diff options
24 files changed, 88 insertions, 157 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 54df9c7e..8a2a4529 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: mkin Type: Package Title: Kinetic Evaluation of Chemical Degradation Data -Version: 1.2.3.1 +Version: 1.2.4 Date: 2023-04-20 Authors@R: c( person("Johannes", "Ranke", role = c("aut", "cre", "cph"), @@ -1,4 +1,8 @@ -# mkin 1.2.3.1 +# mkin 1.2.4 + + + +# mkin 1.2.3.1 (unreleased) - Small fixes to get the online docs right (example code in R/hierarchical_kinetics, cluster setup in cyantraniliprole and dmta pathway vignettes, graphics and model comparison in multistart vignette), rebuild online docs diff --git a/R/multistart.R b/R/multistart.R index bdfbfe63..aeea2d81 100644 --- a/R/multistart.R +++ b/R/multistart.R @@ -45,13 +45,12 @@ #' #' f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") #' illparms(f_saem_reduced) -#' # On Windows, we need to create a cluster first. When working with -#' # such a cluster, we need to export the mmkin object to the cluster -#' # nodes, as it is referred to when updating the saem object on the nodes. +#' # On Windows, we need to create a PSOCK cluster first and refer to it +#' # in the call to multistart() #' library(parallel) #' cl <- makePSOCKcluster(12) #' f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl) -#' parplot(f_saem_reduced_multi, lpos = "topright") +#' parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2)) #' stopCluster(cl) #' } multistart <- function(object, n = 50, @@ -103,9 +102,7 @@ multistart.saem.mmkin <- function(object, n = 50, cores = 1, res <- parallel::mclapply(1:n, fit_function, mc.cores = cores, mc.preschedule = FALSE) } else { - res <- parallel::parLapplyLB(cluster, 1:n, fit_function, - mc.preschedule = FALSE - ) + res <- parallel::parLapplyLB(cluster, 1:n, fit_function) } attr(res, "orig") <- object attr(res, "start_parms") <- start_parms diff --git a/docs/dev/articles/index.html b/docs/dev/articles/index.html index a82eb999..2aacc53a 100644 --- a/docs/dev/articles/index.html +++ b/docs/dev/articles/index.html @@ -81,11 +81,6 @@ <li> <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> - <li class="divider"> - <li class="dropdown-header">Code coverage report</li> - <li> - <a href="../coverage/coverage.html"></a> - </li> </ul></li> <li> <a href="../news/index.html">News</a> diff --git a/docs/dev/articles/web_only/multistart.html b/docs/dev/articles/web_only/multistart.html index d3d9d76d..b5635df2 100644 --- a/docs/dev/articles/web_only/multistart.html +++ b/docs/dev/articles/web_only/multistart.html @@ -127,15 +127,13 @@ - </header><div class="row"> + </header><script src="multistart_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> <div class="col-md-9 contents"> <div class="page-header toc-ignore"> <h1 data-toc-skip>Short demo of the multistart method</h1> - <h4 data-toc-skip class="author">Johannes -Ranke</h4> + <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 data-toc-skip class="date">Last change 26 September 2022 -(rebuilt 2023-04-16)</h4> + <h4 data-toc-skip class="date">Last change 17 April 2023 (rebuilt 2023-04-17)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/multistart.rmd" class="external-link"><code>vignettes/web_only/multistart.rmd</code></a></small> <div class="hidden name"><code>multistart.rmd</code></div> @@ -144,8 +142,7 @@ Ranke</h4> -<p>The dimethenamid data from 2018 from seven soils is used as example -data in this vignette.</p> +<p>The dimethenamid data from 2018 from seven soils is used as example data in this vignette.</p> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/mkin/">mkin</a></span><span class="op">)</span></span> <span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> @@ -157,54 +154,41 @@ data in this vignette.</p> <span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span> <span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span> <span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></code></pre></div> -<p>First, we check the DFOP model with the two-component error model and -random effects for all degradation parameters.</p> +<p>First, we check the DFOP model with the two-component error model and random effects for all degradation parameters.