</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.obs</span>, <span class='va'>fit.tc</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihood ratio test
#&gt;
@@ -549,9 +547,9 @@ Degradation Data. <em>Environments</em> 6(12) 124
#&gt; ---
#&gt; 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'>#&gt; parent_0 k_parent k_m1 f_parent_to_m1 sigma_low
-#&gt; 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049891e-03
+#&gt; 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049884e-03
#&gt; rsd_high
-#&gt; 7.928117e-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>
+#&gt; 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'>#&gt; $ff
#&gt; parent_m1 parent_sink
#&gt; 0.5083933 0.4916067
@@ -559,7 +557,7 @@ Degradation Data. <em>Environments</em> 6(12) 124
#&gt; $distimes
#&gt; DT50 DT90
#&gt; parent 6.89313 22.89848
-#&gt; m1 134.15635 445.65776
+#&gt; m1 134.15634 445.65772
#&gt; </div><div class='input'>
<span class='co'># We can show a quick (only one replication) benchmark for this case, as we</span>
<span class='co'># have several alternative solution methods for the model. We skip</span>
@@ -576,9 +574,9 @@ Degradation Data. <em>Environments</em> 6(12) 124
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'>#&gt; <span class='message'>Loading required package: rbenchmark</span></div><div class='output co'>#&gt; test relative elapsed
-#&gt; 3 analytical 1.000 0.746
-#&gt; 1 deSolve_compiled 2.288 1.707
-#&gt; 2 eigen 2.708 2.020</div><div class='input'><span class='co'># }</span>
+#&gt; 3 analytical 1.000 0.532
+#&gt; 1 deSolve_compiled 1.765 0.939
+#&gt; 2 eigen 2.229 1.186</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>
@@ -588,21 +586,22 @@ Degradation Data. <em>Environments</em> 6(12) 124
</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='va'>fit.FOMC_SFO</span> <span class='op'>&lt;-</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'>&lt;-</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>
-<span class='co'># This model has a higher likelihood, but not significantly so</span>
+</div><div class='output co'>#&gt; <span class='warning'>Warning: Optimisation did not converge:</span>
+#&gt; <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='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'>#&gt; Likelihood ratio test
#&gt;
#&gt; Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0
#&gt; Model 2: SFO_SFO with error model tc and fixed parameter(s) m1_0
#&gt; #Df LogLik Df Chisq Pr(&gt;Chisq)
-#&gt; 1 7 -64.829
-#&gt; 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>
+#&gt; 1 7 -64.870
+#&gt; 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>
<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'>#&gt; <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#&gt; <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#&gt; <span class='warning'>Warning: diag(.) had 0 or NA entries; non-finite result is doubtful</span></div><div class='output co'>#&gt; mkin version used for fitting: 0.9.50.4
+</div><div class='output co'>#&gt; <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#&gt; <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#&gt; <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#&gt; <span class='warning'>Warning: diag(.) had 0 or NA entries; non-finite result is doubtful</span></div><div class='output co'>#&gt; mkin version used for fitting: 0.9.50.4
#&gt; R version used for fitting: 4.0.3
-#&gt; Date of fit: Thu Nov 5 08:25:56 2020
-#&gt; Date of summary: Thu Nov 5 08:25:56 2020
+#&gt; Date of fit: Thu Nov 5 23:14:51 2020
+#&gt; Date of summary: Thu Nov 5 23:14:51 2020
#&gt;
#&gt; Equations:
#&gt; d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
@@ -611,7 +610,7 @@ Degradation Data. <em>Environments</em> 6(12) 124
#&gt;
#&gt; Model predictions using solution type deSolve
#&gt;
-#&gt; Fitted using 3611 model solutions performed in 2.673 s
+#&gt; Fitted using 4273 model solutions performed in 3.081 s
#&gt;
#&gt; Error model: Two-component variance function
#&gt;
@@ -629,80 +628,85 @@ Degradation Data. <em>Environments</em> 6(12) 124
#&gt; rsd_high 0.10 error
#&gt;
#&gt; Starting values for the transformed parameters actually optimised:
-#&gt; value lower upper
-#&gt; parent_0 100.750000 -Inf Inf
-#&gt; log_k_m1 -2.302585 -Inf Inf
-#&gt; f_parent_ilr_1 0.000000 -Inf Inf
-#&gt; log_alpha 0.000000 -Inf Inf
-#&gt; log_beta 2.302585 -Inf Inf
-#&gt; sigma_low 0.100000 0 Inf
-#&gt; rsd_high 0.100000 0 Inf
+#&gt; value lower upper
+#&gt; parent_0 100.750000 -Inf Inf
+#&gt; log_k_m1 -2.302585 -Inf Inf
+#&gt; f_parent_qlogis 0.000000 -Inf Inf
+#&gt; log_alpha 0.000000 -Inf Inf
+#&gt; log_beta 2.302585 -Inf Inf
+#&gt; sigma_low 0.100000 0 Inf
+#&gt; rsd_high 0.100000 0 Inf
#&gt;
#&gt; Fixed parameter values:
#&gt; value type
#&gt; m1_0 0 state
#&gt;
+#&gt;
+#&gt; Warning(s):
+#&gt; Optimisation did not converge:
+#&gt; iteration limit reached without convergence (10)
+#&gt;
#&gt; Results:
#&gt;
-#&gt; AIC BIC logLik
-#&gt; 143.658 155.1211 -64.82902
+#&gt; AIC BIC logLik
+#&gt; 143.7396 155.2027 -64.86982
#&gt;
#&gt; Optimised, transformed parameters with symmetric confidence intervals:
-#&gt; Estimate Std. Error Lower Upper
-#&gt; parent_0 101.600000 2.6390000 96.240000 107.000000
-#&gt; log_k_m1 -5.284000 0.0928900 -5.473000 -5.095000
-#&gt; f_parent_ilr_1 0.001008 0.0541900 -0.109500 0.111500
-#&gt; log_alpha 5.522000 0.0077300 5.506000 5.538000
-#&gt; log_beta 7.806000 NaN NaN NaN
-#&gt; sigma_low 0.002488 0.0002431 0.001992 0.002984
-#&gt; rsd_high 0.079210 0.0093280 0.060180 0.098230
+#&gt; Estimate Std. Error Lower Upper
+#&gt; parent_0 1.016e+02 1.90600 97.7400 105.5000
+#&gt; log_k_m1 -5.285e+00 0.09286 -5.4740 -5.0950
+#&gt; f_parent_qlogis 6.482e-04 0.06164 -0.1251 0.1264
+#&gt; log_alpha 5.467e+00 NaN NaN NaN
+#&gt; log_beta 7.750e+00 NaN NaN NaN
+#&gt; sigma_low 0.000e+00 NaN NaN NaN
+#&gt; rsd_high 7.989e-02 NaN NaN NaN
#&gt;
#&gt; Parameter correlation:
-#&gt; parent_0 log_k_m1 f_parent_ilr_1 log_alpha log_beta sigma_low
-#&gt; parent_0 1.000000 -0.094697 -0.76654 0.70525 NaN 0.016099
-#&gt; log_k_m1 -0.094697 1.000000 0.51404 -0.14347 NaN 0.001576
-#&gt; f_parent_ilr_1 -0.766543 0.514038 1.00000 -0.61368 NaN 0.015465
-#&gt; log_alpha 0.705247 -0.143468 -0.61368 1.00000 NaN 5.871780
-#&gt; log_beta NaN NaN NaN NaN 1 NaN
-#&gt; sigma_low 0.016099 0.001576 0.01546 5.87178 NaN 1.000000
-#&gt; rsd_high 0.006566 -0.011662 -0.05353 0.04845 NaN -0.652554
-#&gt; rsd_high
-#&gt; parent_0 0.006566
-#&gt; log_k_m1 -0.011662
-#&gt; f_parent_ilr_1 -0.053525
-#&gt; log_alpha 0.048451
-#&gt; log_beta NaN
-#&gt; sigma_low -0.652554
-#&gt; rsd_high 1.000000
+#&gt; parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta
+#&gt; parent_0 1.0000000 -0.0002167 -0.6060 NaN NaN
+#&gt; log_k_m1 -0.0002167 1.0000000 0.5474 NaN NaN
+#&gt; f_parent_qlogis -0.6060320 0.5474423 1.0000 NaN NaN
+#&gt; log_alpha NaN NaN NaN 1 NaN
+#&gt; log_beta NaN NaN NaN NaN 1
+#&gt; sigma_low NaN NaN NaN NaN NaN
+#&gt; rsd_high NaN NaN NaN NaN NaN
+#&gt; sigma_low rsd_high
+#&gt; parent_0 NaN NaN
+#&gt; log_k_m1 NaN NaN
+#&gt; f_parent_qlogis NaN NaN
+#&gt; log_alpha NaN NaN
+#&gt; log_beta NaN NaN
+#&gt; sigma_low 1 NaN
+#&gt; rsd_high NaN 1
#&gt;
#&gt; Backtransformed parameters:
#&gt; Confidence intervals for internally transformed parameters are asymmetric.
