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<img src="" class="logo" alt=""><h1>Example evaluation of FOCUS Example Dataset D</h1> + + <h1>Example evaluation of FOCUS Example Dataset D</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 31 January 2019 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/FOCUS_D.rmd" class="external-link"><code>vignettes/FOCUS_D.rmd</code></a></small> <div class="d-none name"><code>FOCUS_D.rmd</code></div> @@ -199,10 +185,10 @@ the <code>mkinparplot</code> function.</p> <code>summary</code> method for <code>mkinfit</code> objects.</p> <div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:11 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:11 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:24 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:24 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - k_parent * parent</span></span> @@ -210,7 +196,7 @@ the <code>mkinparplot</code> function.</p> <span><span class="co">## </span></span> <span><span class="co">## Model predictions using solution type analytical </span></span> <span><span class="co">## </span></span> -<span><span class="co">## Fitted using 401 model solutions performed in 0.051 s</span></span> +<span><span class="co">## Fitted using 401 model solutions performed in 0.054 s</span></span> <span><span class="co">## </span></span> <span><span class="co">## Error model: Constant variance </span></span> <span><span class="co">## </span></span> @@ -326,28 +312,26 @@ the <code>mkinparplot</code> function.</p> <span><span class="co">## 100 m1 33.13 31.98162 1.148e+00</span></span> <span><span class="co">## 120 m1 25.15 28.78984 -3.640e+00</span></span> <span><span class="co">## 120 m1 33.31 28.78984 4.520e+00</span></span></code></pre> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - 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<input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"> -</form> - - <ul class="navbar-nav"> -<li class="nav-item"> - <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github"> - <span class="fab fa fab fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Example evaluation of FOCUS Laboratory Data L1 to L3</h1> + + <h1>Example evaluation of FOCUS Laboratory Data L1 to L3</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 18 May 2023 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/FOCUS_L.rmd" class="external-link"><code>vignettes/FOCUS_L.rmd</code></a></small> <div class="d-none name"><code>FOCUS_L.rmd</code></div> @@ -131,10 +117,10 @@ report.</p> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m.L1.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L1.SFO</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:13 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:13 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:26 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:26 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - k_parent * parent</span></span> @@ -224,7 +210,9 @@ objects.</p> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../reference/mkinresplot.html">mkinresplot</a></span><span class="op">(</span><span class="va">m.L1.SFO</span>, ylab <span class="op">=</span> <span class="st">"Observed"</span>, xlab <span class="op">=</span> <span class="st">"Time"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-5-1.png" width="576"></p> -<p>For comparison, the FOMC model is fitted as well, and the <span class="math inline">\(\chi^2\)</span> error level is checked.</p> +<p>For comparison, the FOMC model is fitted as well, and the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level is checked.</p> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m.L1.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge:</span></span> @@ -235,20 +223,19 @@ objects.</p> <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L1.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Warning in sqrt(diag(covar)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in sqrt(1/diag(V)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result</span></span> -<span><span class="co">## is doubtful</span></span></code></pre> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:13 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:13 2023 </span></span> +<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the</span></span> +<span><span class="co">## non-finite result may be dubious</span></span></code></pre> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:26 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:26 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> <span><span class="co">## </span></span> <span><span class="co">## Model predictions using solution type analytical </span></span> <span><span class="co">## </span></span> -<span><span class="co">## Fitted using 342 model solutions performed in 0.023 s</span></span> +<span><span class="co">## Fitted using 342 model solutions performed in 0.024 s</span></span> <span><span class="co">## </span></span> <span><span class="co">## Error model: Constant variance </span></span> <span><span class="co">## </span></span> @@ -316,36 +303,40 @@ objects.</p> model is overparameterised, <em>i.e.</em> contains too many parameters that are ill-defined as a consequence.</p> <p>And in fact, due to the higher number of parameters, and the lower -number of degrees of freedom of the fit, the <span class="math inline">\(\chi^2\)</span> error level is actually higher for -the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the -parameters <code>log_alpha</code> and <code>log_beta</code> internally -fitted in the model have excessive confidence intervals, that span more -than 25 orders of magnitude (!) when backtransformed to the scale of -<code>alpha</code> and <code>beta</code>. Also, the t-test for -significant difference from zero does not indicate such a significant -difference, with p-values greater than 0.1, and finally, the parameter -correlation of <code>log_alpha</code> and <code>log_beta</code> is -1.000, clearly indicating that the model is overparameterised.</p> -<p>The <span class="math inline">\(\chi^2\)</span> error levels reported -in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to -integer percentages and partly deviate by one percentage point from the -results calculated by mkin. The reason for this is not known. However, -mkin gives the same <span class="math inline">\(\chi^2\)</span> error -levels as the kinfit package and the calculation routines of the kinfit -package have been extensively compared to the results obtained by the -KinGUI software, as documented in the kinfit package vignette. KinGUI -was the first widely used standard package in this field. Also, the -calculation of <span class="math inline">\(\chi^2\)</span> error levels -was compared with KinGUII, CAKE and DegKin manager in a project -sponsored by the German Umweltbundesamt <span class="citation">(Ranke -2014)</span>.</p> +number of degrees of freedom of the fit, the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level is actually higher for the FOMC model (3.6%) than for the +SFO model (3.4%). Additionally, the parameters <code>log_alpha</code> +and <code>log_beta</code> internally fitted in the model have excessive +confidence intervals, that span more than 25 orders of magnitude (!) +when backtransformed to the scale of <code>alpha</code> and +<code>beta</code>. Also, the t-test for significant difference from zero +does not indicate such a significant difference, with p-values greater +than 0.1, and finally, the parameter correlation of +<code>log_alpha</code> and <code>log_beta</code> is 1.000, clearly +indicating that the model is overparameterised.</p> +<p>The +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error levels reported in Appendix 3 and Appendix 7 to the FOCUS kinetics +report are rounded to integer percentages and partly deviate by one +percentage point from the results calculated by mkin. The reason for +this is not known. However, mkin gives the same +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error levels as the kinfit package and the calculation routines of the +kinfit package have been extensively compared to the results obtained by +the KinGUI software, as documented in the kinfit package vignette. +KinGUI was the first widely used standard package in this field. Also, +the calculation of +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error levels was compared with KinGUII, CAKE and DegKin manager in a +project sponsored by the German Umweltbundesamt <span class="citation">(Ranke 2014)</span>.</p> </div> <div class="section level2"> <h2 id="laboratory-data-l2">Laboratory Data L2<a class="anchor" aria-label="anchor" href="#laboratory-data-l2"></a> </h2> <p>The following code defines example dataset L2 from the FOCUS kinetics report, p. 287:</p> -<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">FOCUS_2006_L2</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> <span> t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><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</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="op">)</span>, each <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>,</span> <span> parent <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">96.1</span>, <span class="fl">91.8</span>, <span class="fl">41.4</span>, <span class="fl">38.7</span>,</span> @@ -358,15 +349,16 @@ report, p. 287:</p> <p>Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument <code>show_residuals</code> to the plot command.</p> -<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m.L2.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.SFO</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>,</span> <span> main <span class="op">=</span> <span class="st">"FOCUS L2 - SFO"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-8-1.png" width="672"></p> -<p>The <span class="math inline">\(\chi^2\)</span> error level of 14% -suggests that the model does not fit very well. This is also obvious -from the plots of the fit, in which we have included the residual -plot.</p> +<p>The +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level of 14% suggests that the model does not fit very well. This +is also obvious from the plots of the fit, in which we have included the +residual plot.</p> <p>In the FOCUS kinetics report, it is stated that there is no apparent systematic error observed from the residual plot up to the measured DT90 (approximately at day 5), and there is an underestimation beyond that @@ -381,25 +373,27 @@ kinetics.</p> <div class="section level3"> <h3 id="fomc-fit-for-l2">FOMC fit for L2<a class="anchor" aria-label="anchor" href="#fomc-fit-for-l2"></a> </h3> -<p>For comparison, the FOMC model is fitted as well, and the <span class="math inline">\(\chi^2\)</span> error level is checked.</p> -<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> +<p>For comparison, the FOMC model is fitted as well, and the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level is checked.</p> +<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m.L2.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>,</span> <span> main <span class="op">=</span> <span class="st">"FOCUS L2 - FOMC"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-9-1.png" width="672"></p> -<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:13 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:14 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:26 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:26 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> <span><span class="co">## </span></span> <span><span class="co">## Model predictions using solution type analytical </span></span> <span><span class="co">## </span></span> -<span><span class="co">## Fitted using 239 model solutions performed in 0.014 s</span></span> +<span><span class="co">## Fitted using 239 model solutions performed in 0.015 s</span></span> <span><span class="co">## </span></span> <span><span class="co">## Error model: Constant variance </span></span> <span><span class="co">## </span></span> @@ -457,26 +451,29 @@ kinetics.</p> <span><span class="co">## Estimated disappearance times:</span></span> <span><span class="co">## DT50 DT90 DT50back</span></span> <span><span class="co">## parent 0.8092 5.356 1.612</span></span></code></pre> -<p>The error level at which the <span class="math inline">\(\chi^2\)</span> test passes is much lower in this -case. Therefore, the FOMC model provides a better description of the -data, as less experimental error has to be assumed in order to explain -the data.</p> +<p>The error level at which the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +test passes is much lower in this case. Therefore, the FOMC model +provides a better description of the data, as less experimental error +has to be assumed in order to explain the data.</p> </div> <div class="section level3"> <h3 id="dfop-fit-for-l2">DFOP fit for L2<a class="anchor" aria-label="anchor" href="#dfop-fit-for-l2"></a> </h3> -<p>Fitting the four parameter DFOP model further reduces the <span class="math inline">\(\chi^2\)</span> error level.</p> -<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> +<p>Fitting the four parameter DFOP model further reduces the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level.</p> +<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m.L2.DFOP</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>,</span> <span> main <span class="op">=</span> <span class="st">"FOCUS L2 - DFOP"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-10-1.png" width="672"></p> -<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:14 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:14 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:27 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:27 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span></span> @@ -485,7 +482,7 @@ the data.</p> <span><span class="co">## </span></span> <span><span class="co">## Model predictions using solution type analytical </span></span> <span><span class="co">## </span></span> -<span><span class="co">## Fitted using 581 model solutions performed in 0.041 s</span></span> +<span><span class="co">## Fitted using 581 model solutions performed in 0.043 s</span></span> <span><span class="co">## </span></span> <span><span class="co">## Error model: Constant variance </span></span> <span><span class="co">## </span></span> @@ -557,7 +554,7 @@ based on the chi^2 error level criterion.</p> </h2> <p>The following code defines example dataset L3 from the FOCUS kinetics report, p. 290.