</p> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">dmta_ds</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">7</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="va">f_saem_full</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">)</span></span> <span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_full</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## [1] "sd(log_k2)"</span></span></code></pre> -<p>We see that not all variability parameters are identifiable. The -<code>illparms</code> function tells us that the confidence interval for -the standard deviation of ‘log_k2’ includes zero. We check this -assessment using multiple runs with different starting values.</p> +<p>We see that not all variability parameters are identifiable. The <code>illparms</code> function tells us that the confidence interval for the standard deviation of ‘log_k2’ includes zero. We check this assessment using multiple runs with different starting values.</p> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span><span class="va">f_saem_full_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_full</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">16</span><span class="op">)</span></span> -<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_full_multi</span><span class="op">)</span></span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_saem_full_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_full</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_full_multi</span>, lpos <span class="op">=</span> <span class="st">"topleft"</span><span class="op">)</span></span></code></pre></div> <p><img src="multistart_files/figure-html/unnamed-chunk-3-1.png" width="700"></p> -<p>This confirms that the variance of k2 is the most problematic -parameter, so we reduce the parameter distribution model by removing the -intersoil variability for k2.</p> +<p>This confirms that the variance of k2 is the most problematic parameter, so we reduce the parameter distribution model by removing the intersoil variability for k2.</p> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">f_saem_reduced</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_full</span>, no_random_effect <span class="op">=</span> <span class="st">"log_k2"</span><span class="op">)</span></span> <span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_reduced</span><span class="op">)</span></span> -<span><span class="va">f_saem_reduced_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_reduced</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">16</span><span class="op">)</span></span> -<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span><span class="op">)</span></span></code></pre></div> +<span><span class="va">f_saem_reduced_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_reduced</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span>, ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>, <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> <p><img src="multistart_files/figure-html/unnamed-chunk-4-1.png" width="700"></p> -<p>The results confirm that all remaining parameters can be determined -with sufficient certainty.</p> -<p>We can also analyse the log-likelihoods obtained in the multiple -runs:</p> +<p>The results confirm that all remaining parameters can be determined with sufficient certainty.</p> +<p>We can also analyse the log-likelihoods obtained in the multiple runs:</p> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../../reference/llhist.html">llhist</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span><span class="op">)</span></span></code></pre></div> <p><img src="multistart_files/figure-html/unnamed-chunk-5-1.png" width="700"></p> -<p>The parameter histograms can be further improved by excluding the -result with the low likelihood.</p> +<p>We can use the <code>anova</code> method to compare the models.</p> <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span>, llmin <span class="op">=</span> <span class="op">-</span><span class="fl">326</span>, ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>, <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> -<p><img src="multistart_files/figure-html/unnamed-chunk-6-1.png" width="700"></p> -<p>We can use the <code>anova</code> method to compare the models, -including a likelihood ratio test if the models are nested.