#&gt; t-test (unrealistically) based on the assumption of normal distribution
#&gt; for estimators of untransformed parameters.
#&gt; Estimate t value Pr(&gt;t) Lower Upper
-#&gt; parent_0 1.016e+02 32.7800 6.312e-26 9.624e+01 1.070e+02
-#&gt; k_m1 5.072e-03 10.1200 1.216e-11 4.197e-03 6.130e-03
-#&gt; f_parent_to_m1 5.004e-01 20.8300 4.318e-20 4.614e-01 5.394e-01
-#&gt; alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02
-#&gt; beta 2.455e+03 0.5549 2.915e-01 NA NA
-#&gt; sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03
-#&gt; rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02
+#&gt; parent_0 1.016e+02 32.5400 7.812e-26 97.740000 1.055e+02
+#&gt; k_m1 5.069e-03 10.0400 1.448e-11 0.004194 6.126e-03
+#&gt; f_parent_to_m1 5.002e-01 20.7300 5.001e-20 0.468800 5.315e-01
+#&gt; alpha 2.367e+02 0.6205 2.697e-01 NA NA
+#&gt; beta 2.322e+03 0.6114 2.727e-01 NA NA
+#&gt; sigma_low 0.000e+00 NaN NaN NaN NaN
+#&gt; rsd_high 7.989e-02 8.6630 4.393e-10 NaN NaN
#&gt;
#&gt; FOCUS Chi2 error levels in percent:
#&gt; err.min n.optim df
-#&gt; All data 6.781 5 14
-#&gt; parent 7.141 3 6
-#&gt; m1 4.640 2 8
+#&gt; All data 6.782 5 14
+#&gt; parent 7.142 3 6
+#&gt; m1 4.639 2 8
#&gt;
#&gt; Resulting formation fractions:
#&gt; ff
-#&gt; parent_m1 0.5004
-#&gt; parent_sink 0.4996
+#&gt; parent_m1 0.5002
+#&gt; parent_sink 0.4998
#&gt;
#&gt; Estimated disappearance times:
-#&gt; DT50 DT90 DT50back
-#&gt; parent 6.812 22.7 6.834
-#&gt; m1 136.661 454.0 NA</div><div class='input'>
+#&gt; DT50 DT90 DT50back
+#&gt; parent 6.81 22.7 6.833
+#&gt; m1 136.74 454.2 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'>&lt;-</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/mmkin-1.png b/docs/dev/reference/mmkin-1.png
index 135d5446..7b7da90a 100644
--- a/docs/dev/reference/mmkin-1.png
+++ b/docs/dev/reference/mmkin-1.png
Binary files differ
diff --git a/docs/dev/reference/mmkin-2.png b/docs/dev/reference/mmkin-2.png
index 40109afc..ce2b2af4 100644
--- a/docs/dev/reference/mmkin-2.png
+++ b/docs/dev/reference/mmkin-2.png
Binary files differ
diff --git a/docs/dev/reference/mmkin-3.png b/docs/dev/reference/mmkin-3.png
index bce34531..bb96f1b2 100644
--- a/docs/dev/reference/mmkin-3.png
+++ b/docs/dev/reference/mmkin-3.png
Binary files differ
diff --git a/docs/dev/reference/mmkin-4.png b/docs/dev/reference/mmkin-4.png
index 02976ced..351b21aa 100644
--- a/docs/dev/reference/mmkin-4.png
+++ b/docs/dev/reference/mmkin-4.png
Binary files differ
diff --git a/docs/dev/reference/mmkin-5.png b/docs/dev/reference/mmkin-5.png
index 56750342..c1c05eea 100644
--- a/docs/dev/reference/mmkin-5.png
+++ b/docs/dev/reference/mmkin-5.png
Binary files differ
diff --git a/docs/dev/reference/mmkin.html b/docs/dev/reference/mmkin.html
index a5d7ba42..b0ca90f0 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">0.9.50.3</span>
+ <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span>
</span>
</div>
@@ -123,7 +123,7 @@ datasets specified in its first two arguments." />
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
- <a href="http://github.com/jranke/mkin/">
+ <a href="https://github.com/jranke/mkin/">
<span class="fab fa fab fa-github fa-lg"></span>
</a>
@@ -143,7 +143,7 @@ datasets specified in its first two arguments." />
<div class="page-header">
<h1>Fit one or more kinetic models with one or more state variables to one or
more datasets</h1>
- <small class="dont-index">Source: <a href='http://github.com/jranke/mkin/blob/master/R/mmkin.R'><code>R/mmkin.R</code></a></small>
+ <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/mmkin.R'><code>R/mmkin.R</code></a></small>
<div class="hidden name"><code>mmkin.Rd</code></div>
</div>
@@ -152,13 +152,13 @@ more datasets</h1>
datasets specified in its first two arguments.</p>
</div>
- <pre class="usage"><span class='fu'>mmkin</span>(
- <span class='kw'>models</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span>),
- <span class='no'>datasets</span>,
- <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fu'>detectCores</span>(),
- <span class='kw'>cluster</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
- <span class='no'>...</span>
-)</pre>
+ <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>,
+ cluster <span class='op'>=</span> <span class='cn'>NULL</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">
@@ -201,45 +201,58 @@ first index (row index) and the dataset names for the second index (column
index).</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
- <div class='dont-index'><p><code><a href='Extract.mmkin.html'>[.mmkin</a></code> for subsetting, <code><a href='plot.mmkin.html'>plot.mmkin</a></code> for
+ <div class='dont-index'><p><code><a href='[.mmkin.html'>[.mmkin</a></code> for subsetting, <code><a href='plot.mmkin.html'>plot.mmkin</a></code> for
plotting.</p></div>
+ <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
+
+ <p>Johannes Ranke</p>
<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='no'>m_synth_SFO_lin</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"M1"</span>),
- <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"M2"</span>),
- <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
-<span class='no'>m_synth_FOMC_lin</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"FOMC"</span>, <span class='st'>"M1"</span>),
- <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"M2"</span>),
- <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
-<span class='no'>models</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>SFO_lin</span> <span class='kw'>=</span> <span class='no'>m_synth_SFO_lin</span>, <span class='kw'>FOMC_lin</span> <span class='kw'>=</span> <span class='no'>m_synth_FOMC_lin</span>)
-<span class='no'>datasets</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span>(<span class='no'>synthetic_data_for_UBA_2014</span>[<span class='fl'>1</span>:<span class='fl'>3</span>], <span class='kw'>function</span>(<span class='no'>x</span>) <span class='no'>x</span>$<span class='no'>data</span>)
-<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span>(<span class='no'>datasets</span>) <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span>(<span class='st'>"Dataset"</span>, <span class='fl'>1</span>:<span class='fl'>3</span>)
-
-<span class='no'>time_default</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>fits.0</span> <span class='kw'>&lt;-</span> <span class='fu'>mmkin</span>(<span class='no'>models</span>, <span class='no'>datasets</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))
-<span class='no'>time_1</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>fits.4</span> <span class='kw'>&lt;-</span> <span class='fu'>mmkin</span>(<span class='no'>models</span>, <span class='no'>datasets</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div><div class='output co'>#&gt; <span class='warning'>Warning: Optimisation did not converge:</span>
-#&gt; <span class='warning'>false convergence (8)</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Shapiro-Wilk test for standardized residuals: p = 0.0117</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Shapiro-Wilk test for standardized residuals: p = 0.0174</span></div><div class='input'>
-<span class='no'>time_default</span></div><div class='output co'>#&gt; user system elapsed
-#&gt; 4.500 0.399 1.311 </div><div class='input'><span class='no'>time_1</span></div><div class='output co'>#&gt; user system elapsed
-#&gt; 5.154 0.008 5.165 </div><div class='input'>
-<span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fits.0</span><span class='kw'>[[</span><span class='st'>"SFO_lin"</span>, <span class='fl'>2</span>]])</div><div class='output co'>#&gt; $ff
+<span class='va'>m_synth_SFO_lin</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='mkinsub.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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"M2"</span><span class='op'>)</span>,
+ M2 <span class='op'>=</span> <span class='fu'><a href='mkinsub.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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
+<span class='va'>m_synth_FOMC_lin</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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"M1"</span><span class='op'>)</span>,
+ M1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"M2"</span><span class='op'>)</span>,
+ M2 <span class='op'>=</span> <span class='fu'><a href='mkinsub.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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
+<span class='va'>models</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>SFO_lin <span class='op'>=</span> <span class='va'>m_synth_SFO_lin</span>, FOMC_lin <span class='op'>=</span> <span class='va'>m_synth_FOMC_lin</span><span class='op'>)</span>