</p> -<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">FOCUS_2006_L3</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> <span> t <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</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>,</span> <span> parent <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">97.8</span>, <span class="fl">60</span>, <span class="fl">51</span>, <span class="fl">43</span>, <span class="fl">35</span>, <span class="fl">22</span>, <span class="fl">15</span>, <span class="fl">12</span><span class="op">)</span><span class="op">)</span></span> @@ -569,16 +566,22 @@ report, p. 290.</p> one or more datasets in one call to the function <code>mmkin</code>. The datasets have to be passed in a list, in this case a named list holding only the L3 dataset prepared above.</p> -<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="co"># Only use one core here, not to offend the CRAN checks</span></span> <span><span class="va">mm.L3</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><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="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>,</span> <span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS L3"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L3_mkin</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-12-1.png" width="700"></p> -<p>The <span class="math inline">\(\chi^2\)</span> error level of 21% as -well as the plot suggest that the SFO model does not fit very well. The -FOMC model performs better, with an error level at which the <span class="math inline">\(\chi^2\)</span> test passes of 7%. Fitting the -four parameter DFOP model further reduces the <span class="math inline">\(\chi^2\)</span> error level considerably.</p> +<p>The +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level of 21% as well as the plot suggest that the SFO model does +not fit very well. The FOMC model performs better, with an error level +at which the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +test passes of 7%. Fitting the four parameter DFOP model further reduces +the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level considerably.</p> </div> <div class="section level3"> <h3 id="accessing-mmkin-objects">Accessing mmkin objects<a class="anchor" aria-label="anchor" href="#accessing-mmkin-objects"></a> @@ -588,12 +591,12 @@ as a row index and datasets as a column index.</p> <p>We can extract the summary and plot for <em>e.g.</em> the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.</p> -<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:14 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:14 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:27 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:27 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span></span> @@ -676,14 +679,15 @@ summary and plot functions working on mkinfit objects.</p> <span><span class="co">## 60 parent 22.0 23.26 -1.25919</span></span> <span><span class="co">## 91 parent 15.0 15.18 -0.18181</span></span> <span><span class="co">## 120 parent 12.0 10.19 1.81395</span></span></code></pre> -<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-13-1.png" width="700"></p> <p>Here, a look to the model plot, the confidence intervals of the parameters and the correlation matrix suggest that the parameter estimates are reliable, and the DFOP model can be used as the best-fit -model based on the <span class="math inline">\(\chi^2\)</span> error -level criterion for laboratory data L3.</p> +model based on the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level criterion for laboratory data L3.</p> <p>This is also an example where the standard t-test for the parameter <code>g_ilr</code> is misleading, as it tests for a significant difference from zero. In this case, zero appears to be the correct value @@ -696,31 +700,33 @@ parameter <code>g</code> is quite narrow.</p> </h2> <p>The following code defines example dataset L4 from the FOCUS kinetics report, p. 293:</p> -<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">FOCUS_2006_L4</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> <span> t <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</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>,</span> <span> parent <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">96.6</span>, <span class="fl">96.3</span>, <span class="fl">94.3</span>, <span class="fl">88.8</span>, <span class="fl">74.9</span>, <span class="fl">59.9</span>, <span class="fl">53.5</span>, <span class="fl">49.0</span><span class="op">)</span><span class="op">)</span></span> <span><span class="va">FOCUS_2006_L4_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L4</span><span class="op">)</span></span></code></pre></div> <p>Fits of the SFO and FOMC models, plots and summaries are produced below:</p> -<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="co"># Only use one core here, not to offend the CRAN checks</span></span> <span><span class="va">mm.L4</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><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="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>,</span> <span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS L4"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L4_mkin</span><span class="op">)</span>,</span> <span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-15-1.png" width="700"></p> -<p>The <span class="math inline">\(\chi^2\)</span> error level of 3.3% -as well as the plot suggest that the SFO model fits very well. The error -level at which the <span class="math inline">\(\chi^2\)</span> test -passes is slightly lower for the FOMC model. However, the difference -appears negligible.</p> -<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<p>The +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level of 3.3% as well as the plot suggest that the SFO model fits +very well. The error level at which the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +test passes is slightly lower for the FOMC model. However, the +difference appears negligible.</p> +<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"SFO"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:14 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:15 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:27 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:28 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - k_parent * parent</span></span> @@ -780,12 +786,12 @@ appears negligible.</p> <span><span class="co">## Estimated disappearance times:</span></span> <span><span class="co">## DT50 DT90</span></span> <span><span class="co">## parent 106 352</span></span></code></pre> -<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"FOMC"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> -<pre><code><span><span class="co">## mkin version used for fitting: 1.2.6 </span></span> -<span><span class="co">## R version used for fitting: 4.3.2 </span></span> -<span><span class="co">## Date of fit: Thu Nov 16 04:20:15 2023 </span></span> -<span><span class="co">## Date of summary: Thu Nov 16 04:20:15 2023 </span></span> +<pre><code><span><span class="co">## mkin version used for fitting: 1.2.10 </span></span> +<span><span class="co">## R version used for fitting: 4.5.0 </span></span> +<span><span class="co">## Date of fit: Mon May 12 21:54:27 2025 </span></span> +<span><span class="co">## Date of summary: Mon May 12 21:54:28 2025 </span></span> <span><span class="co">## </span></span> <span><span class="co">## Equations:</span></span> <span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> @@ -862,28 +868,26 @@ Validierung von Modellierungssoftware als Alternative zu ModelMaker </div> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/FOCUS_L_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/FOCUS_L_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd6..00000000 --- a/docs/articles/FOCUS_L_files/accessible-code-block-0.0.1/empty-anchor.js +++ /dev/null @@ -1,15 +0,0 @@ -// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> -// v0.0.1 -// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. - -document.addEventListener('DOMContentLoaded', function() { - const codeList = document.getElementsByClassName("sourceCode"); - for (var i = 0; i < codeList.length; i++) { - var linkList = codeList[i].getElementsByTagName('a'); - for (var j = 0; j < linkList.length; j++) { - if (linkList[j].innerHTML === "") { - linkList[j].setAttribute('aria-hidden', 'true'); - } - } - } -}); diff --git a/docs/articles/FOCUS_L_files/header-attrs-2.6/header-attrs.js b/docs/articles/FOCUS_L_files/header-attrs-2.6/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/FOCUS_L_files/header-attrs-2.6/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. We remove the former (to -// be compatible with the behavior of Pandoc < 2.8). -document.addEventListener('DOMContentLoaded', function(e) { - var hs = document.querySelectorAll("div.section[class*='level'] > :first-child"); - var i, h, a; - for (i = 0; i < hs.length; i++) { - h = hs[i]; - if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6 - a = h.attributes; - while (a.length > 0) h.removeAttribute(a[0].name); - } -}); diff --git a/docs/articles/FOCUS_L_files/header-attrs-2.7/header-attrs.js b/docs/articles/FOCUS_L_files/header-attrs-2.7/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/FOCUS_L_files/header-attrs-2.7/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. We remove the former (to -// be compatible with the behavior of Pandoc < 2.8). -document.addEventListener('DOMContentLoaded', function(e) { - var hs = document.querySelectorAll("div.section[class*='level'] > :first-child"); - var i, h, a; - for (i = 0; i < hs.length; i++) { - h = hs[i]; - if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6 - a = h.attributes; - while (a.length > 0) h.removeAttribute(a[0].name); - } -}); diff --git a/docs/articles/index.html b/docs/articles/index.html index 0c3e7449..b70a25c4 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -1,5 +1,5 @@ <!DOCTYPE html> -<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • mkin</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Articles"></head><body> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • mkin</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Articles"></head><body> <a href="#main" class="visually-hidden-focusable">Skip to contents</a> @@ -7,7 +7,7 @@ <a class="navbar-brand me-2" href="../index.html">mkin</a> - <small class="nav-text text-default me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">1.2.9</small> + <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">1.2.10</small> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> @@ -28,7 +28,7 @@ <li><h6 class="dropdown-header" data-toc-skip>Example evaluations with hierarchical models (nonlinear mixed-effects models)</h6></li> <li><a class="dropdown-item" href="../articles/prebuilt/2022_dmta_parent.html">Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</a></li> <li><a class="dropdown-item" href="../articles/prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a></li> - <li><a class="dropdown-item" href="../articles/prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></li> + <li><a class="dropdown-item" href="../articles/web_only/mesotrione_parent_2023.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></li> <li><a class="dropdown-item" href="../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a></li> <li><a class="dropdown-item" href="../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a></li> <li><a class="dropdown-item" href="../articles/web_only/multistart.html">Short demo of the multistart method</a></li> @@ -68,8 +68,6 @@ <dd> </dd><dt><a href="prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a></dt> <dd> - </dd><dt><a href="prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></dt> - <dd> </dd><dt><a href="web_only/benchmarks.html">Benchmark timings for mkin</a></dt> <dd> </dd><dt><a href="web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a></dt> @@ -82,6 +80,8 @@ <dd> </dd><dt><a href="web_only/FOCUS_Z.html">Example evaluation of FOCUS dataset Z</a></dt> <dd> + </dd><dt><a href="web_only/mesotrione_parent_2023.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></dt> + <dd> </dd><dt><a href="mkin.html">Short introduction to mkin</a></dt> <dd> </dd><dt><a href="web_only/multistart.html">Short demo of the multistart method</a></dt> diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html index b6ca47ad..10239ccb 100644 --- a/docs/articles/mkin.html +++ b/docs/articles/mkin.html @@ -7,8 +7,10 @@ <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <title>Short introduction to mkin • mkin</title> <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> -<link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"> -<script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Short introduction to mkin"> +<link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"> +<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"> +<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"> +<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Short introduction to mkin"> </head> <body> <a href="#main" class="visually-hidden-focusable">Skip to contents</a> @@ -18,7 +20,7 @@ <a class="navbar-brand me-2" href="../index.html">mkin</a> - <small class="nav-text text-default me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">1.2.9</small> + <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">1.2.10</small> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> @@ -56,7 +58,7 @@ <li><a class="dropdown-item" href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a></li> </ul> </li> -<li class="nav-item"><a class="nav-link" href="../coverage/coverage.html">Test coverage report</a></li> +<li class="nav-item"><a class="nav-link" href="../coverage/coverage.html">Test coverage</a></li> <li class="nav-item"><a class="nav-link" href="../news/index.html">News</a></li> </ul> <ul class="navbar-nav"> @@ -82,7 +84,7 @@ Ranke</h4> <h4 data-toc-skip class="date">Last change 18 May 2023 -(rebuilt 2024-07-29)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/mkin.rmd" class="external-link"><code>vignettes/mkin.rmd</code></a></small> <div class="d-none name"><code>mkin.rmd</code></div> @@ -397,7 +399,7 @@ Sensitivity and Monte Carlo Analysis in <span>R</span> Using Package </div> <div class="pkgdown-footer-right"> - 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fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Testing hierarchical pathway kinetics with residue data on cyantraniliprole</h1> + + <h1>Testing hierarchical pathway kinetics with residue data on cyantraniliprole</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 data-toc-skip class="date">Last change on 20 April 2023, -last compiled on 16 November 2023</h4> + <h4 data-toc-skip class="date">Last change on 13 February +2023, last compiled on 12 Mai 2025</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/prebuilt/2022_cyan_pathway.rmd" class="external-link"><code>vignettes/prebuilt/2022_cyan_pathway.rmd</code></a></small> <div class="d-none name"><code>2022_cyan_pathway.rmd</code></div> @@ -117,7 +103,7 @@ be fitted with the mkin package.