</p> -<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_full</span>, <span class="fu"><a href="../../reference/multistart.html">best</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span><span class="op">)</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_full</span>, <span class="fu"><a href="../../reference/multistart.html">best</a></span><span class="op">(</span><span class="va">f_saem_full_multi</span><span class="op">)</span>,</span> +<span> <span class="va">f_saem_reduced</span>, <span class="fu"><a href="../../reference/multistart.html">best</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span><span class="op">)</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Data: 155 observations of 1 variable(s) grouped in 6 datasets</span></span> <span><span class="co">## </span></span> -<span><span class="co">## npar AIC BIC Lik Chisq Df Pr(>Chisq)</span></span> -<span><span class="co">## best(f_saem_reduced_multi) 9 663.69 661.82 -322.85 </span></span> -<span><span class="co">## f_saem_full 10 669.77 667.69 -324.89 0 1 1</span></span></code></pre> -<p>While AIC and BIC are lower for the reduced model, the likelihood -ratio test does not indicate a significant difference between the -fits.</p> +<span><span class="co">## npar AIC BIC Lik Chisq Df Pr(>Chisq)</span></span> +<span><span class="co">## f_saem_reduced 9 663.74 661.87 -322.87 </span></span> +<span><span class="co">## best(f_saem_reduced_multi) 9 663.60 661.72 -322.80 0.1476 0 </span></span> +<span><span class="co">## f_saem_full 10 670.35 668.26 -325.17 0.0000 1 1</span></span> +<span><span class="co">## best(f_saem_full_multi) 10 665.61 663.53 -322.80 4.7372 0</span></span></code></pre> +<p>The reduced model results in lower AIC and BIC values, so it is clearly preferable. Using multiple starting values gives a large improvement in case of the full model, because it is less well-defined, which impedes convergence. For the reduced model, using multiple starting values only results in a small improvement of the model fit.</p> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png Binary files differindex 8f514227..7ad9fa28 100644 --- a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png +++ b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png Binary files differindex 8135d270..f36995ae 100644 --- a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png +++ b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png Binary files differindex f0270537..152554f5 100644 --- a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png +++ b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png diff --git a/docs/dev/authors.html b/docs/dev/authors.html index 7c11d186..3c95e7e0 100644 --- a/docs/dev/authors.html +++ b/docs/dev/authors.html @@ -81,11 +81,6 @@ <li> <a href="articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> - <li class="divider"> - <li class="dropdown-header">Code coverage report</li> - <li> - <a href="coverage/coverage.html"></a> - </li> </ul></li> <li> <a href="news/index.html">News</a> diff --git a/docs/dev/index.html b/docs/dev/index.html index 317e3380..f892841f 100644 --- a/docs/dev/index.html +++ b/docs/dev/index.html @@ -115,12 +115,6 @@ <li> <a href="articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> - <li class="divider"> - </li> -<li class="dropdown-header">Code coverage report</li> - <li> - <a href="coverage/coverage.html"></a> - </li> </ul> </li> <li> @@ -251,21 +245,12 @@ <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a> </h2> <table class="table"> -<tr> -<td> -Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. <i>Environments</i> <b>8</b> (8) 71 <a href="https://doi.org/10.3390/environments8080071" class="external-link">doi:10.3390/environments8080071</a> -</td> -</tr> -<tr> -<td> -Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data <i>Environments</i> <b>6</b> (12) 124 <a href="https://doi.org/10.3390/environments6120124" class="external-link">doi:10.3390/environments6120124</a> -</td> -</tr> -<tr> -<td> -Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data <i>Environmental Sciences Europe</i> <b>30</b> 17 <a href="https://doi.org/10.1186/s12302-018-0145-1" class="external-link">doi:10.1186/s12302-018-0145-1</a> -</td> -</tr> +<tr><td>Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. <i>Environments</i> <b>8</b> (8) 71 <a href="https://doi.org/10.3390/environments8080071" class="external-link">doi:10.3390/environments8080071</a> +</td></tr> +<tr><td>Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data <i>Environments</i> <b>6</b> (12) 124 <a