+<span class='va'>datasets</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>synthetic_data_for_UBA_2014</span><span class='op'>[</span><span class='fl'>1</span><span class='op'>:</span><span class='fl'>3</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/names.html'>names</a></span><span class='op'>(</span><span class='va'>datasets</span><span class='op'>)</span> <span class='op'>&lt;-</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'>1</span><span class='op'>:</span><span class='fl'>3</span><span class='op'>)</span>
+
+<span class='va'>time_default</span> <span class='op'>&lt;-</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'>fits.0</span> <span class='op'>&lt;-</span> <span class='fu'>mmkin</span><span class='op'>(</span><span class='va'>models</span>, <span class='va'>datasets</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span>
+<span class='va'>time_1</span> <span class='op'>&lt;-</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'>fits.4</span> <span class='op'>&lt;-</span> <span class='fu'>mmkin</span><span class='op'>(</span><span class='va'>models</span>, <span class='va'>datasets</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>
+
+<span class='va'>time_default</span>
+</div><div class='output co'>#&gt; user system elapsed
+#&gt; 4.706 0.488 1.375 </div><div class='input'><span class='va'>time_1</span>
+</div><div class='output co'>#&gt; user system elapsed
+#&gt; 5.232 0.005 5.238 </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'>#&gt; $ff
#&gt; parent_M1 parent_sink M1_M2 M1_sink
-#&gt; 0.7340478 0.2659522 0.7505691 0.2494309
+#&gt; 0.7340478 0.2659522 0.7505687 0.2494313
#&gt;
#&gt; $distimes
-#&gt; DT50 DT90
-#&gt; parent 0.8777688 2.915885
-#&gt; M1 2.3257466 7.725963
-#&gt; M2 33.7200800 112.015681
+#&gt; DT50 DT90
+#&gt; parent 0.877769 2.915885
+#&gt; M1 2.325746 7.725960
+#&gt; M2 33.720083 112.015691
#&gt; </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/base/plot.html'>plot</a></span>(<span class='no'>fits.0</span>[<span class='fl'>1</span>, ])</div><div class='img'><img src='mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/plot.html'>plot</a></span>(<span class='no'>fits.0</span>[<span class='fl'>1</span>, ], <span class='kw'>obs_var</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>))</div><div class='img'><img src='mmkin-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/plot.html'>plot</a></span>(<span class='no'>fits.0</span>[, <span class='fl'>1</span>])</div><div class='img'><img src='mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># Use double brackets to extract a single mkinfit object, which will be plotted</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>
+</div><div class='img'><img src='mmkin-1.png' alt='' width='700' height='433' /></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'>fits.0</span><span class='op'>[</span><span class='fl'>1</span>, <span class='op'>]</span>, obs_var <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'>"M1"</span>, <span class='st'>"M2"</span><span class='op'>)</span><span class='op'>)</span>
+</div><div class='img'><img src='mmkin-2.png' alt='' width='700' height='433' /></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'>fits.0</span><span class='op'>[</span>, <span class='fl'>1</span><span class='op'>]</span><span class='op'>)</span>
+</div><div class='img'><img src='mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># Use double brackets to extract a single mkinfit object, which will be plotted</span>
<span class='co'># by plot.mkinfit and can be plotted using plot_sep</span>
-<span class='fu'><a href='https://rdrr.io/r/base/plot.html'>plot</a></span>(<span class='no'>fits.0</span><span class='kw'>[[</span><span class='fl'>1</span>, <span class='fl'>1</span>]], <span class='kw'>sep_obs</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>show_residuals</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>show_errmin</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='img'><img src='mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>fits.0</span><span class='kw'>[[</span><span class='fl'>1</span>, <span class='fl'>1</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='fl'>1</span><span class='op'>]</span><span class='op'>]</span>, sep_obs <span class='op'>=</span> <span class='cn'>TRUE</span>, show_residuals <span class='op'>=</span> <span class='cn'>TRUE</span>, show_errmin <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
+</div><div class='img'><img src='mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>fits.0</span><span class='op'>[[</span><span class='fl'>1</span>, <span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span>
<span class='co'># Plotting with mmkin (single brackets, extracting an mmkin object) does not</span>
<span class='co'># allow to plot the observed variables separately</span>
-<span class='fu'><a href='https://rdrr.io/r/base/plot.html'>plot</a></span>(<span class='no'>fits.0</span>[<span class='fl'>1</span>, <span class='fl'>1</span>])</div><div class='img'><img src='mmkin-5.png' alt='' width='700' height='433' /></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'>fits.0</span><span class='op'>[</span><span class='fl'>1</span>, <span class='fl'>1</span><span class='op'>]</span><span class='op'>)</span>
+</div><div class='img'><img src='mmkin-5.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span>
</div></pre>
</div>
@@ -257,7 +270,7 @@ plotting.</p></div>
</div>
<div class="pkgdown">
- <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.</p>
+ <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>
diff --git a/docs/dev/reference/saemix-1.png b/docs/dev/reference/saemix-1.png
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diff --git a/docs/dev/reference/saemix-8.png b/docs/dev/reference/saemix-8.png
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diff --git a/docs/dev/reference/saemix-9.png b/docs/dev/reference/saemix-9.png
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diff --git a/docs/dev/reference/saemix.html b/docs/dev/reference/saemix.html
index c8cf9fab..5dacefc9 100644
--- a/docs/dev/reference/saemix.html
+++ b/docs/dev/reference/saemix.html
@@ -190,16 +190,15 @@ mmkin. Starting variances of the random effects (argument omega.init) are the
variances of the deviations of the parameters from these mean values.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
- <pre class="examples"><div class='input'><span class='va'>ds</span> <span class='op'>&lt;-</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'>&lt;-</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'>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='mkinsub.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='mkinsub.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'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='co'># \dontrun{</span>
-<span class='va'>f_mmkin</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/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='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
+ <pre class="examples"><div class='input'><span class='co'># \dontrun{</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='va'>m_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
+#&gt; <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='input'><span class='va'>ds</span> <span class='op'>&lt;-</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/pkg/saemix/man/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'>&lt;-</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_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>ds</span>, cores <span class='op'>=</span> <span class='fl'>1</span>,
+ 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'>m_saemix_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixModel object was successfully created:
@@ -208,59 +207,236 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; Model function: Mixed model generated from mmkin object Model type: structural
#&gt; function (psi, id, xidep)
#&gt; {
-#&gt; uid &lt;- unique(id)
-#&gt; res_list &lt;- parallel::mclapply(uid, function(i) {
-#&gt; transparms_optim &lt;- psi[i, ]
-#&gt; names(transparms_optim) &lt;- names(degparms_optim)
-#&gt; odeini_optim &lt;- transparms_optim[odeini_optim_parm_names]
-#&gt; names(odeini_optim) &lt;- gsub("_0$", "", odeini_optim_parm_names)
-#&gt; odeini &lt;- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
-#&gt; ode_transparms_optim_names &lt;- setdiff(names(transparms_optim),
-#&gt; odeini_optim_parm_names)
-#&gt; odeparms_optim &lt;- backtransform_odeparms(transparms_optim[ode_transparms_optim_names],