</p> 173340 (Application of nonlinear hierarchical models to the kinetic evaluation of chemical degradation data) of the German Environment Agency carried out in 2022 and 2023.</p> -<p>The mkin package is used in version 1.2.6 which is currently under +<p>The mkin package is used in version 1.2.10 which is currently under development. The newly introduced functionality that is used here is a simplification of excluding random effects for a set of fits based on a related set of fits with a reduced model, and the documentation of the @@ -1600,10 +1586,58 @@ sd(f_JCZ38_qlogis)</td> </tr> </tbody> </table> -<p>The model comparison below suggests that the pathway fits using DFOP +<p>The model comparisons below suggest that the pathway fits using DFOP or SFORB for the parent compound provide the best fit.</p> <div class="sourceCode" id="cb15"><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_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</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_1</span><span class="op">[</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">npar</th> +<th align="right">AIC</th> +<th align="right">BIC</th> +<th align="right">Lik</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">sfo_path_1 const</td> +<td align="right">16</td> +<td align="right">2693.0</td> +<td align="right">2686.8</td> +<td align="right">-1330.5</td> +</tr> +<tr class="even"> +<td align="left">fomc_path_1 const</td> +<td align="right">18</td> +<td align="right">2427.9</td> +<td align="right">2420.9</td> +<td align="right">-1196.0</td> +</tr> +<tr class="odd"> +<td align="left">dfop_path_1 const</td> +<td align="right">20</td> +<td align="right">2403.2</td> +<td align="right">2395.4</td> +<td align="right">-1181.6</td> +</tr> +<tr class="even"> +<td align="left">sforb_path_1 const</td> +<td align="right">20</td> +<td align="right">2401.4</td> +<td align="right">2393.6</td> +<td align="right">-1180.7</td> +</tr> +<tr class="odd"> +<td align="left">hs_path_1 const</td> +<td align="right">20</td> +<td align="right">2427.2</td> +<td align="right">2419.4</td> +<td align="right">-1193.6</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb16"><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_1</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">4</span>, <span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> <th align="left"></th> @@ -1656,20 +1690,13 @@ or SFORB for the parent compound provide the best fit.</p> <td align="right">-1180.7</td> </tr> <tr class="odd"> -<td align="left">hs_path_1 const</td> -<td align="right">20</td> -<td align="right">2427.2</td> -<td align="right">2419.4</td> -<td align="right">-1193.6</td> -</tr> -<tr class="even"> <td align="left">dfop_path_1 tc</td> <td align="right">20</td> <td align="right">2398.0</td> <td align="right">2390.1</td> <td align="right">-1179.0</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">sforb_path_1 tc</td> <td align="right">20</td> <td align="right">2399.9</td> @@ -1680,14 +1707,14 @@ or SFORB for the parent compound provide the best fit.</p> </table> <p>For these two parent model, successful fits are shown below. Plots of the fits with the other parent models are shown in the Appendix.</p> -<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">[[</span><span class="st">"dfop_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-7-1.png" alt="DFOP pathway fit with two-component error" width="700"><p class="caption"> DFOP pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">[[</span><span class="st">"sforb_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-8-1.png" alt="SFORB pathway fit with two-component error" width="700"><p class="caption"> @@ -1697,7 +1724,7 @@ SFORB pathway fit with two-component error <p>A closer graphical analysis of these Figures shows that the residues of transformation product JCZ38 in the soils Tama and Nambsheim observed at later time points are strongly and systematically underestimated.</p> -<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> <code class="sourceCode R"><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_path_1</span><span class="op">)</span></span></code></pre></div> </div> <div class="section level3"> @@ -1711,7 +1738,7 @@ corresponding amide (Addendum 2014, p. 109). As FOMC provided the best fit for the parent, and the biexponential models DFOP and SFORB provided the best initial pathway fits, these three parent models are used in the alternative pathway fits.</p> -<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">cyan_path_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span> <span> fomc_path_2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span></span> <span> cyan <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</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="st">"JCZ38"</span>, <span class="st">"J9Z38"</span><span class="op">)</span><span class="op">)</span>,</span> @@ -1789,7 +1816,7 @@ alternative pathway fits.</p> </table> <p>Using constant variance, separate fits converge with the exception of the fits to the Sassafras soil data.</p> -<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">f_sep_2_tc</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_sep_2_const</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> <span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_2_tc</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <table class="table"> @@ -1831,11 +1858,11 @@ the fits to the Sassafras soil data.</p> <p>Using the two-component error model, all separate fits converge with the exception of the alternative pathway fit with DFOP used for the parent and the Sassafras dataset.</p> -<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">f_saem_2</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mhmkin.html">mhmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_sep_2_const</span>, <span class="va">f_sep_2_tc</span><span class="op">)</span>,</span> <span> no_random_effect <span class="op">=</span> <span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">cyan_saem_full</span><span class="op">[</span><span class="fl">2</span><span class="op">:</span><span class="fl">4</span>, <span class="op">]</span><span class="op">)</span>,</span> <span> cluster <span class="op">=</span> <span class="va">cl_path_2</span><span class="op">)</span></span></code></pre></div> -<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> @@ -1862,8 +1889,9 @@ parent and the Sassafras dataset.</p> </tbody> </table> <p>The hierarchical fits for the alternative pathway completed -successfully.</p> -<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> +successfully, with the exception of the model using FOMC for the parent +compound and constant variance as the error model.</p> +<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <table class="table"> <colgroup> @@ -1894,11 +1922,12 @@ successfully.</p> </tr> </tbody> </table> -<p>In both fits, the random effects for the formation fractions for the -pathways from JCZ38 to JSE76, and for the reverse pathway from JSE76 to -JCZ38 are ill-defined.</p> -<div class="sourceCode" id="cb24"><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_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<p>In all biphasic fits (DFOP or SFORB for the parent compound), the +random effects for the formation fractions for the pathways from JCZ38 +to JSE76, and for the reverse pathway from JSE76 to JCZ38 are +ill-defined.</p> +<div class="sourceCode" id="cb25"><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_2</span><span class="op">[</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> <th align="left"></th> @@ -1916,27 +1945,54 @@ JCZ38 are ill-defined.</p> <td align="right">-1103.5</td> </tr> <tr class="even"> +<td align="left">dfop_path_2 tc</td> +<td align="right">22</td> +<td align="right">2234.4</td> +<td align="right">2225.8</td> +<td align="right">-1095.2</td> +</tr> +<tr class="odd"> +<td align="left">sforb_path_2 tc</td> +<td align="right">22</td> +<td align="right">2239.7</td> +<td align="right">2231.1</td> +<td align="right">-1097.9</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb26"><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_2</span><span class="op">[</span><span class="fl">2</span><span class="op">:</span><span class="fl">3</span>,<span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">npar</th> +<th align="right">AIC</th> +<th align="right">BIC</th> +<th align="right">Lik</th> +</tr></thead> +<tbody> +<tr class="odd"> <td align="left">dfop_path_2 const</td> <td align="right">22</td> <td align="right">2288.4</td> <td align="right">2279.8</td> <td align="right">-1122.2</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">sforb_path_2 const</td> <td align="right">22</td> <td align="right">2283.3</td> <td align="right">2274.7</td> <td align="right">-1119.7</td> </tr> -<tr class="even"> +<tr class="odd"> <td align="left">dfop_path_2 tc</td> <td align="right">22</td> <td align="right">2234.4</td> <td align="right">2225.8</td> <td align="right">-1095.2</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">sforb_path_2 tc</td> <td align="right">22</td> <td align="right">2239.7</td> @@ -1951,21 +2007,21 @@ and BIC values and are plotted below. Compared with the original pathway, the AIC and BIC values indicate a large improvement. This is confirmed by the plots, which show that the metabolite JCZ38 is fitted much better with this model.</p> -<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">[[</span><span class="st">"fomc_path_2"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-13-1.png" alt="FOMC pathway fit with two-component error, alternative pathway" width="700"><p class="caption"> FOMC pathway fit with two-component error, alternative pathway </p> </div> -<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">[[</span><span class="st">"dfop_path_2"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-14-1.png" alt="DFOP pathway fit with two-component error, alternative pathway" width="700"><p class="caption"> DFOP pathway fit with two-component error, alternative pathway </p> </div> -<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">[[</span><span class="st">"sforb_path_2"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-15-1.png" alt="SFORB pathway fit with two-component error, alternative pathway" width="700"><p class="caption"> @@ -1983,7 +2039,7 @@ created below that can be indexed by row and column indices, and which contains the degradation parameter names for which random effects should be excluded for each of the hierarchical fits contained in <code>f_saem_2</code>.</p> -<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">no_ranef</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>, nrow <span class="op">=</span> <span class="fl">3</span>, ncol <span class="op">=</span> <span class="fl">2</span>, dimnames <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/dimnames.html" class="external-link">dimnames</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span><span class="op">)</span></span> <span><span class="va">no_ranef</span><span class="op">[[</span><span class="st">"fomc_path_2"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span> <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="st">"log_beta"</span>, <span class="st">"f_JCZ38_qlogis"</span>, <span class="st">"f_JSE76_qlogis"</span><span class="op">)</span></span> <span><span class="va">no_ranef</span><span class="op">[[</span><span class="st">"fomc_path_2"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span> <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="st">"cyan_0"</span>, <span class="st">"f_JCZ38_qlogis"</span>, <span class="st">"f_JSE76_qlogis"</span><span class="op">)</span></span> @@ -1998,7 +2054,7 @@ be excluded for each of the hierarchical fits contained in <span><span class="va">f_saem_3</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_2</span>,</span> <span> no_random_effect <span class="op">=</span> <span class="va">no_ranef</span>,</span> <span> cluster <span class="op">=</span> <span class="va">cl_path_2</span><span class="op">)</span></span></code></pre></div> -<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_3</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> @@ -2028,7 +2084,7 @@ be excluded for each of the hierarchical fits contained in all updated fits completed successfully. However, the Fisher Information Matrix for the fixed effects (Fth) could not be inverted, so no confidence intervals for the optimised parameters are available.</p> -<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_3</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> @@ -2054,8 +2110,8 @@ confidence intervals for the optimised parameters are available.</p> </tr> </tbody> </table> -<div class="sourceCode" id="cb31"><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_3</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb33"><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_3</span><span class="op">[</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> <th align="left"></th> @@ -2073,27 +2129,54 @@ confidence intervals for the optimised parameters are available.</p> <td align="right">-1105.5</td> </tr> <tr class="even"> +<td align="left">dfop_path_2 tc</td> +<td align="right">20</td> +<td align="right">2237.3</td> +<td align="right">2229.5</td> +<td align="right">-1098.6</td> +</tr> +<tr class="odd"> +<td align="left">sforb_path_2 tc</td> +<td align="right">20</td> +<td align="right">2241.3</td> +<td align="right">2233.5</td> +<td align="right">-1100.7</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb34"><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_3</span><span class="op">[</span><span class="fl">2</span><span class="op">:</span><span class="fl">3</span>,<span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">npar</th> +<th align="right">AIC</th> +<th align="right">BIC</th> +<th align="right">Lik</th> +</tr></thead> +<tbody> +<tr class="odd"> <td align="left">dfop_path_2 const</td> <td align="right">20</td> <td align="right">2282.2</td> <td align="right">2274.4</td> <td align="right">-1121.1</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">sforb_path_2 const</td> <td align="right">20</td> <td align="right">2279.7</td> <td align="right">2271.9</td> <td align="right">-1119.9</td> </tr> -<tr class="even"> +<tr class="odd"> <td align="left">dfop_path_2 tc</td> <td align="right">20</td> <td align="right">2237.3</td> <td align="right">2229.5</td> <td align="right">-1098.6</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">sforb_path_2 tc</td> <td align="right">20</td> <td align="right">2241.3</td> @@ -2106,7 +2189,7 @@ confidence intervals for the optimised parameters are available.