href="https://doi.org/10.3390/environments6120124" class="external-link">doi:10.3390/environments6120124</a> +</td></tr> +<tr><td>Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data <i>Environmental Sciences Europe</i> <b>30</b> 17 <a href="https://doi.org/10.1186/s12302-018-0145-1" class="external-link">doi:10.1186/s12302-018-0145-1</a> +</td></tr> </table> </div> <div class="section level2"> diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html index 2c169609..70eeeed6 100644 --- a/docs/dev/news/index.html +++ b/docs/dev/news/index.html @@ -81,11 +81,6 @@ <li> <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> - <li class="divider"> - <li class="dropdown-header">Code coverage report</li> - <li> - <a href="../coverage/coverage.html"></a> - </li> </ul></li> <li> <a href="../news/index.html">News</a> @@ -176,8 +171,7 @@ </div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.5" id="mkin-105-2021-09-15">mkin 1.0.5 (2021-09-15)<a class="anchor" aria-label="anchor" href="#mkin-105-2021-09-15"></a></h2> -<ul><li>‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”</li> -</ul></div> +<ul><li>‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.4" id="mkin-104-2021-04-20">mkin 1.0.4 (2021-04-20)<a class="anchor" aria-label="anchor" href="#mkin-104-2021-04-20"></a></h2> <ul><li><p>All plotting functions setting graphical parameters: Use on.exit() for resetting graphical parameters</p></li> @@ -186,12 +180,10 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.3" id="mkin-103-2021-02-15">mkin 1.0.3 (2021-02-15)<a class="anchor" aria-label="anchor" href="#mkin-103-2021-02-15"></a></h2> -<ul><li>Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages</li> -</ul></div> +<ul><li>Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.2" id="mkin-102-unreleased">mkin 1.0.2 (Unreleased)<a class="anchor" aria-label="anchor" href="#mkin-102-unreleased"></a></h2> -<ul><li>‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’</li> -</ul></div> +<ul><li>‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.1" id="mkin-101-2021-02-10">mkin 1.0.1 (2021-02-10)<a class="anchor" aria-label="anchor" href="#mkin-101-2021-02-10"></a></h2> <ul><li><p>‘confint.mmkin’, ‘nlme.mmkin’, ‘transform_odeparms’: Fix example code in dontrun sections that failed with current defaults</p></li> @@ -246,8 +238,7 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.49.11" id="mkin-094911-2020-04-20">mkin 0.9.49.11 (2020-04-20)<a class="anchor" aria-label="anchor" href="#mkin-094911-2020-04-20"></a></h2> -<ul><li>Increase a test tolerance to make it pass on all CRAN check machines</li> -</ul></div> +<ul><li>Increase a test tolerance to make it pass on all CRAN check machines</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.49.10" id="mkin-094910-2020-04-18">mkin 0.9.49.10 (2020-04-18)<a class="anchor" aria-label="anchor" href="#mkin-094910-2020-04-18"></a></h2> <ul><li><p>‘nlme.mmkin’: An nlme method for mmkin row objects and an associated S3 class with print, plot, anova and endpoint methods</p></li> @@ -362,8 +353,7 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.46" id="mkin-0946-2017-07-24">mkin 0.9.46 (2017-07-24)<a class="anchor" aria-label="anchor" href="#mkin-0946-2017-07-24"></a></h2> -<ul><li>Remove <code>test_FOMC_ill-defined.R</code> as it is too platform dependent</li> -</ul></div> +<ul><li>Remove <code>test_FOMC_ill-defined.R</code> as it is too platform dependent</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.45.2" id="mkin-09452-2017-07-24">mkin 0.9.45.2 (2017-07-24)<a class="anchor" aria-label="anchor" href="#mkin-09452-2017-07-24"></a></h2> <ul><li><p>Rename <code>twa</code> to <code>max_twa_parent</code> to avoid conflict with <code>twa</code> from my <code>pfm</code> package</p></li> @@ -375,8 +365,7 @@ <h2 class="page-header" data-toc-text="0.9.45.1" id="mkin-09451-2016-12-20">mkin 0.9.45.1 (2016-12-20)<a class="anchor" aria-label="anchor" href="#mkin-09451-2016-12-20"></a></h2> <div class="section level3"> <h3 id="new-features-0-9-45-1">New features<a class="anchor" aria-label="anchor" href="#new-features-0-9-45-1"></a></h3> -<ul><li>A <code>twa</code> function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).