-#&gt; mkin_model, transform_rates = object[[1]]$transform_rates,
-#&gt; transform_fractions = object[[1]]$transform_fractions)
-#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
-#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
-#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
-#&gt; odeparms)
-#&gt; }
-#&gt; else {
-#&gt; i_time &lt;- xidep_i$time
-#&gt; i_name &lt;- xidep_i$name
-#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
-#&gt; outtimes = sort(unique(i_time)))
-#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
-#&gt; out_values &lt;- out_wide[out_index]
-#&gt; }
-#&gt; return(out_values)
-#&gt; }, mc.cores = cores)
-#&gt; res &lt;- unlist(res_list)
-#&gt; return(res)
+#&gt; odeini_fixed/(xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id,
+#&gt; 1])
+#&gt; }
+#&gt; &lt;bytecode: 0x5555599945b8&gt;
+#&gt; &lt;environment: 0x555559984388&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] log_alpha normal Estimated
+#&gt; [2,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; log_alpha log_beta
+#&gt; log_alpha 1 0
+#&gt; log_beta 0 1
+#&gt; Error model: constant , initial values: a.1=2.95893806804889
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; log_alpha log_beta
+#&gt; Pop.CondInit -0.347996 1.66788</div><div class='input'><span class='va'>d_saemix_parent</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixData object was successfully created:
+#&gt;
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>saemix_options</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>seed <span class='op'>=</span> <span class='fl'>123456</span>, displayProgress <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>, 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'>200</span>, <span class='fl'>80</span><span class='op'>)</span><span class='op'>)</span>
+<span class='va'>f_saemix_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_p0_fixed</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:29 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:30 2020"</div><div class='img'><img src='saemix-1.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; odeini_fixed/(xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id,
+#&gt; 1])
+#&gt; }
+#&gt; &lt;bytecode: 0x5555599945b8&gt;
+#&gt; &lt;environment: 0x555559984388&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] log_alpha normal Estimated
+#&gt; [2,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; log_alpha log_beta
+#&gt; log_alpha 1 0
+#&gt; log_beta 0 1
+#&gt; Error model: constant , initial values: a.1=2.95893806804889
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; log_alpha log_beta
+#&gt; Pop.CondInit -0.347996 1.66788
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; log_alpha -0.33 0.30 91.6
+#&gt; log_beta 1.70 0.21 12.4
+#&gt; a a.1 3.15 0.25 7.9
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; log_alpha omega2.log_alpha 0.44 0.28 65
+#&gt; log_beta omega2.log_beta 0.18 0.14 79
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.log_alpha omega2.log_beta
+#&gt; omega2.log_alpha 1 0
+#&gt; omega2.log_beta 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 501.6082
+#&gt; AIC = 511.6082
+#&gt; BIC = 509.6554
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 501.7
+#&gt; AIC = 511.7
+#&gt; BIC = 509.7472
+#&gt; ----------------------------------------------------</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'>m_saemix_sfo</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</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;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1] * exp(-exp(psi[id, 2]) * xidep[, "time"])
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555e35c170&gt;
+#&gt; &lt;bytecode: 0x55555998d588&gt;
+#&gt; &lt;environment: 0x55555c0f4ae8&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: parent_0 log_k_parent
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_parent normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_k_parent
+#&gt; parent_0 1 0
+#&gt; log_k_parent 0 1
+#&gt; Error model: constant , initial values: a.1=5.76827561471585
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_k_parent
+#&gt; Pop.CondInit 86.39406 -3.215063</div><div class='input'><span class='va'>m_saemix_fomc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</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;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x5555595d7668&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.91976382242696
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 94.43884 -0.2226095 2.048192</div><div class='input'><span class='va'>m_saemix_dfop</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</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;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; g &lt;- plogis(psi[id, 4])
+#&gt; t = xidep[, "time"]
+#&gt; psi[id, 1] * (g * exp(-exp(psi[id, 2]) * t) + (1 - g) * exp(-exp(psi[id,
+#&gt; 3]) * t))
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998e548&gt;
+#&gt; &lt;environment: 0x555558225bf0&gt;
#&gt; Nb of parameters: 4
-#&gt; parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1
+#&gt; parameter names: parent_0 log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
-#&gt; [3,] log_k_A1 normal Estimated
-#&gt; [4,] f_parent_ilr_1 normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k1 normal Estimated
+#&gt; [3,] log_k2 normal Estimated
+#&gt; [4,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; parent_0 1 0 0 0
-#&gt; log_k_parent 0 1 0 0
-#&gt; log_k_A1 0 0 1 0
-#&gt; f_parent_ilr_1 0 0 0 1
-#&gt; Error model: constant , initial values: a.1=4.97259024646577
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0
+#&gt; log_k1 0 1 0 0
+#&gt; log_k2 0 0 1 0
+#&gt; g_qlogis 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.94671278396371
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; Pop.CondInit 86.53449 -3.207005 -3.060308 -1.920449</div><div class='input'><span class='va'>d_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 94.08322 -1.834163 -4.210797 0.11002</div><div class='input'><span class='va'>d_saemix_parent</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</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;
#&gt;
#&gt; The following SaemixData object was successfully created:
@@ -269,15 +445,12 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; longitudinal data for use with the SAEM algorithm
#&gt; Dataset ds_saemix
#&gt; Structured data: value ~ time + name | ds
-#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>saemix_options</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>seed <span class='op'>=</span> <span class='fl'>123456</span>,
- save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span> <span class='cn'>FALSE</span>, displayProgress <span class='op'>=</span> <span class='cn'>FALSE</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'>200</span>, <span class='fl'>80</span><span class='op'>)</span><span class='op'>)</span>
-<span class='va'>f_saemix</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix</span>, <span class='va'>d_saemix</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_sfo</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Thu Nov 5 08:26:39 2020"
+#&gt; [1] "Thu Nov 5 23:53:31 2020"
#&gt; ..
#&gt; Minimisation finished
-#&gt; [1] "Thu Nov 5 08:28:33 2020"</div><div class='img'><img src='saemix-1.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:32 2020"</div><div class='img'><img src='saemix-2.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
#&gt; -----------------------------------
#&gt; ---- Data ----
#&gt; -----------------------------------
@@ -288,8 +461,8 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; X variable for graphs: time ()
#&gt; Dataset characteristics:
#&gt; number of subjects: 5
-#&gt; number of observations: 170
-#&gt; average/min/max nb obs: 34.00 / 30 / 38
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
#&gt; First 10 lines of data:
#&gt; ds time name value mdv cens occ ytype
#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
@@ -309,59 +482,248 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; Model function: Mixed model generated from mmkin object Model type: structural
#&gt; function (psi, id, xidep)
#&gt; {
-#&gt; uid &lt;- unique(id)
-#&gt; res_list &lt;- parallel::mclapply(uid, function(i) {
-#&gt; transparms_optim &lt;- psi[i, ]
-#&gt; names(transparms_optim) &lt;- names(degparms_optim)
-#&gt; odeini_optim &lt;- transparms_optim[odeini_optim_parm_names]
-#&gt; names(odeini_optim) &lt;- gsub("_0$", "", odeini_optim_parm_names)
-#&gt; odeini &lt;- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