</p> two-component error) are lower than in the previous fits with the alternative pathway, the practical value of these refined evaluations is limited as no confidence intervals are obtained.</p> -<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> <code class="sourceCode R"><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_path_2</span><span class="op">)</span></span></code></pre></div> </div> </div> @@ -2134,21 +2217,21 @@ Agency are gratefully acknowledged.</p> <div class="section level3"> <h3 id="plots-of-fits-that-were-not-refined-further">Plots of fits that were not refined further<a class="anchor" aria-label="anchor" href="#plots-of-fits-that-were-not-refined-further"></a> </h3> -<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">[[</span><span class="st">"sfo_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-20-1.png" alt="SFO pathway fit with two-component error" width="700"><p class="caption"> SFO pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">[[</span><span class="st">"fomc_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-21-1.png" alt="FOMC pathway fit with two-component error" width="700"><p class="caption"> FOMC pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">[[</span><span class="st">"sforb_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_cyan_pathway_files/figure-html/unnamed-chunk-22-1.png" alt="HS pathway fit with two-component error" width="700"><p class="caption"> @@ -2166,11 +2249,11 @@ HS pathway fit with two-component error Hierarchical SFO path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:27:41 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:35:03 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - k_cyan * cyan @@ -2183,7 +2266,7 @@ Data: Model predictions using solution type deSolve -Fitted in 421.347 s +Fitted in 445.08 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -2294,11 +2377,11 @@ JSE76 143.91 478.04 Hierarchical SFO path 1 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:27:55 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:34:47 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - k_cyan * cyan @@ -2311,7 +2394,7 @@ Data: Model predictions using solution type deSolve -Fitted in 435.122 s +Fitted in 428.46 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -2424,11 +2507,11 @@ JSE76 114.20 379.35 Hierarchical FOMC path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:28:33 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:35:21 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -2443,7 +2526,7 @@ Data: Model predictions using solution type deSolve -Fitted in 473.357 s +Fitted in 462.739 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -2569,11 +2652,11 @@ JSE76 318.86 1059.22 NA Hierarchical FOMC path 1 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:28:46 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:35:31 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -2588,7 +2671,7 @@ Data: Model predictions using solution type deSolve -Fitted in 486.031 s +Fitted in 472.067 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -2707,11 +2790,11 @@ JSE76 210.98 700.9 NA Hierarchical DFOP path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:29:15 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:36:02 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -2730,7 +2813,7 @@ Data: Model predictions using solution type deSolve -Fitted in 514.477 s +Fitted in 503.671 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -2853,11 +2936,11 @@ JSE76 200.41 665.76 NA NA NA Hierarchical DFOP path 1 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:31:58 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:38:54 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -2876,7 +2959,7 @@ Data: Model predictions using solution type deSolve -Fitted in 677.928 s +Fitted in 674.81 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -2999,11 +3082,11 @@ JSE76 179.30 595.62 NA NA NA Hierarchical SFORB path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:29:33 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:36:26 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -3021,7 +3104,7 @@ Data: Model predictions using solution type deSolve -Fitted in 532.937 s +Fitted in 527.639 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -3164,11 +3247,11 @@ JSE76 193.42 642.53 NA NA NA Hierarchical SFORB path 1 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:31:58 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:38:31 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -3186,7 +3269,7 @@ Data: Model predictions using solution type deSolve -Fitted in 677.936 s +Fitted in 651.67 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -3329,11 +3412,11 @@ JSE76 177.11 588.3 NA NA NA Hierarchical HS path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:29:18 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:36:13 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ifelse(time <= tb, k1, k2) * cyan @@ -3348,7 +3431,7 @@ Data: Model predictions using solution type deSolve -Fitted in 518.128 s +Fitted in 514.353 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -3475,11 +3558,11 @@ JSE76 187.01 621.23 NA NA NA Hierarchical FOMC path 2 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:40:28 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:47:30 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -3494,7 +3577,7 @@ Data: Model predictions using solution type deSolve -Fitted in 499.317 s +Fitted in 505.533 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -3543,28 +3626,28 @@ Likelihood computed by importance sampling 2249 2241 -1104 Optimised parameters: - est. lower upper -cyan_0 101.55265 9.920e+01 103.90593 -log_k_JCZ38 -2.32302 -2.832e+00 -1.81416 -log_k_J9Z38 -5.13082 -5.942e+00 -4.31990 -log_k_JSE76 -3.01756 -4.262e+00 -1.77360 -f_cyan_ilr_1 0.70850 3.657e-01 1.05135 -f_cyan_ilr_2 0.95775 2.612e-01 1.65432 -f_JCZ38_qlogis 3.86105 9.248e-01 6.79733 -f_JSE76_qlogis 7.51583 -1.120e+02 127.03921 -log_alpha -0.15308 -4.508e-01 0.14462 -log_beta 2.99165 2.711e+00 3.27202 -a.1 2.04034 1.811e+00 2.26968 -b.1 0.06924 5.745e-02 0.08104 -SD.log_k_JCZ38 0.50818 1.390e-01 0.87736 -SD.log_k_J9Z38 0.86597 2.652e-01 1.46671 -SD.log_k_JSE76 1.38092 4.864e-01 2.27541 -SD.f_cyan_ilr_1 0.38204 1.354e-01 0.62864 -SD.f_cyan_ilr_2 0.55129 7.198e-02 1.03060 -SD.f_JCZ38_qlogis 1.88457 1.710e-02 3.75205 -SD.f_JSE76_qlogis 2.64018 -2.450e+03 2455.27887 -SD.log_alpha 0.31860 1.047e-01 0.53249 -SD.log_beta 0.24195 1.273e-02 0.47117 + est. lower upper +cyan_0 101.55265 9.920e+01 103.9059 +log_k_JCZ38 -2.32302 -2.832e+00 -1.8142 +log_k_J9Z38 -5.13082 -5.942e+00 -4.3199 +log_k_JSE76 -3.01756 -4.262e+00 -1.7736 +f_cyan_ilr_1 0.70850 3.657e-01 1.0513 +f_cyan_ilr_2 0.95775 2.612e-01 1.6543 +f_JCZ38_qlogis 3.86105 9.248e-01 6.7973 +f_JSE76_qlogis 7.51583 -1.120e+02 127.0392 +log_alpha -0.15308 -4.508e-01 0.1446 +log_beta 2.99165 2.711e+00 3.2720 +a.1 2.04034 1.843e+00 2.2382 +b.1 0.06924 5.749e-02 0.0810 +SD.log_k_JCZ38 0.50818 1.390e-01 0.8774 +SD.log_k_J9Z38 0.86597 2.652e-01 1.4667 +SD.log_k_JSE76 1.38092 4.864e-01 2.2754 +SD.f_cyan_ilr_1 0.38204 1.354e-01 0.6286 +SD.f_cyan_ilr_2 0.55129 7.198e-02 1.0306 +SD.f_JCZ38_qlogis 1.88457 1.711e-02 3.7520 +SD.f_JSE76_qlogis 2.64018 -2.450e+03 2454.9447 +SD.log_alpha 0.31860 1.047e-01 0.5325 +SD.log_beta 0.24195 1.273e-02 0.4712 Correlation: cyan_0 l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76 @@ -3595,15 +3678,15 @@ SD.log_k_J9Z38 0.8660 2.652e-01 1.4667 SD.log_k_JSE76 1.3809 4.864e-01 2.2754 SD.f_cyan_ilr_1 0.3820 1.354e-01 0.6286 SD.f_cyan_ilr_2 0.5513 7.198e-02 1.0306 -SD.f_JCZ38_qlogis 1.8846 1.710e-02 3.7520 -SD.f_JSE76_qlogis 2.6402 -2.450e+03 2455.2789 +SD.f_JCZ38_qlogis 1.8846 1.711e-02 3.7520 +SD.f_JSE76_qlogis 2.6402 -2.450e+03 2454.9447 SD.log_alpha 0.3186 1.047e-01 0.5325 SD.log_beta 0.2420 1.273e-02 0.4712 Variance model: - est. lower upper -a.1 2.04034 1.81101 2.26968 -b.1 0.06924 0.05745 0.08104 + est. lower upper +a.1 2.04034 1.84252 2.238 +b.1 0.06924 0.05749 0.081 Backtransformed parameters: est. lower upper @@ -3641,11 +3724,11 @@ JSE76 14.169 47.07 NA Hierarchical DFOP path 2 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:41:25 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:48:20 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -3665,7 +3748,7 @@ Data: Model predictions using solution type deSolve -Fitted in 555.724 s +Fitted in 555.413 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -3832,11 +3915,11 @@ JSE76 24.32 80.78 NA NA NA Hierarchical DFOP path 2 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:44:08 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:51:02 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -3856,7 +3939,7 @@ Data: Model predictions using solution type deSolve -Fitted in 718.988 s +Fitted in 717.675 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -3933,15 +4016,15 @@ f_JSE76_qlogis 4.54884 -7.25628 16.35395 log_k1 -2.38201 -2.51639 -2.24763 log_k2 -4.66741 -4.91865 -4.41617 g_qlogis -0.28446 -1.14192 0.57300 -a.1 2.05925 1.83267 2.28582 -b.1 0.06172 0.05076 0.07268 +a.1 2.05925 1.86481 2.25369 +b.1 0.06172 0.05062 0.07282 SD.log_k_JCZ38 0.81137 0.25296 1.36977 -SD.log_k_J9Z38 0.83542 0.25396 1.41689 +SD.log_k_J9Z38 0.83542 0.25395 1.41689 SD.log_k_JSE76 0.97903 0.30100 1.65707 SD.f_cyan_ilr_1 0.37878 0.13374 0.62382 SD.f_cyan_ilr_2 0.67274 0.10102 1.24446 -SD.f_JCZ38_qlogis 1.35327 -0.42361 3.13015 -SD.f_JSE76_qlogis 1.43956 -19.15140 22.03052 +SD.f_JCZ38_qlogis 1.35327 -0.42359 3.13012 +SD.f_JSE76_qlogis 1.43956 -19.14972 22.02884 SD.log_k2 0.25329 0.07521 0.43138 SD.g_qlogis 0.95167 0.35149 1.55184 @@ -3972,19 +4055,19 @@ g_qlogis -0.1656 -0.0928 Random effects: est. lower upper SD.log_k_JCZ38 0.8114 0.25296 1.3698 -SD.log_k_J9Z38 0.8354 0.25396 1.4169 +SD.log_k_J9Z38 0.8354 0.25395 1.4169 SD.log_k_JSE76 0.9790 0.30100 1.6571 SD.f_cyan_ilr_1 0.3788 0.13374 0.6238 SD.f_cyan_ilr_2 0.6727 0.10102 1.2445 -SD.f_JCZ38_qlogis 1.3533 -0.42361 3.1301 -SD.f_JSE76_qlogis 1.4396 -19.15140 22.0305 +SD.f_JCZ38_qlogis 1.3533 -0.42359 3.1301 +SD.f_JSE76_qlogis 1.4396 -19.14972 22.0288 SD.log_k2 0.2533 0.07521 0.4314 SD.g_qlogis 0.9517 0.35149 1.5518 Variance model: est. lower upper -a.1 2.05925 1.83267 2.28582 -b.1 0.06172 0.05076 0.07268 +a.1 2.05925 1.86481 2.25369 +b.1 0.06172 0.05062 0.07282 Backtransformed parameters: est. lower upper @@ -4023,11 +4106,11 @@ JSE76 17.96 59.66 NA NA NA Hierarchical SFORB path 2 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:41:22 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:48:15 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -4045,7 +4128,7 @@ Data: Model predictions using solution type deSolve -Fitted in 553.276 s +Fitted in 550.772 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -4219,11 +4302,11 @@ JSE76 14.287 47.46 NA NA NA Hierarchical SFORB path 2 fit with two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:44:02 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 20:50:59 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -4241,7 +4324,7 @@ Data: Model predictions using solution type deSolve -Fitted in 713.14 s +Fitted in 714.48 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -4320,17 +4403,17 @@ f_cyan_ilr_1 0.70640 3.562e-01 1.057e+00 f_cyan_ilr_2 1.42704 3.170e-01 2.537e+00 f_JCZ38_qlogis 2.84779 1.042e+00 4.654e+00 f_JSE76_qlogis 8.63674 -6.407e+02 6.580e+02 -a.1 2.07082 1.846e+00 2.296e+00 -b.1 0.06227 5.120e-02 7.334e-02 +a.1 2.07082 1.877e+00 2.265e+00 +b.1 0.06227 5.098e-02 7.355e-02 SD.log_k_cyan_free 0.49674 1.865e-01 8.069e-01 -SD.log_k_cyan_bound_free 0.28537 6.808e-02 5.027e-01 +SD.log_k_cyan_bound_free 0.28537 6.809e-02 5.027e-01 SD.log_k_JCZ38 0.74846 2.305e-01 1.266e+00 SD.log_k_J9Z38 0.86077 2.713e-01 1.450e+00 SD.log_k_JSE76 0.97613 3.030e-01 1.649e+00 SD.f_cyan_ilr_1 0.38994 1.382e-01 6.417e-01 SD.f_cyan_ilr_2 0.82869 3.917e-02 1.618e+00 -SD.f_JCZ38_qlogis 1.05000 -2.809e-02 2.128e+00 -SD.f_JSE76_qlogis 0.44681 -3.986e+05 3.986e+05 +SD.f_JCZ38_qlogis 1.05000 -2.808e-02 2.128e+00 +SD.f_JSE76_qlogis 0.44681 -3.985e+05 3.985e+05 Correlation: cyn_f_0 lg_k_c_ lg_k_cyn_f_ lg_k_cyn_b_ l__JCZ3 l__J9Z3 @@ -4359,19 +4442,19 @@ f_JSE76_qlogis 0.0064 0.0345 0.2015 -0.7058 Random effects: est. lower upper SD.log_k_cyan_free 0.4967 1.865e-01 8.069e-01 -SD.log_k_cyan_bound_free 0.2854 6.808e-02 5.027e-01 +SD.log_k_cyan_bound_free 0.2854 6.809e-02 5.027e-01 SD.log_k_JCZ38 0.7485 2.305e-01 1.266e+00 SD.log_k_J9Z38 0.8608 2.713e-01 1.450e+00 SD.log_k_JSE76 0.9761 3.030e-01 1.649e+00 SD.f_cyan_ilr_1 0.3899 1.382e-01 6.417e-01 SD.f_cyan_ilr_2 0.8287 3.917e-02 1.618e+00 -SD.f_JCZ38_qlogis 1.0500 -2.809e-02 2.128e+00 -SD.f_JSE76_qlogis 0.4468 -3.986e+05 3.986e+05 +SD.f_JCZ38_qlogis 1.0500 -2.808e-02 2.128e+00 +SD.f_JSE76_qlogis 0.4468 -3.985e+05 3.985e+05 Variance model: - est. lower upper -a.1 2.07082 1.8458 2.29588 -b.1 0.06227 0.0512 0.07334 + est. lower upper +a.1 2.07082 1.87680 2.26483 +b.1 0.06227 0.05098 0.07355 Backtransformed parameters: est. lower upper @@ -4420,11 +4503,11 @@ Hierarchical FOMC path 2 fit with reduced random effects, two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:57:07 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:04:10 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -4439,7 +4522,7 @@ Data: Model predictions using solution type deSolve -Fitted in 776.732 s +Fitted in 786.038 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -4488,26 +4571,26 @@ Likelihood computed by importance sampling 2249 2242 -1106 Optimised parameters: - est. lower upper -cyan_0 101.24524 NA NA -log_k_JCZ38 -2.85375 NA NA -log_k_J9Z38 -5.07729 NA NA -log_k_JSE76 -3.53511 NA NA -f_cyan_ilr_1 0.67478 NA NA -f_cyan_ilr_2 0.97152 NA NA -f_JCZ38_qlogis 213.48001 NA NA -f_JSE76_qlogis 2.02040 NA NA -log_alpha -0.11041 NA NA -log_beta 3.06575 NA NA -a.1 2.05279 1.82393 2.28166 -b.1 0.07116 0.05910 0.08322 -SD.log_k_JCZ38 1.21713 0.44160 1.99266 -SD.log_k_J9Z38 0.88268 0.27541 1.48995 -SD.log_k_JSE76 0.59452 0.15005 1.03898 -SD.f_cyan_ilr_1 0.35370 0.12409 0.58331 -SD.f_cyan_ilr_2 0.78186 0.18547 1.37824 -SD.log_alpha 0.27781 0.08168 0.47394 -SD.log_beta 0.32608 0.06490 0.58726 + est. lower upper +cyan_0 101.24524 NA NA +log_k_JCZ38 -2.85375 NA NA +log_k_J9Z38 -5.07729 NA NA +log_k_JSE76 -3.53511 NA NA +f_cyan_ilr_1 0.67478 NA NA +f_cyan_ilr_2 0.97152 NA NA +f_JCZ38_qlogis 213.48001 NA NA +f_JSE76_qlogis 2.02040 NA NA +log_alpha -0.11041 NA