</li> -</ul></div> +<ul><li>A <code>twa</code> function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.45" id="mkin-0945-2016-12-08">mkin 0.9.45 (2016-12-08)<a class="anchor" aria-label="anchor" href="#mkin-0945-2016-12-08"></a></h2> @@ -391,8 +380,7 @@ <h2 class="page-header" data-toc-text="0.9.44" id="mkin-0944-2016-06-29">mkin 0.9.44 (2016-06-29)<a class="anchor" aria-label="anchor" href="#mkin-0944-2016-06-29"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-44">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-44"></a></h3> -<ul><li>The test <code>test_FOMC_ill-defined</code> failed on several architectures, so the test is now skipped</li> -</ul></div> +<ul><li>The test <code>test_FOMC_ill-defined</code> failed on several architectures, so the test is now skipped</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.43" id="mkin-0943-2016-06-28">mkin 0.9.43 (2016-06-28)<a class="anchor" aria-label="anchor" href="#mkin-0943-2016-06-28"></a></h2> @@ -426,8 +414,7 @@ <h2 class="page-header" data-toc-text="0.9.42" id="mkin-0942-2016-03-25">mkin 0.9.42 (2016-03-25)<a class="anchor" aria-label="anchor" href="#mkin-0942-2016-03-25"></a></h2> <div class="section level3"> <h3 id="major-changes-0-9-42">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-42"></a></h3> -<ul><li>Add the argument <code>from_max_mean</code> to <code>mkinfit</code>, for fitting only the decline from the maximum observed value for models with a single observed variable</li> -</ul></div> +<ul><li>Add the argument <code>from_max_mean</code> to <code>mkinfit</code>, for fitting only the decline from the maximum observed value for models with a single observed variable</li></ul></div> <div class="section level3"> <h3 id="minor-changes-0-9-42">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-9-42"></a></h3> <ul><li><p>Add plots to <code>compiled_models</code> vignette</p></li> @@ -447,21 +434,18 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-41">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-41"></a></h3> <ul><li> -<code><a href="../reference/summary.mkinfit.html">print.summary.mkinfit()</a></code>: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36</li> -</ul></div> +<code><a href="../reference/summary.mkinfit.html">print.summary.mkinfit()</a></code>: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-40" id="mkin-09-40-2015-07-21">mkin 0.9-40 (2015-07-21)<a class="anchor" aria-label="anchor" href="#mkin-09-40-2015-07-21"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-40">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-40"></a></h3> <ul><li> -<code><a href="../reference/endpoints.html">endpoints()</a></code>: For DFOP and SFORB models, where <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.</li> -</ul></div> +<code><a href="../reference/endpoints.html">endpoints()</a></code>: For DFOP and SFORB models, where <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.</li></ul></div> <div class="section level3"> <h3 id="internal-changes-0-9-40">Internal changes<a class="anchor" aria-label="anchor" href="#internal-changes-0-9-40"></a></h3> <ul><li> -<code>DESCRIPTION</code>, <code>NAMESPACE</code>, <code>R/*.R</code>: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.</li> -</ul></div> +<code>DESCRIPTION</code>, <code>NAMESPACE</code>, <code>R/*.R</code>: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-39" id="mkin-09-39-2015-06-26">mkin 0.9-39 (2015-06-26)<a class="anchor" aria-label="anchor" href="#mkin-09-39-2015-06-26"></a></h2> @@ -473,8 +457,7 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-39">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-39"></a></h3> <ul><li> -<code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.</li> -</ul></div> +<code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-38" id="mkin-09-38-2015-06-24">mkin 0.9-38 (2015-06-24)<a class="anchor" aria-label="anchor" href="#mkin-09-38-2015-06-24"></a></h2> @@ -486,8 +469,7 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-38">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-38"></a></h3> <ul><li> -<code><a href="../reference/mkinmod.html">mkinmod()</a></code>: When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.