-#&gt; ode_transparms_optim_names &lt;- setdiff(names(transparms_optim),
-#&gt; odeini_optim_parm_names)
-#&gt; odeparms_optim &lt;- backtransform_odeparms(transparms_optim[ode_transparms_optim_names],
-#&gt; mkin_model, transform_rates = object[[1]]$transform_rates,
-#&gt; transform_fractions = object[[1]]$transform_fractions)
-#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
-#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
-#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
-#&gt; odeparms)
-#&gt; }
-#&gt; else {
-#&gt; i_time &lt;- xidep_i$time
-#&gt; i_name &lt;- xidep_i$name
-#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
-#&gt; outtimes = sort(unique(i_time)))
-#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
-#&gt; out_values &lt;- out_wide[out_index]
-#&gt; }
-#&gt; return(out_values)
-#&gt; }, mc.cores = cores)
-#&gt; res &lt;- unlist(res_list)
-#&gt; return(res)
+#&gt; psi[id, 1] * exp(-exp(psi[id, 2]) * xidep[, "time"])
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555e35c170&gt;
+#&gt; &lt;bytecode: 0x55555998d588&gt;
+#&gt; &lt;environment: 0x55555c0f4ae8&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: parent_0 log_k_parent
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_parent normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_k_parent
+#&gt; parent_0 1 0
+#&gt; log_k_parent 0 1
+#&gt; Error model: constant , initial values: a.1=5.76827561471585
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_k_parent
+#&gt; Pop.CondInit 86.39406 -3.215063
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 85.8 1.85 2.2
+#&gt; log_k_parent -3.2 0.59 18.3
+#&gt; a a.1 6.2 0.49 7.9
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 7.8 10.7 138
+#&gt; log_k_parent omega2.log_k_parent 1.7 1.1 64
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_k_parent
+#&gt; omega2.parent_0 1 0
+#&gt; omega2.log_k_parent 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 615.4074
+#&gt; AIC = 625.4074
+#&gt; BIC = 623.4546
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 614.4911
+#&gt; AIC = 624.4911
+#&gt; BIC = 622.5382
+#&gt; ----------------------------------------------------</div><div class='input'><span class='va'>f_saemix_fomc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_fomc</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:33 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:34 2020"</div><div class='img'><img src='saemix-3.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x5555595d7668&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.91976382242696
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 94.43884 -0.2226095 2.048192
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 94.49 1.18 1.2
+#&gt; log_alpha -0.21 0.30 142.0
+#&gt; log_beta 2.06 0.21 10.4
+#&gt; a a.1 2.28 0.19 8.2
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 4.66 4.34 93
+#&gt; log_alpha omega2.log_alpha 0.45 0.29 65
+#&gt; log_beta omega2.log_beta 0.19 0.14 75
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_alpha omega2.log_beta
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_alpha 0 1 0
+#&gt; omega2.log_beta 0 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 454.0598
+#&gt; AIC = 468.0598
+#&gt; BIC = 465.3259
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 453.7499
+#&gt; AIC = 467.7499
+#&gt; BIC = 465.016
+#&gt; ----------------------------------------------------</div><div class='input'><span class='va'>f_saemix_dfop</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_dfop</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:35 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:37 2020"</div><div class='img'><img src='saemix-4.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; g &lt;- plogis(psi[id, 4])
+#&gt; t = xidep[, "time"]
+#&gt; psi[id, 1] * (g * exp(-exp(psi[id, 2]) * t) + (1 - g) * exp(-exp(psi[id,
+#&gt; 3]) * t))
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998e548&gt;
+#&gt; &lt;environment: 0x555558225bf0&gt;
#&gt; Nb of parameters: 4
-#&gt; parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1
+#&gt; parameter names: parent_0 log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
-#&gt; [3,] log_k_A1 normal Estimated
-#&gt; [4,] f_parent_ilr_1 normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k1 normal Estimated
+#&gt; [3,] log_k2 normal Estimated
+#&gt; [4,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; parent_0 1 0 0 0
-#&gt; log_k_parent 0 1 0 0
-#&gt; log_k_A1 0 0 1 0
-#&gt; f_parent_ilr_1 0 0 0 1
-#&gt; Error model: constant , initial values: a.1=4.97259024646577
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0
+#&gt; log_k1 0 1 0 0
+#&gt; log_k2 0 0 1 0
+#&gt; g_qlogis 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.94671278396371
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; Pop.CondInit 86.53449 -3.207005 -3.060308 -1.920449
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 94.08322 -1.834163 -4.210797 0.11002
#&gt; -----------------------------------
#&gt; ---- Key algorithm options ----
#&gt; -----------------------------------
@@ -383,69 +745,195 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; ----------------------------------------------------
#&gt; ----------------- Fixed effects ------------------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 86.09 1.57 1.8
-#&gt; log_k_parent -3.21 0.59 18.5
-#&gt; log_k_A1 -4.69 0.31 6.6
-#&gt; f_parent_ilr_1 -0.34 0.30 89.2
-#&gt; a a.1 4.69 0.27 5.8
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 93.97 1.35 1.4
+#&gt; log_k1 -2.37 0.58 24.5
+#&gt; log_k2 -3.63 0.87 24.0
+#&gt; g_qlogis -0.14 0.34 246.1
+#&gt; a a.1 2.32 0.19 8.3
#&gt; ----------------------------------------------------
#&gt; ----------- Variance of random effects -----------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 omega2.parent_0 7.07 7.72 109
-#&gt; log_k_parent omega2.log_k_parent 1.75 1.11 63
-#&gt; log_k_A1 omega2.log_k_A1 0.28 0.28 99
-#&gt; f_parent_ilr_1 omega2.f_parent_ilr_1 0.39 0.27 71
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 6.97 5.72 82
+#&gt; log_k1 omega2.log_k1 1.63 1.06 65
+#&gt; log_k2 omega2.log_k2 3.73 2.39 64
+#&gt; g_qlogis omega2.g_qlogis 0.16 0.27 173
#&gt; ----------------------------------------------------
#&gt; ------ Correlation matrix of random effects ------
#&gt; ----------------------------------------------------
-#&gt; omega2.parent_0 omega2.log_k_parent omega2.log_k_A1
-#&gt; omega2.parent_0 1 0 0
-#&gt; omega2.log_k_parent 0 1 0
-#&gt; omega2.log_k_A1 0 0 1
-#&gt; omega2.f_parent_ilr_1 0 0 0
-#&gt; omega2.f_parent_ilr_1
-#&gt; omega2.parent_0 0
-#&gt; omega2.log_k_parent 0
-#&gt; omega2.log_k_A1 0
-#&gt; omega2.f_parent_ilr_1 1
+#&gt; omega2.parent_0 omega2.log_k1 omega2.log_k2 omega2.g_qlogis
+#&gt; omega2.parent_0 1 0 0 0
+#&gt; omega2.log_k1 0 1 0 0
+#&gt; omega2.log_k2 0 0 1 0
+#&gt; omega2.g_qlogis 0 0 0 1
#&gt; ----------------------------------------------------
#&gt; --------------- Statistical criteria -------------
#&gt; ----------------------------------------------------
#&gt; Likelihood computed by linearisation
-#&gt; -2LL= 1064.35
-#&gt; AIC = 1082.35
-#&gt; BIC = 1078.835
+#&gt; -2LL= 485.4627
+#&gt; AIC = 503.4627
+#&gt; BIC = 499.9477
#&gt;
#&gt; Likelihood computed by importance sampling
-#&gt; -2LL= 1063.475
-#&gt; AIC = 1081.475
-#&gt; BIC = 1077.96
-#&gt; ----------------------------------------------------</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_saemix</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='img'><img src='saemix-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span>
-<span class='co'># Synthetic data with two-component error</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'>dt50_sfo_in</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>80</span>, <span class='fl'>90</span>, <span class='fl'>100</span>, <span class='fl'>111.111</span>, <span class='fl'>125</span><span class='op'>)</span>
-<span class='va'>k_in</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>2</span><span class='op'>)</span> <span class='op'>/</span> <span class='va'>dt50_sfo_in</span>
-
-<span class='va'>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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span>
-
-<span class='va'>pred_sfo</span> <span class='op'>&lt;-</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>k</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'>SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='va'>k</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><span class='op'>)</span>, <span class='va'>sampling_times</span><span class='op'>)</span>
-<span class='op'>}</span>
-