NA +log_beta 3.06575 NA NA +a.1 2.05279 1.85495 2.2506 +b.1 0.07116 0.05912 0.0832 +SD.log_k_JCZ38 1.21713 0.44160 1.9927 +SD.log_k_J9Z38 0.88268 0.27541 1.4900 +SD.log_k_JSE76 0.59452 0.15005 1.0390 +SD.f_cyan_ilr_1 0.35370 0.12409 0.5833 +SD.f_cyan_ilr_2 0.78186 0.18547 1.3782 +SD.log_alpha 0.27781 0.08168 0.4739 +SD.log_beta 0.32608 0.06490 0.5873 Correlation is not available @@ -4522,9 +4605,9 @@ SD.log_alpha 0.2778 0.08168 0.4739 SD.log_beta 0.3261 0.06490 0.5873 Variance model: - est. lower upper -a.1 2.05279 1.8239 2.28166 -b.1 0.07116 0.0591 0.08322 + est. lower upper +a.1 2.05279 1.85495 2.2506 +b.1 0.07116 0.05912 0.0832 Backtransformed parameters: est. lower upper @@ -4563,11 +4646,11 @@ Hierarchical DFOP path 2 fit with reduced random effects, constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:58:51 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:05:56 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -4587,7 +4670,7 @@ Data: Model predictions using solution type deSolve -Fitted in 880.94 s +Fitted in 892.139 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -4729,11 +4812,11 @@ Hierarchical DFOP path 2 fit with reduced random effects, two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:58:58 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:02 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -4753,7 +4836,7 @@ Data: Model predictions using solution type deSolve -Fitted in 887.853 s +Fitted in 898.534 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -4830,13 +4913,13 @@ f_JSE76_qlogis 414.80884 NA NA log_k1 -2.38601 NA NA log_k2 -4.63632 NA NA g_qlogis -0.33920 NA NA -a.1 2.10837 1.88051 2.33623 -b.1 0.06223 0.05108 0.07338 +a.1 2.10837 1.91261 2.30413 +b.1 0.06223 0.05085 0.07361 SD.log_k_JCZ38 1.30902 0.48128 2.13675 SD.log_k_J9Z38 0.83882 0.25790 1.41974 SD.log_k_JSE76 0.58104 0.14201 1.02008 SD.f_cyan_ilr_1 0.35421 0.12398 0.58443 -SD.f_cyan_ilr_2 0.79373 0.12007 1.46740 +SD.f_cyan_ilr_2 0.79373 0.12007 1.46739 SD.log_k2 0.27476 0.08557 0.46394 SD.g_qlogis 0.96170 0.35463 1.56878 @@ -4854,8 +4937,8 @@ SD.g_qlogis 0.9617 0.35463 1.5688 Variance model: est. lower upper -a.1 2.10837 1.88051 2.33623 -b.1 0.06223 0.05108 0.07338 +a.1 2.10837 1.91261 2.30413 +b.1 0.06223 0.05085 0.07361 Backtransformed parameters: est. lower upper @@ -4895,11 +4978,11 @@ Hierarchical SFORB path 2 fit with reduced random effects, constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:58:49 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:05:52 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -4917,7 +5000,7 @@ Data: Model predictions using solution type deSolve -Fitted in 878.878 s +Fitted in 888.333 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -5066,11 +5149,11 @@ Hierarchical SFORB path 2 fit with reduced random effects, two-component error </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:10 2023 -Date of summary: Thu Nov 16 04:59:11 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:21 2025 +Date of summary: Mon May 12 21:06:22 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -5088,7 +5171,7 @@ Data: Model predictions using solution type deSolve -Fitted in 899.539 s +Fitted in 916.619 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -5167,8 +5250,8 @@ f_cyan_ilr_1 0.72263 NA NA f_cyan_ilr_2 1.45352 NA NA f_JCZ38_qlogis 2.00778 NA NA f_JSE76_qlogis 941.58570 NA NA -a.1 2.11130 1.88299 2.33960 -b.1 0.06299 0.05176 0.07421 +a.1 2.11130 1.91479 2.30780 +b.1 0.06299 0.05152 0.07445 SD.log_k_cyan_free 0.50098 0.18805 0.81390 SD.log_k_cyan_bound_free 0.31671 0.08467 0.54875 SD.log_k_JCZ38 1.25865 0.45932 2.05798 @@ -5182,7 +5265,7 @@ Correlation is not available Random effects: est. lower upper SD.log_k_cyan_free 0.5010 0.18805 0.8139 -SD.log_k_cyan_bound_free 0.3167 0.08467 0.5488 +SD.log_k_cyan_bound_free 0.3167 0.08467 0.5487 SD.log_k_JCZ38 1.2587 0.45932 2.0580 SD.log_k_J9Z38 0.8683 0.27222 1.4644 SD.log_k_JSE76 0.5933 0.14711 1.0394 @@ -5191,8 +5274,8 @@ SD.f_cyan_ilr_2 0.8854 0.13797 1.6329 Variance model: est. lower upper -a.1 2.11130 1.88299 2.33960 -b.1 0.06299 0.05176 0.07421 +a.1 2.11130 1.91479 2.30780 +b.1 0.06299 0.05152 0.07445 Backtransformed parameters: est. lower upper @@ -5237,13 +5320,13 @@ JSE76 25.44 84.51 NA NA NA <div class="section level3"> <h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> </h3> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -5261,56 +5344,52 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.6 +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 cellranger_1.1.0 rprojroot_2.0.3 -[13] jsonlite_1.8.4 processx_3.8.1 pkgbuild_1.4.0 deSolve_1.35 -[17] DBI_1.1.3 mclust_6.0.0 ps_1.7.5 gridExtra_2.3 -[21] purrr_1.0.1 fansi_1.0.4 scales_1.2.1 codetools_0.2-19 -[25] textshaping_0.3.6 jquerylib_0.1.4 cli_3.6.1 crayon_1.5.2 -[29] rlang_1.1.1 munsell_0.5.0 cachem_1.0.8 yaml_2.3.7 -[33] inline_0.3.19 tools_4.3.2 memoise_2.0.1 dplyr_1.1.2 -[37] colorspace_2.1-0 ggplot2_3.4.2 vctrs_0.6.2 R6_2.5.1 -[41] zoo_1.8-12 lifecycle_1.0.3 stringr_1.5.0 fs_1.6.2 -[45] MASS_7.3-60 ragg_1.2.5 callr_3.7.3 pkgconfig_2.0.3 -[49] desc_1.4.2 pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 -[53] gtable_0.3.3 glue_1.6.2 systemfonts_1.0.4 highr_0.10 -[57] xfun_0.39 tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 -[61] htmltools_0.5.5 nlme_3.1-163 rmarkdown_2.21 compiler_4.3.2 -[65] prettyunits_1.1.1 readxl_1.4.2 </code></pre> + [1] sass_0.4.9 generics_0.1.3 lattice_0.22-6 digest_0.6.37 + [5] magrittr_2.0.3 evaluate_1.0.3 grid_4.5.0 fastmap_1.2.0 + [9] cellranger_1.1.0 jsonlite_1.9.0 processx_3.8.6 pkgbuild_1.4.6 +[13] deSolve_1.40 mclust_6.1.1 ps_1.9.0 gridExtra_2.3 +[17] scales_1.3.0 codetools_0.2-20 textshaping_1.0.0 jquerylib_0.1.4 +[21] cli_3.6.4 rlang_1.1.5 munsell_0.5.1 cachem_1.1.0 +[25] yaml_2.3.10 inline_0.3.21 tools_4.5.0 dplyr_1.1.4 +[29] colorspace_2.1-1 ggplot2_3.5.1 vctrs_0.6.5 R6_2.6.1 +[33] zoo_1.8-13 lifecycle_1.0.4 fs_1.6.5 htmlwidgets_1.6.4 +[37] MASS_7.3-65 ragg_1.3.3 pkgconfig_2.0.3 desc_1.4.3 +[41] callr_3.7.6 pkgdown_2.1.1 pillar_1.10.1 bslib_0.9.0 +[45] gtable_0.3.6 glue_1.8.0 systemfonts_1.2.1 xfun_0.51 +[49] tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.1 htmltools_0.5.8.1 +[53] nlme_3.1-168 compiler_4.5.0 readxl_1.4.4 </code></pre> </div> <div class="section level3"> <h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> </h3> <pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> -<pre><code>MemTotal: 64927712 kB</code></pre> +<pre><code>MemTotal: 64927780 kB</code></pre> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/prebuilt/2022_cyan_pathway_files/figure-html/unnamed-chunk-13-1.png b/docs/articles/prebuilt/2022_cyan_pathway_files/figure-html/unnamed-chunk-13-1.png Binary files differindex b3d6066b..d2201974 100644 --- a/docs/articles/prebuilt/2022_cyan_pathway_files/figure-html/unnamed-chunk-13-1.png +++ 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href="../../articles/prebuilt/2022_dmta_parent.html">Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/multistart.html">Short demo of the multistart 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href="../../coverage/coverage.html">Test coverage</a></li> +<li class="nav-item"><a class="nav-link" href="../../news/index.html">News</a></li> </ul> -<form class="form-inline my-2 my-lg-0" role="search"> - <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../../search.json" id="search-input" placeholder="Search for" autocomplete="off"> -</form> - - <ul class="navbar-nav"> -<li class="nav-item"> - <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github"> - <span class="fab fa fab fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</h1> + + <h1>Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change on 5 January -2023, last compiled on 16 November 2023</h4> +2023, last compiled on 12 Mai 2025</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/prebuilt/2022_dmta_parent.rmd" class="external-link"><code>vignettes/prebuilt/2022_dmta_parent.rmd</code></a></small> <div class="d-none name"><code>2022_dmta_parent.rmd</code></div> @@ -116,7 +102,7 @@ FOMC, DFOP and HS can be fitted with the mkin package.</p> 173340 (Application of nonlinear hierarchical models to the kinetic evaluation of chemical degradation data) of the German Environment Agency carried out in 2022 and 2023.</p> -<p>The mkin package is used in version 1.2.6. It contains the test data +<p>The mkin package is used in version 1.2.10. It contains the test data and the functions used in the evaluations. The <code>saemix</code> package is used as a backend for fitting the NLHM, but is also loaded to make the convergence plot function available.</p> @@ -1247,11 +1233,11 @@ Plot of the final NLHM DFOP fit <p>Finally, a summary report of the fit is produced.</p> <div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_tc_no_ranef_k2</span><span class="op">)</span></span></code></pre></div> -<pre><code>saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:35 2023 -Date of summary: Thu Nov 16 04:59:35 2023 +<pre><code>saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:46 2025 +Date of summary: Mon May 12 21:06:46 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1263,7 +1249,7 @@ Data: Model predictions using solution type analytical -Fitted in 4.4 s +Fitted in 3.953 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1298,11 +1284,11 @@ DMTA_0 98.256267 96.286112 100.22642 k1 0.064037 0.033281 0.09479 k2 0.008469 0.006002 0.01094 g 0.954167 0.914460 0.99387 -a.1 1.061795 0.863943 1.25965 -b.1 0.029550 0.022529 0.03657 -SD.DMTA_0 2.068581 0.427706 3.70946 +a.1 1.061795 0.878608 1.24498 +b.1 0.029550 0.022593 0.03651 +SD.DMTA_0 2.068581 0.427178 3.70998 SD.k1 0.598285 0.258235 0.93833 -SD.g 1.016689 0.360057 1.67332 +SD.g 1.016689 0.360061 1.67332 Correlation: DMTA_0 k1 k2 @@ -1312,14 +1298,14 @@ g -0.0521 -0.0286 -0.2744 Random effects: est. lower upper -SD.DMTA_0 2.0686 0.4277 3.7095 +SD.DMTA_0 2.0686 0.4272 3.7100 SD.k1 0.5983 0.2582 0.9383 SD.g 1.0167 0.3601 1.6733 Variance model: est. lower upper -a.1 1.06180 0.86394 1.25965 -b.1 0.02955 0.02253 0.03657 +a.1 1.06180 0.87861 1.24498 +b.1 0.02955 0.02259 0.03651 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -1423,11 +1409,11 @@ Erythropoiesis.”</span> <em>BMC Bioinformatics</em> 22 (478). <a href="https:/ Hierarchical mkin fit of the SFO model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:26 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:38 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1437,7 +1423,7 @@ Data: Model predictions using solution type analytical -Fitted in 0.788 s +Fitted in 0.793 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1495,11 +1481,11 @@ DMTA 12.24 40.65 Hierarchical mkin fit of the SFO model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:40 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1509,7 +1495,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.428 s +Fitted in 2.462 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1537,13 +1523,13 @@ Likelihood computed by importance sampling 798.3 797.1 -393.2 Optimised parameters: - est. lower upper -DMTA_0 97.271822 95.703157 98.84049 -k_DMTA 0.056638 0.029110 0.08417 -a.1 2.660081 2.230398 3.08976 -b.1 0.001665 -0.006911 0.01024 -SD.DMTA_0 1.545520 0.145035 2.94601 -SD.k_DMTA 0.606422 0.262274 0.95057 + est. lower upper +DMTA_0 97.271822 95.70316 98.84049 +k_DMTA 0.056638 0.02911 0.08417 +a.1 2.660081 2.27492 3.04525 +b.1 0.001665 -0.14451 0.14784 +SD.DMTA_0 1.545520 0.14301 2.94803 +SD.k_DMTA 0.606422 0.26227 0.95057 Correlation: DMTA_0 @@ -1551,13 +1537,13 @@ k_DMTA 0.0169 Random effects: est. lower upper -SD.DMTA_0 1.5455 0.1450 2.9460 +SD.DMTA_0 1.5455 0.1430 2.9480 SD.k_DMTA 0.6064 0.2623 0.9506 Variance model: - est. lower upper -a.1 2.660081 2.230398 3.08976 -b.1 0.001665 -0.006911 0.01024 + est. lower upper +a.1 2.660081 2.2749 3.0452 +b.1 0.001665 -0.1445 0.1478 Estimated disappearance times: DT50 DT90 @@ -1569,11 +1555,11 @@ DMTA 12.24 40.65 Hierarchical mkin fit of the FOMC model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:27 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1583,7 +1569,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.28 s +Fitted in 1.408 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1646,11 +1632,11 @@ DMTA 11.41 42.53 12.8 Hierarchical mkin fit of the FOMC model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:40 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1660,7 +1646,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.793 s +Fitted in 2.735 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1693,11 +1679,11 @@ Optimised parameters: DMTA_0 99.10577 97.33296 100.87859 alpha 5.46260 2.52199 8.40321 beta 81.66080 30.46664 132.85497 -a.1 1.50219 1.23601 1.76836 -b.1 0.02893 0.02099 0.03687 -SD.DMTA_0 1.61887 -0.03636 3.27411 +a.1 1.50219 1.25801 1.74636 +b.1 0.02893 0.02048 0.03739 +SD.DMTA_0 1.61887 -0.03843 3.27618 SD.alpha 0.58145 0.17364 0.98925 -SD.beta 0.68205 0.21108 1.15303 +SD.beta 0.68205 0.21108 1.15302 Correlation: DMTA_0 alpha @@ -1706,14 +1692,14 @@ beta -0.1430 0.2467 Random effects: est. lower upper -SD.DMTA_0 1.6189 -0.03636 3.2741 +SD.DMTA_0 1.6189 -0.03843 3.2762 SD.alpha 0.5814 0.17364 0.9892 SD.beta 0.6821 0.21108 1.1530 Variance model: est. lower upper -a.1 1.50219 1.23601 1.76836 -b.1 0.02893 0.02099 0.03687 +a.1 1.50219 1.25801 1.74636 +b.1 0.02893 0.02048 0.03739 Estimated disappearance times: DT50 DT90 DT50back @@ -1725,11 +1711,11 @@ DMTA 11.05 42.81 12.89 Hierarchical mkin fit of the DFOP model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:27 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1741,7 +1727,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.752 s +Fitted in 1.769 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1809,11 +1795,11 @@ DMTA 11.79 42.8 12.88 11.09 76.46 Hierarchical mkin fit of the DFOP model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:29 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:41 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1825,7 +1811,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.186 s +Fitted in 3.069 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1860,12 +1846,12 @@ DMTA_0 98.347470 96.380815 100.31413 k1 0.064524 0.034279 0.09477 k2 0.008304 0.005843 0.01076 g 0.952128 0.909578 0.99468 -a.1 1.068907 0.868694 1.26912 -b.1 0.029265 0.022262 0.03627 -SD.DMTA_0 2.065796 0.428485 3.70311 +a.1 1.068907 0.883665 1.25415 +b.1 0.029265 0.022318 0.03621 +SD.DMTA_0 2.065796 0.427951 3.70364 SD.k1 0.583703 0.251796 0.91561 -SD.k2 0.004167 -7.832168 7.84050 -SD.g 1.064450 0.397476 1.73142 +SD.k2 0.004167 -7.831228 7.83956 +SD.g 1.064450 0.397479 1.73142 Correlation: DMTA_0 k1 k2 @@ -1875,15 +1861,15 @@ g -0.0464 -0.0269 -0.2713 Random effects: est. lower upper -SD.DMTA_0 2.065796 0.4285 3.7031 +SD.DMTA_0 2.065796 0.4280 3.7036 SD.k1 0.583703 0.2518 0.9156 -SD.k2 0.004167 -7.8322 7.8405 +SD.k2 0.004167 -7.8312 7.8396 SD.g 1.064450 0.3975 1.7314 Variance model: est. lower upper -a.1 1.06891 0.86869 1.26912 -b.1 0.02927 0.02226 0.03627 +a.1 1.06891 0.88367 1.25415 +b.1 0.02927 0.02232 0.03621 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -1895,11 +1881,11 @@ DMTA 11.39 41.36 12.45 10.74 83.48 Hierarchical mkin fit of the HS model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -1909,7 +1895,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.28 s +Fitted in 1.996 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1977,11 +1963,11 @@ DMTA 8.801 67.91 20.44 8.801 31.13 Hierarchical mkin fit of the HS model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:29 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:41 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -1991,7 +1977,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.658 s +Fitted in 3.389 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -2026,12 +2012,12 @@ DMTA_0 97.76571 95.81350 99.71791 k1 0.05855 0.03080 0.08630 k2 0.02337 0.01664 0.03010 tb 31.09638 29.38289 32.80987 -a.1 1.08835 0.88590 1.29080 -b.1 0.02964 0.02257 0.03671 -SD.DMTA_0 2.04877 0.42607 3.67147 +a.1 1.08835 0.90059 1.27611 +b.1 0.02964 0.02261 0.03667 +SD.DMTA_0 2.04877 0.42553 3.67200 SD.k1 0.59166 0.25621 0.92711 SD.k2 0.30698 0.09561 0.51835 -SD.tb 0.01274 -0.10914 0.13462 +SD.tb 0.01274 -0.10915 0.13464 Correlation: DMTA_0 k1 k2 @@ -2041,15 +2027,15 @@ tb -0.0668 -0.0103 -0.2013 Random effects: est. lower upper -SD.DMTA_0 2.04877 0.42607 3.6715 +SD.DMTA_0 2.04877 0.42553 3.6720 SD.k1 0.59166 0.25621 0.9271 SD.k2 0.30698 0.09561 0.5183 -SD.tb 0.01274 -0.10914 0.1346 +SD.tb 0.01274 -0.10915 0.1346 Variance model: est. lower upper -a.1 1.08835 0.88590 1.29080 -b.1 0.02964 0.02257 0.03671 +a.1 1.08835 0.90059 1.27611 +b.1 0.02964 0.02261 0.03667 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -2105,13 +2091,13 @@ Convergence plot for the NLHM HS fit with two-component error <div class="section level3"> <h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> </h3> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -2129,53 +2115,50 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.6 +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.4 -[13] DBI_1.1.3 mclust_6.0.0 gridExtra_2.3 purrr_1.0.1 -[17] fansi_1.0.4 scales_1.2.1 codetools_0.2-19 textshaping_0.3.6 -[21] jquerylib_0.1.4 cli_3.6.1 rlang_1.1.1 munsell_0.5.0 -[25] cachem_1.0.8 yaml_2.3.7 tools_4.3.2 memoise_2.0.1 -[29] dplyr_1.1.2 colorspace_2.1-0 ggplot2_3.4.2 vctrs_0.6.2 -[33] R6_2.5.1 zoo_1.8-12 lifecycle_1.0.3 stringr_1.5.0 -[37] fs_1.6.2 MASS_7.3-60 ragg_1.2.5 pkgconfig_2.0.3 -[41] desc_1.4.2 pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 -[45] gtable_0.3.3 glue_1.6.2 systemfonts_1.0.4 highr_0.10 -[49] xfun_0.39 tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 -[53] htmltools_0.5.5 nlme_3.1-163 rmarkdown_2.21 compiler_4.3.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.2.1 + [9] scales_1.3.0 textshaping_1.0.0 yaml_2.3.10 fastmap_1.2.0 +[13] lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 generics_0.1.3 +[17] lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 tibble_3.2.1 +[21] desc_1.4.3 munsell_0.5.1 bslib_0.9.0 pillar_1.10.1 +[25] rlang_1.1.5 cachem_1.1.0 xfun_0.51 fs_1.6.5 +[29] sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 magrittr_2.0.3 +[33] digest_0.6.37 grid_4.5.0 mclust_6.1.1 lifecycle_1.0.4 +[37] nlme_3.1-168 vctrs_0.6.5 evaluate_1.0.3 glue_1.8.0 +[41] codetools_0.2-20 ragg_1.3.3 zoo_1.8-13 colorspace_2.1-1 +[45] tools_4.5.0 pkgconfig_2.0.3 htmltools_0.5.8.1</code></pre> </div> <div class="section level3"> <h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> </h3> <pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> -<pre><code>MemTotal: 64927712 kB</code></pre> +<pre><code>MemTotal: 64927780 kB</code></pre> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/prebuilt/2022_dmta_parent_files/figure-html/convergence-saem-dfop-const-1.png b/docs/articles/prebuilt/2022_dmta_parent_files/figure-html/convergence-saem-dfop-const-1.png 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role="search"> - <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../../search.json" id="search-input" placeholder="Search for" autocomplete="off"> -</form> - - <ul class="navbar-nav"> -<li class="nav-item"> - <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github"> - <span class="fab fa fab fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</h1> + + <h1>Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change on 20 April 2023, -last compiled on 16 November 2023</h4> +last compiled on 12 Mai 2025</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/prebuilt/2022_dmta_pathway.rmd" class="external-link"><code>vignettes/prebuilt/2022_dmta_pathway.rmd</code></a></small> <div class="d-none name"><code>2022_dmta_pathway.rmd</code></div> @@ -117,7 +103,7 @@ can be fitted with the mkin package.</p> 173340 (Application of nonlinear hierarchical models to the kinetic evaluation of chemical degradation data) of the German Environment Agency carried out in 2022 and 2023.</p> -<p>The mkin package is used in version 1.2.6, which is currently under +<p>The mkin package is used in version 1.2.10, which is currently under development. It contains the test data, and the functions used in the evaluations. The <code>saemix</code> package is used as a backend for fitting the NLHM, but is also loaded to make the convergence plot @@ -1809,7 +1795,9 @@ performed on the basis of the refined fit shown above.</p> <div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">saem_sforb_path_1_tc_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">saem_sforb_path_1_tc_reduced</span>,</span> <span> n <span class="op">=</span> <span class="fl">32</span>, cores <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></span></code></pre></div> -<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> +<pre><code> + (subscript) logical subscript too long</code></pre> +<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">saem_sforb_path_1_tc_reduced_multi</span><span class="op">)</span></span></code></pre></div> <pre><code><multistart> object with 32 fits: E OK @@ -1823,7 +1811,7 @@ the SAEM algorithm leads to parameter combinations for the degradation model that the numerical integration routine cannot cope with. Because of this variation of initial parameters, some of the model fits take up to two times more time than the original fit.</p> -<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/graphics/par.html" class="external-link">par</a></span><span class="op">(</span>mar <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">12.1</span>, <span class="fl">4.1</span>, <span class="fl">2.1</span>, <span class="fl">2.1</span><span class="op">)</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">saem_sforb_path_1_tc_reduced_multi</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>, las <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> @@ -1842,14 +1830,14 @@ ill-defined parameters.</p> </h2> <p>The SFORB pathway fits with full and reduced parameter distribution model are shown below.</p> -<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">saem_1</span><span class="op">[[</span><span class="st">"sforb_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_dmta_pathway_files/figure-html/unnamed-chunk-3-1.png" alt="SFORB pathway fit with two-component error" width="700"><p class="caption"> SFORB pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">saem_sforb_path_1_tc_reduced</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_dmta_pathway_files/figure-html/unnamed-chunk-4-1.png" alt="SFORB pathway fit with two-component error, reduced parameter model" width="700"><p class="caption"> @@ -1858,7 +1846,7 @@ SFORB pathway fit with two-component error, reduced parameter model </div> <p>Plots of the remaining fits and listings for all successful fits are shown in the Appendix.</p> -<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> <code class="sourceCode R"><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></code></pre></div> </div> <div class="section level2"> @@ -1898,21 +1886,21 @@ Level with Nonlinear Mixed-Effects Models.”</span> <em>Environments</em> <div class="section level3"> <h3 id="plots-of-hierarchical-fits-not-selected-for-refinement">Plots of hierarchical fits not selected for refinement<a class="anchor" aria-label="anchor" href="#plots-of-hierarchical-fits-not-selected-for-refinement"></a> </h3> -<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">saem_1</span><span class="op">[[</span><span class="st">"sfo_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_dmta_pathway_files/figure-html/unnamed-chunk-6-1.png" alt="SFO pathway fit with two-component error" width="700"><p class="caption"> SFO pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">saem_1</span><span class="op">[[</span><span class="st">"fomc_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_dmta_pathway_files/figure-html/unnamed-chunk-7-1.png" alt="FOMC pathway fit with two-component error" width="700"><p class="caption"> FOMC pathway fit with two-component error </p> </div> -<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">saem_1</span><span class="op">[[</span><span class="st">"sforb_path_1"</span>, <span class="st">"tc"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <div class="figure" style="text-align: center"> <img src="2022_dmta_pathway_files/figure-html/unnamed-chunk-8-1.png" alt="HS pathway fit with two-component error" width="700"><p class="caption"> @@ -1938,13 +1926,13 @@ error<a class="anchor" aria-label="anchor" href="#improved-fit-of-the-sforb-path <div class="section level3"> <h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> </h3> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -1962,55 +1950,52 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.6 +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.4 -[13] processx_3.8.1 pkgbuild_1.4.0 deSolve_1.35 DBI_1.1.3 -[17] mclust_6.0.0 ps_1.7.5 gridExtra_2.3 purrr_1.0.1 -[21] fansi_1.0.4 scales_1.2.1 codetools_0.2-19 textshaping_0.3.6 -[25] jquerylib_0.1.4 cli_3.6.1 crayon_1.5.2 rlang_1.1.1 -[29] munsell_0.5.0 cachem_1.0.8 yaml_2.3.7 inline_0.3.19 -[33] tools_4.3.2 memoise_2.0.1 dplyr_1.1.2 colorspace_2.1-0 -[37] ggplot2_3.4.2 vctrs_0.6.2 R6_2.5.1 zoo_1.8-12 -[41] lifecycle_1.0.3 stringr_1.5.0 fs_1.6.2 MASS_7.3-60 -[45] ragg_1.2.5 callr_3.7.3 pkgconfig_2.0.3 desc_1.4.2 -[49] pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 gtable_0.3.3 -[53] glue_1.6.2 systemfonts_1.0.4 highr_0.10 xfun_0.39 -[57] tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 htmltools_0.5.5 -[61] nlme_3.1-163 rmarkdown_2.21 compiler_4.3.2 prettyunits_1.1.1</code></pre> + [1] sass_0.4.9 generics_0.1.3 lattice_0.22-6 digest_0.6.37 + [5] magrittr_2.0.3 evaluate_1.0.3 grid_4.5.0 fastmap_1.2.0 + [9] jsonlite_1.9.0 processx_3.8.6 pkgbuild_1.4.6 deSolve_1.40 +[13] mclust_6.1.1 ps_1.9.0 gridExtra_2.3 scales_1.3.0 +[17] codetools_0.2-20 textshaping_1.0.0 jquerylib_0.1.4 cli_3.6.4 +[21] rlang_1.1.5 munsell_0.5.1 cachem_1.1.0 yaml_2.3.10 +[25] tools_4.5.0 inline_0.3.21 dplyr_1.1.4 colorspace_2.1-1 +[29] ggplot2_3.5.1 vctrs_0.6.5 R6_2.6.1 zoo_1.8-13 +[33] lifecycle_1.0.4 fs_1.6.5 htmlwidgets_1.6.4 MASS_7.3-65 +[37] ragg_1.3.3 pkgconfig_2.0.3 desc_1.4.3 callr_3.7.6 +[41] pkgdown_2.1.1 pillar_1.10.1 bslib_0.9.0 gtable_0.3.6 +[45] glue_1.8.0 systemfonts_1.2.1 xfun_0.51 tibble_3.2.1 +[49] lmtest_0.9-40 tidyselect_1.2.1 htmltools_0.5.8.1 nlme_3.1-168 +[53] compiler_4.5.0 </code></pre> </div> <div class="section level3"> <h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> </h3> <pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> -<pre><code>MemTotal: 64927712 kB</code></pre> +<pre><code>MemTotal: 64927780 kB</code></pre> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/prebuilt/2022_dmta_pathway_files/figure-html/saem-sforb-path-1-tc-reduced-convergence-1.png 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class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</h1> + + <h1>Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change on 4 August 2023, -last compiled on 16 November 2023</h4> +last compiled on 12 Mai 2025</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/prebuilt/2023_mesotrione_parent.rmd" class="external-link"><code>vignettes/prebuilt/2023_mesotrione_parent.rmd</code></a></small> <div class="d-none name"><code>2023_mesotrione_parent.rmd</code></div> @@ -117,7 +103,7 @@ parameters. Because in some other case studies, the SFORB parameterisation of biexponential decline has shown some advantages over the DFOP parameterisation, SFORB was included in the list of tested models as well.</p> -<p>The mkin package is used in version 1.2.6, which is contains the +<p>The mkin package is used in version 1.2.10, which is contains the functions that were used for the evaluations. The <code>saemix</code> package is used as a backend for fitting the NLHM, but is also loaded to make the convergence plot function available.</p> @@ -1479,7 +1465,7 @@ according to the <code>illparms</code> function.</p> <tr class="odd"> <td align="left">HS</td> <td align="left"></td> -<td align="left"></td> +<td align="left">b.1</td> </tr> </tbody> </table> @@ -2439,13 +2425,13 @@ further refined to make them fully identifiable.</p> <div class="section level3"> <h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> </h3> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -2463,53 +2449,51 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.6 +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.4 -[13] DBI_1.1.3 mclust_6.0.0 gridExtra_2.3 purrr_1.0.1 -[17] fansi_1.0.4 scales_1.2.1 textshaping_0.3.6 jquerylib_0.1.4 -[21] cli_3.6.1 rlang_1.1.1 munsell_0.5.0 cachem_1.0.8 -[25] yaml_2.3.7 tools_4.3.2 memoise_2.0.1 dplyr_1.1.2 -[29] colorspace_2.1-0 ggplot2_3.4.2 vctrs_0.6.2 R6_2.5.1 -[33] zoo_1.8-12 lifecycle_1.0.3 stringr_1.5.0 fs_1.6.2 -[37] MASS_7.3-60 ragg_1.2.5 pkgconfig_2.0.3 desc_1.4.2 -[41] pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 gtable_0.3.3 -[45] glue_1.6.2 systemfonts_1.0.4 xfun_0.39 tibble_3.2.1 -[49] lmtest_0.9-40 tidyselect_1.2.0 htmltools_0.5.5 nlme_3.1-163 -[53] rmarkdown_2.21 compiler_4.3.