</li> -</ul></div> +<code><a href="../reference/mkinmod.html">mkinmod()</a></code>: When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-36" id="mkin-09-36-2015-06-21">mkin 0.9-36 (2015-06-21)<a class="anchor" aria-label="anchor" href="#mkin-09-36-2015-06-21"></a></h2> @@ -500,15 +482,13 @@ </ul></div> <div class="section level3"> <h3 id="minor-changes-0-9-36">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-9-36"></a></h3> -<ul><li>Added a simple showcase vignette with an evaluation of FOCUS example dataset D</li> -</ul></div> +<ul><li>Added a simple showcase vignette with an evaluation of FOCUS example dataset D</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-35" id="mkin-09-35-2015-05-15">mkin 0.9-35 (2015-05-15)<a class="anchor" aria-label="anchor" href="#mkin-09-35-2015-05-15"></a></h2> <div class="section level3"> <h3 id="major-changes-0-9-35">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-35"></a></h3> -<ul><li>Switch from RUnit to testthat for testing</li> -</ul></div> +<ul><li>Switch from RUnit to testthat for testing</li></ul></div> <div class="section level3"> <h3 id="bug-fixes-0-9-35">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-35"></a></h3> <ul><li><p><code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Avoid warnings that occurred when not all confidence intervals were available in the summary of the fit</p></li> @@ -590,15 +570,13 @@ <h2 class="page-header" data-toc-text="0.9-31" id="mkin-09-31-2014-07-14">mkin 0.9-31 (2014-07-14)<a class="anchor" aria-label="anchor" href="#mkin-09-31-2014-07-14"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-31">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-31"></a></h3> -<ul><li>The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in <code><a href="../reference/mkinerrmin.html">mkinerrmin()</a></code> used by the summary function.</li> -</ul></div> +<ul><li>The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in <code><a href="../reference/mkinerrmin.html">mkinerrmin()</a></code> used by the summary function.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-30" id="mkin-09-30-2014-07-11">mkin 0.9-30 (2014-07-11)<a class="anchor" aria-label="anchor" href="#mkin-09-30-2014-07-11"></a></h2> <div class="section level3"> <h3 id="new-features-0-9-30">New features<a class="anchor" aria-label="anchor" href="#new-features-0-9-30"></a></h3> -<ul><li>It is now possible to use formation fractions in combination with turning off the sink in <code><a href="../reference/mkinmod.html">mkinmod()</a></code>.</li> -</ul></div> +<ul><li>It is now possible to use formation fractions in combination with turning off the sink in <code><a href="../reference/mkinmod.html">mkinmod()</a></code>.</li></ul></div> <div class="section level3"> <h3 id="major-changes-0-9-30">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-30"></a></h3> <ul><li><p>The original and the transformed parameters now have different names (e.g. <code>k_parent</code> and <code>log_k_parent</code>. They also differ in how many they are when we have formation fractions but no pathway to sink.</p></li> diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index b7825ae1..a9ab0c60 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -1,4 +1,4 @@ -pandoc: 2.17.1.1 +pandoc: 2.9.2.1 pkgdown: 2.0.7 pkgdown_sha: ~ articles: @@ -16,7 +16,7 @@ articles: dimethenamid_2018: web_only/dimethenamid_2018.html multistart: web_only/multistart.html saem_benchmarks: web_only/saem_benchmarks.html -last_built: 2023-04-16T08:48Z +last_built: 2023-04-17T17:35Z 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 Binary files differindex 5de2bdc7..278fd2e2 100644 --- a/docs/dev/reference/Rplot001.png +++ b/docs/dev/reference/Rplot001.png diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png Binary files differindex 556ca0a7..4b646f22 100644 --- a/docs/dev/reference/Rplot002.png +++ b/docs/dev/reference/Rplot002.png diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html index 84bbbdc4..85dc7c6e 100644 --- a/docs/dev/reference/index.html +++ b/docs/dev/reference/index.html @@ -81,11 +81,6 @@ <li> <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> - <li class="divider"> - <li class="dropdown-header">Code coverage report</li> - <li> - <a href="../coverage/coverage.html"></a> - </li> </ul></li> <li> <a href="../news/index.html">News</a> diff --git a/docs/dev/reference/mkinpredict.html b/docs/dev/reference/mkinpredict.html index 01c15a19..7d8e7c26 100644 --- a/docs/dev/reference/mkinpredict.html +++ b/docs/dev/reference/mkinpredict.html @@ -394,11 +394,12 @@ as these always return mapped output.