-<span class='va'>ds_sfo_mean</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>k_in</span>, <span class='va'>pred_sfo</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'>123456L</span><span class='op'>)</span>
-<span class='va'>ds_sfo_syn</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>ds_sfo_mean</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='va'>f_mmkin_syn</span> <span class='op'>&lt;-</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>, 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>
-<span class='co'># plot(f_mmkin_syn)</span>
-<span class='va'>m_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_syn</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
+#&gt; -2LL= 473.563
+#&gt; AIC = 491.563
+#&gt; BIC = 488.048
+#&gt; ----------------------------------------------------</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_saemix_sfo</span>, <span class='va'>f_saemix_fomc</span>, <span class='va'>f_saemix_dfop</span><span class='op'>)</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 624.4911 622.5382
+#&gt; 2 467.7499 465.0160
+#&gt; 3 491.5630 488.0480</div><div class='input'><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'>m_saemix_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</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;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x555559a957f8&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: combined , initial values: a.1=1.10728182011691 b.1=0.024889924291374
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 93.13042 -0.1215336 2.230815</div><div class='input'><span class='va'>f_saemix_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_fomc_tc</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:38 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:42 2020"</div><div class='img'><img src='saemix-5.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x555559a957f8&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: combined , initial values: a.1=1.10728182011691 b.1=0.024889924291374
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 93.13042 -0.1215336 2.230815
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 94.4481 1.2052 1.3
+#&gt; log_alpha -0.2088 0.3059 146.5
+#&gt; log_beta 2.0668 0.2182 10.6
+#&gt; a a.1 2.4273 0.3178 13.1
+#&gt; b b.1 -0.0037 0.0062 168.3
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 5.34 4.58 86
+#&gt; log_alpha omega2.log_alpha 0.46 0.29 65
+#&gt; log_beta omega2.log_beta 0.20 0.15 74
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_alpha omega2.log_beta
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_alpha 0 1 0
+#&gt; omega2.log_beta 0 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 453.7703
+#&gt; AIC = 469.7703
+#&gt; BIC = 466.6458
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 453.6186
+#&gt; AIC = 469.6186
+#&gt; BIC = 466.4942
+#&gt; ----------------------------------------------------</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_saemix_fomc</span>, <span class='va'>f_saemix_fomc_tc</span><span class='op'>)</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 467.7499 465.0160
+#&gt; 2 469.6186 466.4942</div><div class='input'>
+<span class='va'>dfop_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='mkinsub.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='mkinsub.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'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='va'>f_mmkin</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/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><span class='op'>)</span>
+<span class='va'>m_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixModel object was successfully created:
@@ -468,7 +956,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; transform_fractions = object[[1]]$transform_fractions)
#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
+#&gt; if (solution_type == "analytical") {
#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
#&gt; odeparms)
#&gt; }
@@ -476,7 +964,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; i_time &lt;- xidep_i$time
#&gt; i_name &lt;- xidep_i$name
#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
+#&gt; odeini = odeini, solution_type = solution_type,
#&gt; outtimes = sort(unique(i_time)))
#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
#&gt; out_values &lt;- out_wide[out_index]
@@ -486,23 +974,31 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; res &lt;- unlist(res_list)
#&gt; return(res)
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555cd8e028&gt;
-#&gt; Nb of parameters: 2
-#&gt; parameter names: parent_0 log_k_parent
+#&gt; &lt;bytecode: 0x55555998cba0&gt;
+#&gt; &lt;environment: 0x55555bd1fee8&gt;
+#&gt; Nb of parameters: 6
+#&gt; parameter names: parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_A1 normal Estimated
+#&gt; [3,] f_parent_qlogis normal Estimated
+#&gt; [4,] log_k1 normal Estimated
+#&gt; [5,] log_k2 normal Estimated
+#&gt; [6,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent
-#&gt; parent_0 1 0
-#&gt; log_k_parent 0 1
-#&gt; Error model: combined , initial values: a.1=1.05209877924905 b.1=0.0586479225303944
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0 0 0
+#&gt; log_k_A1 0 1 0 0 0 0
+#&gt; f_parent_qlogis 0 0 1 0 0 0
+#&gt; log_k1 0 0 0 1 0 0
+#&gt; log_k2 0 0 0 0 1 0
+#&gt; g_qlogis 0 0 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.64723790168612
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent
-#&gt; Pop.CondInit 100.315 -4.962075</div><div class='input'><span class='va'>d_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin_syn</span><span class='op'>)</span>
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 93.81015 -9.764746 -0.9711148 -1.879937 -4.270814 0.1356441</div><div class='input'><span class='va'>d_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixData object was successfully created:
@@ -511,12 +1007,12 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; longitudinal data for use with the SAEM algorithm
#&gt; Dataset ds_saemix
#&gt; Structured data: value ~ time + name | ds
-#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_tc</span>, <span class='va'>d_saemix_tc</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix</span>, <span class='va'>d_saemix</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Thu Nov 5 08:28:50 2020"
+#&gt; [1] "Thu Nov 5 23:53:43 2020"
#&gt; ..
#&gt; Minimisation finished
-#&gt; [1] "Thu Nov 5 08:29:41 2020"</div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:56:33 2020"</div><div class='img'><img src='saemix-6.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
#&gt; -----------------------------------
#&gt; ---- Data ----
#&gt; -----------------------------------
@@ -527,20 +1023,20 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; X variable for graphs: time ()
#&gt; Dataset characteristics:
#&gt; number of subjects: 5
-#&gt; number of observations: 90
-#&gt; average/min/max nb obs: 18.00 / 18 / 18
+#&gt; number of observations: 170
+#&gt; average/min/max nb obs: 34.00 / 30 / 38
#&gt; First 10 lines of data:
-#&gt; ds time name value mdv cens occ ytype
-#&gt; 1 1 0 parent 105.9 0 0 1 1
-#&gt; 2 1 0 parent 98.0 0 0 1 1
-#&gt; 3 1 1 parent 96.6 0 0 1 1
-#&gt; 4 1 1 parent 99.8 0 0 1 1
-#&gt; 5 1 3 parent 113.0 0 0 1 1
-#&gt; 6 1 3 parent 103.2 0 0 1 1
-#&gt; 7 1 7 parent 102.9 0 0 1 1
-#&gt; 8 1 7 parent 110.8 0 0 1 1
-#&gt; 9 1 14 parent 95.9 0 0 1 1
-#&gt; 10 1 14 parent 85.9 0 0 1 1
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
#&gt; -----------------------------------
#&gt; ---- Model ----
#&gt; -----------------------------------
@@ -562,7 +1058,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; transform_fractions = object[[1]]$transform_fractions)
#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
+#&gt; if (solution_type == "analytical") {
#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
#&gt; odeparms)
#&gt; }
@@ -570,7 +1066,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; i_time &lt;- xidep_i$time
#&gt; i_name &lt;- xidep_i$name
#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
+#&gt; odeini = odeini, solution_type = solution_type,
#&gt; outtimes = sort(unique(i_time)))
#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
#&gt; out_values &lt;- out_wide[out_index]
@@ -580,23 +1076,31 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; res &lt;- unlist(res_list)
#&gt; return(res)
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555cd8e028&gt;
-#&gt; Nb of parameters: 2
-#&gt; parameter names: parent_0 log_k_parent
+#&gt; &lt;bytecode: 0x55555998cba0&gt;
+#&gt; &lt;environment: 0x55555bd1fee8&gt;
+#&gt; Nb of parameters: 6