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.2.1 + [9] scales_1.3.0 textshaping_1.0.0 readxl_1.4.4 yaml_2.3.10 +[13] fastmap_1.2.0 lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 +[17] generics_0.1.3 lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 +[21] tibble_3.2.1 desc_1.4.3 munsell_0.5.1 bslib_0.9.0 +[25] pillar_1.10.1 rlang_1.1.5 cachem_1.1.0 xfun_0.51 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.5.0 mclust_6.1.1 +[37] lifecycle_1.0.4 nlme_3.1-168 vctrs_0.6.5 evaluate_1.0.3 +[41] glue_1.8.0 cellranger_1.1.0 codetools_0.2-20 ragg_1.3.3 +[45] zoo_1.8-13 colorspace_2.1-1 tools_4.5.0 pkgconfig_2.0.3 +[49] htmltools_0.5.8.1</code></pre> </div> <div class="section level3"> <h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> </h3> <pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> -<pre><code>MemTotal: 64928100 kB</code></pre> +<pre><code>MemTotal: 64927780 kB</code></pre> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-14-1.png 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id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Calculation of time weighted average concentrations with mkin</h1> + + <h1>Calculation of time weighted average concentrations with mkin</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 18 September 2019 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/twa.rmd" class="external-link"><code>vignettes/twa.rmd</code></a></small> <div class="d-none name"><code>twa.rmd</code></div> @@ -118,48 +104,44 @@ model are calculated using the formulas given in the FOCUS kinetics guidance <span class="citation">(FOCUS Work Group on Degradation Kinetics 2014, 251)</span>:</p> <p>SFO:</p> -<p><span class="math display">\[c_\textrm{twa} = c_0 \frac{\left( 1 - -e^{- k t} \right)}{ k t} \]</span></p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><msub><mi>c</mi><mn>0</mn></msub><mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><mi>k</mi><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mi>k</mi><mi>t</mi></mrow></mfrac></mrow><annotation encoding="application/x-tex">c_\textrm{twa} = c_0 \frac{\left( 1 - e^{- k t} \right)}{ k t} </annotation></semantics></math></p> <p>FOMC:</p> -<p><span class="math display">\[c_\textrm{twa} = c_0 \frac{\beta}{t (1 - -\alpha)} - \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha} -- 1 \right) \]</span></p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><msub><mi>c</mi><mn>0</mn></msub><mfrac><mi>β</mi><mrow><mi>t</mi><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><mi>α</mi><mo stretchy="true" form="postfix">)</mo></mrow></mrow></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><msup><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mi>t</mi><mi>β</mi></mfrac><mo>+</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mn>1</mn><mo>−</mo><mi>α</mi></mrow></msup><mo>−</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">c_\textrm{twa} = c_0 \frac{\beta}{t (1 - \alpha)} + \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha} - 1 \right) </annotation></semantics></math></p> <p>DFOP:</p> -<p><span class="math display">\[c_\textrm{twa} = \frac{c_0}{t} \left( +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><msub><mi>c</mi><mn>0</mn></msub><mi>t</mi></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mi>g</mi><msub><mi>k</mi><mn>1</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mfrac><mrow><mn>1</mn><mo>−</mo><mi>g</mi></mrow><msub><mi>k</mi><mn>2</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>2</mn></msub><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">c_\textrm{twa} = \frac{c_0}{t} \left( \frac{g}{k_1} \left( 1 - e^{- k_1 t} \right) + - \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right) \right) \]</span></p> -<p>HS for <span class="math inline">\(t > t_b\)</span>:</p> -<p><span class="math display">\[c_\textrm{twa} = \frac{c_0}{t} \left( + \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right) \right) </annotation></semantics></math></p> +<p>HS for +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi><mo>></mo><msub><mi>t</mi><mi>b</mi></msub></mrow><annotation encoding="application/x-tex">t > t_b</annotation></semantics></math>:</p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><msub><mi>c</mi><mn>0</mn></msub><mi>t</mi></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mn>1</mn><msub><mi>k</mi><mn>1</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><msub><mi>t</mi><mi>b</mi></msub></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mfrac><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><msub><mi>t</mi><mi>b</mi></msub></mrow></msup><msub><mi>k</mi><mn>2</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>2</mn></msub><mrow><mo stretchy="true" form="prefix">(</mo><mi>t</mi><mo>−</mo><msub><mi>t</mi><mi>b</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">c_\textrm{twa} = \frac{c_0}{t} \left( \frac{1}{k_1} \left( 1 - e^{- k_1 t_b} \right) + - \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)} -\right) \right) \]</span></p> + \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)} \right) \right) </annotation></semantics></math></p> <p>Often, the ratio between the time weighted average concentration -<span class="math inline">\(c_\textrm{twa}\)</span> and the initial -concentration <span class="math inline">\(c_0\)</span></p> -<p><span class="math display">\[f_\textrm{twa} = -\frac{c_\textrm{twa}}{c_0}\]</span></p> +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><annotation encoding="application/x-tex">c_\textrm{twa}</annotation></semantics></math> +and the initial concentration +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>c</mi><mn>0</mn></msub><annotation encoding="application/x-tex">c_0</annotation></semantics></math></p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>f</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><msub><mi>c</mi><mn>0</mn></msub></mfrac></mrow><annotation encoding="application/x-tex">f_\textrm{twa} = \frac{c_\textrm{twa}}{c_0}</annotation></semantics></math></p> <p>is needed. This can be calculated from the fitted initial -concentration <span class="math inline">\(c_0\)</span> and the time -weighted average concentration <span class="math inline">\(c_\textrm{twa}\)</span>, or directly from the -model parameters using the following formulas:</p> +concentration +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>c</mi><mn>0</mn></msub><annotation encoding="application/x-tex">c_0</annotation></semantics></math> +and the time weighted average concentration +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>c</mi><mtext mathvariant="normal">twa</mtext></msub><annotation encoding="application/x-tex">c_\textrm{twa}</annotation></semantics></math>, +or directly from the model parameters using the following formulas:</p> <p>SFO:</p> -<p><span class="math display">\[f_\textrm{twa} = \frac{\left( 1 - e^{- k -t} \right)}{k t} \]</span></p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>f</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><mi>k</mi><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mi>k</mi><mi>t</mi></mrow></mfrac></mrow><annotation encoding="application/x-tex">f_\textrm{twa} = \frac{\left( 1 - e^{- k t} \right)}{k t} </annotation></semantics></math></p> <p>FOMC:</p> -<p><span class="math display">\[f_\textrm{twa} = \frac{\beta}{t (1 - -\alpha)} - \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha} -- 1 \right) \]</span></p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>f</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><mi>β</mi><mrow><mi>t</mi><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><mi>α</mi><mo stretchy="true" form="postfix">)</mo></mrow></mrow></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><msup><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mi>t</mi><mi>β</mi></mfrac><mo>+</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mn>1</mn><mo>−</mo><mi>α</mi></mrow></msup><mo>−</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">f_\textrm{twa} = \frac{\beta}{t (1 - \alpha)} + \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha} - 1 \right) </annotation></semantics></math></p> <p>DFOP:</p> -<p><span class="math display">\[f_\textrm{twa} = \frac{1}{t} \left( +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>f</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><mn>1</mn><mi>t</mi></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mi>g</mi><msub><mi>k</mi><mn>1</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mfrac><mrow><mn>1</mn><mo>−</mo><mi>g</mi></mrow><msub><mi>k</mi><mn>2</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>2</mn></msub><mi>t</mi></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">f_\textrm{twa} = \frac{1}{t} \left( \frac{g}{k_1} \left( 1 - e^{- k_1 t} \right) + - \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right) \right) \]</span></p> -<p>HS for <span class="math inline">\(t > t_b\)</span>:</p> -<p><span class="math display">\[f_\textrm{twa} = \frac{1}{t} \left( + \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right) \right) </annotation></semantics></math></p> +<p>HS for +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi><mo>></mo><msub><mi>t</mi><mi>b</mi></msub></mrow><annotation encoding="application/x-tex">t > t_b</annotation></semantics></math>:</p> +<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>f</mi><mtext mathvariant="normal">twa</mtext></msub><mo>=</mo><mfrac><mn>1</mn><mi>t</mi></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mfrac><mn>1</mn><msub><mi>k</mi><mn>1</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><msub><mi>t</mi><mi>b</mi></msub></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mfrac><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>1</mn></msub><msub><mi>t</mi><mi>b</mi></msub></mrow></msup><msub><mi>k</mi><mn>2</mn></msub></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>−</mo><msup><mi>e</mi><mrow><mo>−</mo><msub><mi>k</mi><mn>2</mn></msub><mrow><mo stretchy="true" form="prefix">(</mo><mi>t</mi><mo>−</mo><msub><mi>t</mi><mi>b</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow></msup><mo stretchy="true" form="postfix">)</mo></mrow><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">f_\textrm{twa} = \frac{1}{t} \left( \frac{1}{k_1} \left( 1 - e^{- k_1 t_b} \right) + - \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)} -\right) \right) \]</span></p> + \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)} \right) \right) </annotation></semantics></math></p> <p>Note that a method for calculating maximum moving window time weighted average concentrations for a model fitted by ‘mkinfit’ or from parent decline model parameters is included in the @@ -173,28 +155,26 @@ Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration</em>. 1.1 ed. <a href="http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics" class="external-link">http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a>. </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - 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<input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../../search.json" id="search-input" placeholder="Search for" autocomplete="off"> -</form> - - <ul class="navbar-nav"> -<li class="nav-item"> - <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github"> - <span class="fab fa fab fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Example evaluation of FOCUS dataset Z</h1> + + <h1>Example evaluation of FOCUS dataset Z</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 16 January 2018 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/FOCUS_Z.rmd" class="external-link"><code>vignettes/web_only/FOCUS_Z.rmd</code></a></small> <div class="d-none name"><code>FOCUS_Z.rmd</code></div> @@ -296,9 +282,11 @@ not fitted very well using the SFO model, as residues at a certain low level remain.</p> <p>Therefore, an additional model is offered here, using the single first-order reversible binding (SFORB) model for metabolite Z3. As -expected, the <span class="math inline">\(\chi^2\)</span> error level is -lower for metabolite Z3 using this model and the graphical fit for Z3 is -improved. However, the covariance matrix is not returned.</p> +expected, the +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level is lower for metabolite Z3 using this model and the +graphical fit for Z3 is improved. However, the covariance matrix is not +returned.</p> <div class="sourceCode" id="cb38"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">Z.mkin.1</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>Z0 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"Z1"</span>, sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> <span> Z1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"Z2"</span>, sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> @@ -432,28 +420,26 @@ Studies on Pesticides in EU Registration</em>. 1.1 ed. <a href="http://esdac.jrc </div> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/web_only/FOCUS_Z_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/FOCUS_Z_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd6..00000000 --- a/docs/articles/web_only/FOCUS_Z_files/accessible-code-block-0.0.1/empty-anchor.js +++ /dev/null @@ -1,15 +0,0 @@ -// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> -// v0.0.1 -// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. - -document.addEventListener('DOMContentLoaded', function() { - const codeList = document.getElementsByClassName("sourceCode"); - for (var i = 0; i < codeList.length; i++) { - var linkList = codeList[i].getElementsByTagName('a'); - for (var j = 0; j < linkList.length; j++) { - if (linkList[j].innerHTML === "") { - linkList[j].setAttribute('aria-hidden', 'true'); - } - } - } -}); diff --git a/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.6/header-attrs.js b/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.6/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.6/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. We remove the former (to -// be compatible with the behavior of Pandoc < 2.8). -document.addEventListener('DOMContentLoaded', function(e) { - var hs = document.querySelectorAll("div.section[class*='level'] > :first-child"); - var i, h, a; - for (i = 0; i < hs.length; i++) { - h = hs[i]; - if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6 - a = h.attributes; - while (a.length > 0) h.removeAttribute(a[0].name); - } -}); diff --git a/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.7/header-attrs.js b/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.7/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/web_only/FOCUS_Z_files/header-attrs-2.7/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. We remove the former (to -// be compatible with the behavior of Pandoc < 2.8). -document.addEventListener('DOMContentLoaded', function(e) { - var hs = document.querySelectorAll("div.section[class*='level'] > :first-child"); - var i, h, a; - for (i = 0; i < hs.length; i++) { - h = hs[i]; - if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6 - a = h.attributes; - while (a.length > 