</p></dd> <span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">20</span>, by <span class="op">=</span> <span class="fl">0.1</span><span class="op">)</span>,</span></span> <span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"analytical"</span>, use_compiled <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span><span class="op">[</span><span class="fl">201</span>,<span class="op">]</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Loading required package: rbenchmark</span> <span class="r-out co"><span class="r-pr">#></span> test relative elapsed</span> -<span class="r-out co"><span class="r-pr">#></span> 2 deSolve_compiled 1.0 0.002</span> -<span class="r-out co"><span class="r-pr">#></span> 4 analytical 1.0 0.002</span> -<span class="r-out co"><span class="r-pr">#></span> 1 eigen 4.0 0.008</span> -<span class="r-out co"><span class="r-pr">#></span> 3 deSolve 30.5 0.061</span> +<span class="r-out co"><span class="r-pr">#></span> 2 deSolve_compiled 1.00 0.004</span> +<span class="r-out co"><span class="r-pr">#></span> 1 eigen 4.00 0.016</span> +<span class="r-out co"><span class="r-pr">#></span> 4 analytical 4.25 0.017</span> +<span class="r-out co"><span class="r-pr">#></span> 3 deSolve 40.75 0.163</span> <span class="r-in"><span></span></span> <span class="r-in"><span><span class="co"># \dontrun{</span></span></span> <span class="r-in"><span> <span class="co"># Predict from a fitted model</span></span></span> diff --git a/docs/dev/reference/multistart-1.png b/docs/dev/reference/multistart-1.png Binary files differindex c7937d67..ee0306d6 100644 --- a/docs/dev/reference/multistart-1.png +++ b/docs/dev/reference/multistart-1.png diff --git a/docs/dev/reference/multistart-2.png b/docs/dev/reference/multistart-2.png Binary files differindex e1983f12..69a178e3 100644 --- a/docs/dev/reference/multistart-2.png +++ b/docs/dev/reference/multistart-2.png diff --git a/docs/dev/reference/multistart.html b/docs/dev/reference/multistart.html index 3cdede7b..36767560 100644 --- a/docs/dev/reference/multistart.html +++ b/docs/dev/reference/multistart.html @@ -222,15 +222,13 @@ doi: 10.1186/s12859-021-04373-4.</p> <span class="r-in"><span></span></span> <span class="r-in"><span><span class="va">f_saem_reduced</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_full</span>, no_random_effect <span class="op">=</span> <span class="st">"log_k2"</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_reduced</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="co"># On Windows, we need to create a cluster first. When working with</span></span></span> -<span class="r-in"><span><span class="co"># such a cluster, we need to export the mmkin object to the cluster</span></span></span> -<span class="r-in"><span><span class="co"># nodes, as it is referred to when updating the saem object on the nodes.</span></span></span> +<span class="r-in"><span><span class="co"># On Windows, we need to create a PSOCK cluster first and refer to it</span></span></span> +<span class="r-in"><span><span class="co"># in the call to multistart()</span></span></span> <span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">parallel</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="va">cl</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/parallel/makeCluster.html" class="external-link">makePSOCKcluster</a></span><span class="op">(</span><span class="fl">12</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="va">f_saem_reduced_multi</span> <span class="op"><-</span> <span class="fu">multistart</span><span class="op">(</span><span class="va">f_saem_reduced</span>, n <span class="op">=</span> <span class="fl">16</span>, cluster <span class="op">=</span> <span class="va">cl</span><span class="op">)</span></span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in checkForRemoteErrors(val):</span> 16 nodes produced errors; first error: unused argument (mc.preschedule = FALSE)</span> -<span class="r-in"><span><span class="fu"><a href="parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span><span class="op">)</span></span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in parplot(f_saem_reduced_multi, lpos = "topright"):</span> object 'f_saem_reduced_multi' not found</span> +<span class="r-in"><span><span class="fu"><a href="parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span>, ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>, <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="multistart-2.png" alt="" width="700" height="433"></span> <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/parallel/makeCluster.html" class="external-link">stopCluster</a></span><span