+#&gt; parameter names: parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_A1 normal Estimated
+#&gt; [3,] f_parent_qlogis normal Estimated
+#&gt; [4,] log_k1 normal Estimated
+#&gt; [5,] log_k2 normal Estimated
+#&gt; [6,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent
-#&gt; parent_0 1 0
-#&gt; log_k_parent 0 1
-#&gt; Error model: combined , initial values: a.1=1.05209877924905 b.1=0.0586479225303944
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0 0 0
+#&gt; log_k_A1 0 1 0 0 0 0
+#&gt; f_parent_qlogis 0 0 1 0 0 0
+#&gt; log_k1 0 0 0 1 0 0
+#&gt; log_k2 0 0 0 0 1 0
+#&gt; g_qlogis 0 0 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.64723790168612
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent
-#&gt; Pop.CondInit 100.315 -4.962075
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 93.81015 -9.764746 -0.9711148 -1.879937 -4.270814 0.1356441
#&gt; -----------------------------------
#&gt; ---- Key algorithm options ----
#&gt; -----------------------------------
@@ -618,37 +1122,55 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; ----------------------------------------------------
#&gt; ----------------- Fixed effects ------------------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 100.232 1.266 1.3
-#&gt; log_k_parent -4.961 0.089 1.8
-#&gt; a a.1 -0.106 1.211 1142.0
-#&gt; b b.1 0.071 0.017 24.2
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 93.78 1.35 1.4
+#&gt; log_k_A1 -6.05 1.12 18.5
+#&gt; f_parent_qlogis -0.97 0.20 21.1
+#&gt; log_k1 -2.46 0.51 20.7
+#&gt; log_k2 -3.63 0.95 26.3
+#&gt; g_qlogis -0.08 0.36 447.7
+#&gt; a a.1 1.88 0.11 5.9
#&gt; ----------------------------------------------------
#&gt; ----------- Variance of random effects -----------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 omega2.parent_0 3.334 5.024 151
-#&gt; log_k_parent omega2.log_k_parent 0.036 0.024 68
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 7.85 5.76 73
+#&gt; log_k_A1 omega2.log_k_A1 4.27 3.44 80
+#&gt; f_parent_qlogis omega2.f_parent_qlogis 0.20 0.13 65
+#&gt; log_k1 omega2.log_k1 1.08 0.77 72
+#&gt; log_k2 omega2.log_k2 4.24 2.83 67
+#&gt; g_qlogis omega2.g_qlogis 0.21 0.26 123
#&gt; ----------------------------------------------------
#&gt; ------ Correlation matrix of random effects ------
#&gt; ----------------------------------------------------
-#&gt; omega2.parent_0 omega2.log_k_parent
-#&gt; omega2.parent_0 1 0
-#&gt; omega2.log_k_parent 0 1
+#&gt; omega2.parent_0 omega2.log_k_A1 omega2.f_parent_qlogis
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_k_A1 0 1 0
+#&gt; omega2.f_parent_qlogis 0 0 1
+#&gt; omega2.log_k1 0 0 0
+#&gt; omega2.log_k2 0 0 0
+#&gt; omega2.g_qlogis 0 0 0
+#&gt; omega2.log_k1 omega2.log_k2 omega2.g_qlogis
+#&gt; omega2.parent_0 0 0 0
+#&gt; omega2.log_k_A1 0 0 0
+#&gt; omega2.f_parent_qlogis 0 0 0
+#&gt; omega2.log_k1 1 0 0
+#&gt; omega2.log_k2 0 1 0
+#&gt; omega2.g_qlogis 0 0 1
#&gt; ----------------------------------------------------
#&gt; --------------- Statistical criteria -------------
#&gt; ----------------------------------------------------
#&gt; Likelihood computed by linearisation
-#&gt; -2LL= 575.5586
-#&gt; AIC = 587.5586
-#&gt; BIC = 585.2153
+#&gt; -2LL= 879.7721
+#&gt; AIC = 905.7721
+#&gt; BIC = 900.6948
#&gt;
#&gt; Likelihood computed by importance sampling
-#&gt; -2LL= 575.7797
-#&gt; AIC = 587.7797
-#&gt; BIC = 585.4364
-#&gt; ----------------------------------------------------</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_saemix_tc</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
-</div><div class='img'><img src='saemix-3.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Plotting convergence plots</div><div class='img'><img src='saemix-4.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span>
+#&gt; -2LL= 816.8276
+#&gt; AIC = 842.8276
+#&gt; BIC = 837.7503
+#&gt; ----------------------------------------------------</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/transform_odeparms.html b/docs/dev/reference/transform_odeparms.html
index 58a1e9a1..6b849d3f 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">0.9.50.3</span>
+ <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.4</span>
</span>
</div>
@@ -125,7 +125,7 @@ the ilr transformation is used." />
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
- <a href="http://github.com/jranke/mkin/">
+ <a href="https://github.com/jranke/mkin/">
<span class="fab fa fab fa-github fa-lg"></span>
</a>
@@ -144,7 +144,7 @@ the ilr transformation is used." />
<div class="col-md-9 contents">
<div class="page-header">
<h1>Functions to transform and backtransform kinetic parameters for fitting</h1>
- <small class="dont-index">Source: <a href='http://github.com/jranke/mkin/blob/master/R/transform_odeparms.R'><code>R/transform_odeparms.R</code></a></small>
+ <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/transform_odeparms.R'><code>R/transform_odeparms.R</code></a></small>
<div class="hidden name"><code>transform_odeparms.Rd</code></div>
</div>
@@ -154,22 +154,22 @@ restricted values to the full scale of real numbers. For kinetic rate
constants and other parameters that can only take on positive values, a
simple log transformation is used. For compositional parameters, such as the
formations fractions that should always sum up to 1 and can not be negative,
-the <code><a href='ilr.html'>ilr</a></code> transformation is used.</p>
+the <a href='ilr.html'>ilr</a> transformation is used.</p>
</div>
- <pre class="usage"><span class='fu'>transform_odeparms</span>(
- <span class='no'>parms</span>,
- <span class='no'>mkinmod</span>,
- <span class='kw'>transform_rates</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
- <span class='kw'>transform_fractions</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
-)
+ <pre class="usage"><span class='fu'>transform_odeparms</span><span class='op'>(</span>
+ <span class='va'>parms</span>,
+ <span class='va'>mkinmod</span>,
+ transform_rates <span class='op'>=</span> <span class='cn'>TRUE</span>,
+ transform_fractions <span class='op'>=</span> <span class='cn'>TRUE</span>
+<span class='op'>)</span>
-<span class='fu'>backtransform_odeparms</span>(
- <span class='no'>transparms</span>,
- <span class='no'>mkinmod</span>,
- <span class='kw'>transform_rates</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
- <span class='kw'>transform_fractions</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
-)</pre>
+<span class='fu'>backtransform_odeparms</span><span class='op'>(</span>
+ <span class='va'>transparms</span>,
+ <span class='va'>mkinmod</span>,
+ transform_rates <span class='op'>=</span> <span class='cn'>TRUE</span>,
+ transform_fractions <span class='op'>=</span> <span class='cn'>TRUE</span>
+<span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@@ -181,9 +181,9 @@ equations.</p></td>
</tr>
<tr>
<th>mkinmod</th>
- <td><p>The kinetic model of class <code><a href='mkinmod.html'>mkinmod</a></code>, containing
+ <td><p>The kinetic model of class <a href='mkinmod.html'>mkinmod</a>, containing
the names of the model variables that are needed for grouping the
-formation fractions before <code><a href='ilr.html'>ilr</a></code> transformation, the parameter
+formation fractions before <a href='ilr.html'>ilr</a> transformation, the parameter
names and the information if the pathway to sink is included in the model.</p></td>
</tr>
<tr>
@@ -200,10 +200,13 @@ models and the break point tb of the HS model.</p></td>
<td><p>Boolean specifying if formation fractions
constants should be transformed in the model specification used in the
fitting for better compliance with the assumption of normal distribution
-of the estimator. The default (TRUE) is to do transformations. The g
-parameter of the DFOP and HS models are also transformed, as they can also
-be seen as compositional data. The transformation used for these
-transformations is the <code><a href='ilr.html'>ilr</a></code> transformation.</p></td>
+of the estimator. The default (TRUE) is to do transformations.
+The g parameter of the DFOP model is also seen as a fraction.
+If a single fraction is transformed (g parameter of DFOP or only a single
+target variable e.g. a single metabolite plus a pathway to sink), a
+logistic transformation is used <code><a href='https://rdrr.io/r/stats/Logistic.html'>stats::qlogis()</a></code>. In other cases, i.e. if
+two or more formation fractions need to be transformed whose sum cannot
+exceed one, the <a href='ilr.html'>ilr</a> transformation is used.</p></td>
</tr>
<tr>
<th>transparms</th>
@@ -219,74 +222,96 @@ fitting procedure.</p></td>
<p>The transformation of sets of formation fractions is fragile, as it supposes
the same ordering of the components in forward and backward transformation.
-This is no problem for the internal use in <code><a href='mkinfit.html'>mkinfit</a></code>.</p>
+This is no problem for the internal use in <a href='mkinfit.html'>mkinfit</a>.</p>
+ <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
+
+ <p>Johannes Ranke</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'>
-<span class='no'>SFO_SFO</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(
- <span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></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'>sink</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
- <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>))</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='co'># Fit the model to the FOCUS example dataset D using defaults</span>
-<span class='no'>fit</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Shapiro-Wilk test for standardized residuals: p = 0.0165</span></div><div class='input'><span class='no'>fit.s</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit</span>)
+<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='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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</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'>&lt;-</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'>#&gt; <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'>&lt;-</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='no'>fit.s</span>$<span class='no'>par</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate Std. Error Lower Upper
-#&gt; parent_0 99.598 1.5702 96.4038 102.793
-#&gt; log_k_parent -2.316 0.0409 -2.3988 -2.233
-#&gt; log_k_m1 -5.248 0.1332 -5.5184 -4.977
-#&gt; f_parent_ilr_1 0.041 0.0631 -0.0875 0.169
-#&gt; sigma 3.126 0.3585 2.3961 3.855</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.s</span>$<span class='no'>bpar</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
-#&gt; parent_0 99.59848 1.57022 63.43 2.30e-36 96.40384 102.7931
+<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Estimate Std. Error Lower Upper
+#&gt; parent_0 99.5985 1.5702 96.404 102.79
+#&gt; log_k_parent -2.3157 0.0409 -2.399 -2.23
+#&gt; log_k_m1 -5.2475 0.1332 -5.518 -4.98
+#&gt; f_parent_qlogis 0.0579 0.0893 -0.124 0.24
+#&gt; 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'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
+#&gt; parent_0 99.59848 1.57022 63.43 2.30e-36 96.40383 102.7931
#&gt; k_parent 0.09870 0.00403 24.47 4.96e-23 0.09082 0.1073
#&gt; k_m1 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069
#&gt; f_parent_to_m1 0.51448 0.02230 23.07 3.10e-22 0.46912 0.5596
#&gt; 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='no'>fit.2</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>transform_rates</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#&gt; <span class='error'>Error in if (cost &lt; 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'>#&gt; <span class='message'>Timing stopped at: 0.002 0 0.003</span></div><div class='input'><span class='no'>fit.2.s</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit.2</span>)</div><div class='output co'>#&gt; <span class='error'>Error in summary(fit.2): 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='no'>fit.2.s</span>$<span class='no'>par</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; <span class='error'>Error in print(fit.2.s$par, 3): object 'fit.2.s' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.2.s</span>$<span class='no'>bpar</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; <span class='error'>Error in print(fit.2.s$bpar, 3): object 'fit.2.s' not found</span></div><div class='input'><span class='co'># }</span>
-
-<span class='no'>initials</span> <span class='kw'>&lt;-</span> <span class='no'>fit</span>$<span class='no'>start</span>$<span class='no'>value</span>
-<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span>(<span class='no'>initials</span>) <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span>(<span class='no'>fit</span>$<span class='no'>start</span>)
-<span class='no'>transformed</span> <span class='kw'>&lt;-</span> <span class='no'>fit</span>$<span class='no'>start_transformed</span>$<span class='no'>value</span>
-<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span>(<span class='no'>transformed</span>) <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span>(<span class='no'>fit</span>$<span class='no'>start_transformed</span>)
-<span class='fu'>transform_odeparms</span>(<span class='no'>initials</span>, <span class='no'>SFO_SFO</span>)</div><div class='output co'>#&gt; parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#&gt; 100.750000 -2.302585 -2.301586 0.000000 </div><div class='input'><span class='fu'>backtransform_odeparms</span>(<span class='no'>transformed</span>, <span class='no'>SFO_SFO</span>)</div><div class='output co'>#&gt; parent_0 k_parent k_m1 f_parent_to_m1
+<span class='va'>fit.2</span> <span class='op'>&lt;-</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'>#&gt; <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#&gt; <span class='error'>Error in if (cost &lt; 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'>#&gt; <span class='message'>Timing stopped at: 0.003 0 0.002</span></div><div class='input'><span class='va'>fit.2.s</span> <span class='op'>&lt;-</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'>#&gt; <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'>#&gt; <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'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; <span class='error'>Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found</span></div><div class='input'><span class='co'># }</span>
+
+<span class='va'>initials</span> <span class='op'>&lt;-</span> <span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>$</span><span class='va'>value</span>
+<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>initials</span><span class='op'>)</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>)</span>
+<span class='va'>transformed</span> <span class='op'>&lt;-</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'>&lt;-</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'>#&gt; parent_0 log_k_parent log_k_m1 f_parent_qlogis
+#&gt; 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'>#&gt; parent_0 k_parent k_m1 f_parent_to_m1
#&gt; 100.7500 0.1000 0.1001 0.5000 </div><div class='input'>
<span class='co'># \dontrun{</span>
<span class='co'># The case of formation fractions</span>
-<span class='no'>SFO_SFO.ff</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(
- <span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></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'>sink</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
- <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
-<span class='no'>fit.ff</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO.ff</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Shapiro-Wilk test for standardized residuals: p = 0.0165</span></div><div class='input'><span class='no'>fit.ff.s</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit.ff</span>)
-<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.ff.s</span>$<span class='no'>par</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate Std. Error Lower Upper
-#&gt; parent_0 99.598 1.5702 96.4038 102.793
-#&gt; log_k_parent -2.316 0.0409 -2.3988 -2.233
-#&gt; log_k_m1 -5.248 0.1332 -5.5184 -4.977
-#&gt; f_parent_ilr_1 0.041 0.0631 -0.0875 0.169
-#&gt; sigma 3.126 0.3585 2.3961 3.855</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.ff.s</span>$<span class='no'>bpar</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
-#&gt; parent_0 99.59848 1.57022 63.43 2.30e-36 96.40384 102.7931
+<span class='va'>SFO_SFO.ff</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='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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
+<span class='va'>fit.ff</span> <span class='op'>&lt;-</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'>#&gt; <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'>&lt;-</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'>#&gt; Estimate Std. Error Lower Upper
+#&gt; parent_0 99.5985 1.5702 96.404 102.79
+#&gt; log_k_parent -2.3157 0.0409 -2.399 -2.23
+#&gt; log_k_m1 -5.2475 0.1332 -5.518 -4.98
+#&gt; f_parent_qlogis 0.0579 0.0893 -0.124 0.24
+#&gt; 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.ff.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'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
+#&gt; parent_0 99.59848 1.57022 63.43 2.30e-36 96.40383 102.7931
#&gt; k_parent 0.09870 0.00403 24.47 4.96e-23 0.09082 0.1073
#&gt; k_m1 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069
#&gt; f_parent_to_m1 0.51448 0.02230 23.07 3.10e-22 0.46912 0.5596
-#&gt; sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'><span class='no'>initials</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"f_parent_to_m1"</span> <span class='kw'>=</span> <span class='fl'>0.5</span>)
-<span class='no'>transformed</span> <span class='kw'>&lt;-</span> <span class='fu'>transform_odeparms</span>(<span class='no'>initials</span>, <span class='no'>SFO_SFO.ff</span>)
-<span class='fu'>backtransform_odeparms</span>(<span class='no'>transformed</span>, <span class='no'>SFO_SFO.ff</span>)</div><div class='output co'>#&gt; f_parent_to_m1
+#&gt; sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'><span class='va'>initials</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"f_parent_to_m1"</span> <span class='op'>=</span> <span class='fl'>0.5</span><span class='op'>)</span>
+<span class='va'>transformed</span> <span class='op'>&lt;-</span> <span class='fu'>transform_odeparms</span><span class='op'>(</span><span class='va'>initials</span>, <span class='va'>SFO_SFO.ff</span><span class='op'>)</span>
+<span class='fu'>backtransform_odeparms</span><span class='op'>(</span><span class='va'>transformed</span>, <span class='va'>SFO_SFO.ff</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; f_parent_to_m1
#&gt; 0.5 </div><div class='input'>
<span class='co'># And without sink</span>
-<span class='no'>SFO_SFO.ff.2</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(
- <span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></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'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>),
- <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
-
-<span class='no'>fit.ff.2</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO.ff.2</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Shapiro-Wilk test for standardized residuals: p = 0.0242</span></div><div class='input'><span class='no'>fit.ff.2.s</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit.ff.2</span>)
-<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.ff.2.s</span>$<span class='no'>par</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate Std. Error Lower Upper
+<span class='va'>SFO_SFO.ff.2</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='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'>FALSE</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'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
+
+<span class='va'>fit.ff.2</span> <span class='op'>&lt;-</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'>#&gt; <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'>&lt;-</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'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Estimate Std. Error Lower Upper
#&gt; parent_0 84.79 3.012 78.67 90.91
#&gt; log_k_parent -2.76 0.082 -2.92 -2.59
#&gt; log_k_m1 -4.21 0.123 -4.46 -3.96
-#&gt; sigma 8.22 0.943 6.31 10.14</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>fit.ff.2.s</span>$<span class='no'>bpar</span>, <span class='fl'>3</span>)</div><div class='output co'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
+#&gt; sigma 8.22 0.943 6.31 10.14</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.ff.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'>#&gt; Estimate se_notrans t value Pr(&gt;t) Lower Upper
#&gt; parent_0 84.7916 3.01203 28.15 1.92e-25 78.6704 90.913
#&gt; k_parent 0.0635 0.00521 12.19 2.91e-14 0.0538 0.075
#&gt; k_m1 0.0148 0.00182 8.13 8.81e-10 0.0115 0.019
-#&gt; sigma 8.2229 0.94323 8.72 1.73e-10 6.3060 10.140</div><div class='input'># }
+#&gt; sigma 8.2229 0.94323 8.72 1.73e-10 6.3060 10.140</div><div class='input'><span class='co'># }</span>
</div></pre>
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@@ -304,7 +329,7 @@ This is no problem for the internal use in <code><a href='mkinfit.html'>mkinfit<
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- <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.</p>
+ <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
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