class="op">(</span><span class="va">cl</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> diff --git a/docs/dev/sitemap.xml b/docs/dev/sitemap.xml index b70dc782..b3542d0b 100644 --- a/docs/dev/sitemap.xml +++ b/docs/dev/sitemap.xml @@ -55,9 +55,6 @@ <loc>https://pkgdown.jrwb.de/mkin/authors.html</loc> </url> <url> - <loc>https://pkgdown.jrwb.de/mkin/coverage/coverage.html</loc> - </url> - <url> <loc>https://pkgdown.jrwb.de/mkin/index.html</loc> </url> <url> diff --git a/inst/rmarkdown/templates/hierarchical_kinetics/skeleton/.skeleton.Rmd.swp b/inst/rmarkdown/templates/hierarchical_kinetics/skeleton/.skeleton.Rmd.swp Binary files differnew file mode 100644 index 00000000..2c5bfed8 --- /dev/null +++ b/inst/rmarkdown/templates/hierarchical_kinetics/skeleton/.skeleton.Rmd.swp diff --git a/man/multistart.Rd b/man/multistart.Rd index 5a5f7b44..0df29bfa 100644 --- a/man/multistart.Rd +++ b/man/multistart.Rd @@ -82,13 +82,12 @@ illparms(f_saem_full) f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") illparms(f_saem_reduced) -# On Windows, we need to create a cluster first. When working with -# such a cluster, we need to export the mmkin object to the cluster -# nodes, as it is referred to when updating the saem object on the nodes. +# On Windows, we need to create a PSOCK cluster first and refer to it +# in the call to multistart() library(parallel) cl <- makePSOCKcluster(12) f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl) -parplot(f_saem_reduced_multi, lpos = "topright") +parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2)) stopCluster(cl) } } diff --git a/vignettes/web_only/multistart.html b/vignettes/web_only/multistart.html index 88c64a28..c65bf376 100644 --- a/vignettes/web_only/multistart.html +++ b/vignettes/web_only/multistart.html @@ -403,18 +403,20 @@ runs:</p> <p><img 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" width="672" /></p> <p>We can use the <code>anova</code> method to compare the models.</p> <pre class="r"><code>anova(f_saem_full, best(f_saem_full_multi), - f_saem_reduced, best(f_saem_reduced_multi))</code></pre> + f_saem_reduced, best(f_saem_reduced_multi), test = TRUE)</code></pre> <pre><code>## Data: 155 observations of 1 variable(s) grouped in 6 datasets ## -## npar AIC BIC Lik -## f_saem_reduced 9 663.73 661.86 -322.86 -## best(f_saem_reduced_multi) 9 663.69 661.82 -322.85 -## f_saem_full 10 669.77 667.69 -324.89 -## best(f_saem_full_multi) 10 665.56 663.48 -322.78</code></pre> -<p>The reduced model gives the lowest information criteria and similar -likelihoods as the best variant of the full model. The multistart method -leads to a much lower improvement of the likelihood for the reduced -model, indicating that it is fitted more efficiently.</p> +## npar AIC BIC Lik Chisq Df Pr(>Chisq) +## f_saem_reduced 9 663.73 661.86 -322.86 +## best(f_saem_reduced_multi) 9 663.69 661.82 -322.85 0.0361 0 +## f_saem_full 10 669.77 667.69 -324.89 0.0000 1 1 +## best(f_saem_full_multi) 10 665.56 663.48 -322.78 4.2060 0</code></pre> +<p>The reduced model results in lower AIC and BIC values, so it is +clearly preferable. Using multiple starting values gives a large +improvement in case of the full model, because it is less well-defined, +which impedes convergence. For the reduced model, using multiple +starting values only results in a small improvement of the model +fit.</p> diff --git a/vignettes/web_only/multistart.rmd b/vignettes/web_only/multistart.rmd index 2a9b3599..34ed1ad4 100644 --- a/vignettes/web_only/multistart.rmd +++ b/vignettes/web_only/multistart.rmd @@ -67,11 +67,12 @@ We can use the `anova` method to compare the models. ```{r} anova(f_saem_full, best(f_saem_full_multi), - f_saem_reduced, best(f_saem_reduced_multi)) + f_saem_reduced, best(f_saem_reduced_multi), test = TRUE) ``` -The reduced model gives the lowest information criteria and similar -likelihoods as the best variant of the full model. The multistart method -leads to a much lower improvement of the likelihood for the reduced model, -indicating that it converges faster. - +The reduced model results in lower AIC and BIC values, so it +is clearly preferable. Using multiple starting values gives +a large improvement in case of the full model, because it is +less well-defined, which impedes convergence. For the reduced +model, using multiple starting values only results in a small +improvement of the model fit. |