0) h.removeAttribute(a[0].name); - } -}); diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html index 57b2ed1c..53e1db48 100644 --- a/docs/articles/web_only/NAFTA_examples.html +++ b/docs/articles/web_only/NAFTA_examples.html @@ -5,86 +5,71 @@ <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> -<meta name="description" content="mkin"> <title>Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance • 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href="../../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a></li> + <li><hr class="dropdown-divider"></li> + <li><h6 class="dropdown-header" data-toc-skip>Example evaluations with hierarchical models (nonlinear mixed-effects models)</h6></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_dmta_parent.html">Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/multistart.html">Short demo of the multistart method</a></li> + <li><hr class="dropdown-divider"></li> + <li><h6 class="dropdown-header" data-toc-skip>Performance</h6></li> + <li><a class="dropdown-item" href="../../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/benchmarks.html">Benchmark timings for mkin</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/saem_benchmarks.html">Benchmark timings for saem.mmkin</a></li> + <li><hr class="dropdown-divider"></li> + <li><h6 class="dropdown-header" data-toc-skip>Miscellaneous</h6></li> + <li><a class="dropdown-item" href="../../articles/twa.html">Calculation of time weighted average concentrations with mkin</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a></li> + </ul> </li> +<li class="nav-item"><a class="nav-link" href="../../coverage/coverage.html">Test coverage</a></li> +<li class="nav-item"><a class="nav-link" href="../../news/index.html">News</a></li> </ul> -<form class="form-inline my-2 my-lg-0" role="search"> - <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../../search.json" id="search-input" placeholder="Search for" autocomplete="off"> -</form> - - <ul class="navbar-nav"> -<li class="nav-item"> - <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github"> - <span class="fab fa fab fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,12 +78,13 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance</h1> + + <h1>Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">26 February 2019 (rebuilt -2023-11-16)</h4> +2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/NAFTA_examples.rmd" class="external-link"><code>vignettes/web_only/NAFTA_examples.rmd</code></a></small> <div class="d-none name"><code>NAFTA_examples.rmd</code></div> @@ -690,15 +676,14 @@ overparameterisation.</p> <pre><code><span><span class="co">## Warning in qt(alpha/2, rdf): NaNs produced</span></span></code></pre> <pre><code><span><span class="co">## Warning in qt(1 - alpha/2, rdf): NaNs produced</span></span></code></pre> <pre><code><span><span class="co">## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in sqrt(1/diag(V)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result</span></span> -<span><span class="co">## is doubtful</span></span></code></pre> +<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the</span></span> +<span><span class="co">## non-finite result may be dubious</span></span></code></pre> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The half-life obtained from the IORE model may be used</span></span></code></pre> -<div class="sourceCode" id="cb73"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb72"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p12b</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p12b-1.png" width="700"></p> -<div class="sourceCode" id="cb74"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb73"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p12b</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -742,14 +727,14 @@ overparameterisation.</p> <div class="section level3"> <h3 id="example-on-page-13">Example on page 13<a class="anchor" aria-label="anchor" href="#example-on-page-13"></a> </h3> -<div class="sourceCode" id="cb76"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb75"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">p13</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/nafta.html">nafta</a></span><span class="op">(</span><span class="va">NAFTA_SOP_Attachment</span><span class="op">[[</span><span class="st">"p13"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The half-life obtained from the IORE model may be used</span></span></code></pre> -<div class="sourceCode" id="cb79"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb78"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p13</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p13-1.png" width="700"></p> -<div class="sourceCode" id="cb80"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb79"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p13</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -794,18 +779,17 @@ overparameterisation.</p> <div class="section level2"> <h2 id="dt50-not-observed-in-the-study-and-dfop-problems-in-pestdf">DT50 not observed in the study and DFOP problems in PestDF<a class="anchor" aria-label="anchor" href="#dt50-not-observed-in-the-study-and-dfop-problems-in-pestdf"></a> </h2> -<div class="sourceCode" id="cb82"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb81"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">p14</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/nafta.html">nafta</a></span><span class="op">(</span><span class="va">NAFTA_SOP_Attachment</span><span class="op">[[</span><span class="st">"p14"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Warning in sqrt(diag(covar)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in sqrt(1/diag(V)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result</span></span> -<span><span class="co">## is doubtful</span></span></code></pre> +<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the</span></span> +<span><span class="co">## non-finite result may be dubious</span></span></code></pre> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The half-life obtained from the IORE model may be used</span></span></code></pre> -<div class="sourceCode" id="cb88"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb86"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p14</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p14-1.png" width="700"></p> -<div class="sourceCode" id="cb89"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb87"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p14</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -852,18 +836,17 @@ same results in mkin and PestDF.</p> <div class="section level2"> <h2 id="n-is-less-than-1-and-dfop-fraction-parameter-is-below-zero">N is less than 1 and DFOP fraction parameter is below zero<a class="anchor" aria-label="anchor" href="#n-is-less-than-1-and-dfop-fraction-parameter-is-below-zero"></a> </h2> -<div class="sourceCode" id="cb91"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb89"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">p15a</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/nafta.html">nafta</a></span><span class="op">(</span><span class="va">NAFTA_SOP_Attachment</span><span class="op">[[</span><span class="st">"p15a"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Warning in sqrt(diag(covar)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in sqrt(1/diag(V)): NaNs produced</span></span></code></pre> -<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result</span></span> -<span><span class="co">## is doubtful</span></span></code></pre> +<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the</span></span> +<span><span class="co">## non-finite result may be dubious</span></span></code></pre> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The half-life obtained from the IORE model may be used</span></span></code></pre> -<div class="sourceCode" id="cb97"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb94"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p15a</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p15a-1.png" width="700"></p> -<div class="sourceCode" id="cb98"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb95"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p15a</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -903,16 +886,16 @@ same results in mkin and PestDF.</p> <span><span class="co">## </span></span> <span><span class="co">## Representative half-life:</span></span> <span><span class="co">## [1] 41.33</span></span></code></pre> -<div class="sourceCode" id="cb100"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb97"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">p15b</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/nafta.html">nafta</a></span><span class="op">(</span><span class="va">NAFTA_SOP_Attachment</span><span class="op">[[</span><span class="st">"p15b"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance</span></span> <span><span class="co">## matrix</span></span></code></pre> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The half-life obtained from the IORE model may be used</span></span></code></pre> -<div class="sourceCode" id="cb104"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb101"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p15b</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p15b-1.png" width="700"></p> -<div class="sourceCode" id="cb105"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb102"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p15b</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -960,16 +943,16 @@ mkin and PestDF.</p> <div class="section level2"> <h2 id="the-dfop-fraction-parameter-is-greater-than-1">The DFOP fraction parameter is greater than 1<a class="anchor" aria-label="anchor" href="#the-dfop-fraction-parameter-is-greater-than-1"></a> </h2> -<div class="sourceCode" id="cb107"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb104"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">p16</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/nafta.html">nafta</a></span><span class="op">(</span><span class="va">NAFTA_SOP_Attachment</span><span class="op">[[</span><span class="st">"p16"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c</span></span></code></pre> <pre><code><span><span class="co">## The representative half-life of the IORE model is longer than the one corresponding</span></span></code></pre> <pre><code><span><span class="co">## to the terminal degradation rate found with the DFOP model.</span></span></code></pre> <pre><code><span><span class="co">## The representative half-life obtained from the DFOP model may be used</span></span></code></pre> -<div class="sourceCode" id="cb112"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb109"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">p16</span><span class="op">)</span></span></code></pre></div> <p><img src="NAFTA_examples_files/figure-html/p16-1.png" width="700"></p> -<div class="sourceCode" id="cb113"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb110"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">p16</span><span class="op">)</span></span></code></pre></div> <pre><code><span><span class="co">## Sums of squares:</span></span> <span><span class="co">## SFO IORE DFOP </span></span> @@ -1010,10 +993,12 @@ mkin and PestDF.</p> <span><span class="co">## Representative half-life:</span></span> <span><span class="co">## [1] 8.93</span></span></code></pre> <p>In PestDF, the DFOP fit seems to have stuck in a local minimum, as -mkin finds a solution with a much lower <span class="math inline">\(\chi^2\)</span> error level. As the half-life from -the slower rate constant of the DFOP model is larger than the IORE -derived half-life, the NAFTA recommendation obtained with mkin is to use -the DFOP representative half-life of 8.9 days.</p> +mkin finds a solution with a much lower +<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>χ</mi><mn>2</mn></msup><annotation encoding="application/x-tex">\chi^2</annotation></semantics></math> +error level. As the half-life from the slower rate constant of the DFOP +model is larger than the IORE derived half-life, the NAFTA +recommendation obtained with mkin is to use the DFOP representative +half-life of 8.9 days.</p> </div> <div class="section level2"> <h2 id="conclusions">Conclusions<a class="anchor" aria-label="anchor" href="#conclusions"></a> @@ -1038,28 +1023,26 @@ Pesticide Degradation.”</span> <a href="https://www.epa.gov/pesticide-science- </div> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd6..00000000 --- a/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js +++ /dev/null @@ -1,15 +0,0 @@ -// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> -// v0.0.1 -// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. - -document.addEventListener('DOMContentLoaded', function() { - const codeList = document.getElementsByClassName("sourceCode"); - for (var i = 0; i < codeList.length; i++) { - var linkList = codeList[i].getElementsByTagName('a'); - for (var j = 0; j < linkList.length; j++) { - if (linkList[j].innerHTML === "") { - linkList[j].setAttribute('aria-hidden', 'true'); - } - } - } -}); diff --git a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js b/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. We remove the former (to -// be compatible with the behavior of Pandoc < 2.8). -document.addEventListener('DOMContentLoaded', function(e) { - var hs = document.querySelectorAll("div.section[class*='level'] > :first-child"); - var i, h, a; - for (i = 0; i < hs.length; i++) { - h = hs[i]; - if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6 - a = h.attributes; - while (a.length > 0) h.removeAttribute(a[0].name); - } -}); diff --git a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js b/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js deleted file mode 100644 index dd57d92e..00000000 --- a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js +++ /dev/null @@ -1,12 +0,0 @@ -// Pandoc 2.9 adds attributes on both header and div. 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<img src="" class="logo" alt=""><h1>Benchmark timings for mkin</h1> + + <h1>Benchmark timings for mkin</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 17 February 2023 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-13)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/benchmarks.rmd" class="external-link"><code>vignettes/web_only/benchmarks.rmd</code></a></small> <div class="d-none name"><code>benchmarks.rmd</code></div> @@ -428,6 +414,30 @@ models fitted to two datasets, i.e. eight fits for each test.</p> <td align="right">1.408</td> <td align="right">2.041</td> </tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.9</td> +<td align="right">1.323</td> +<td align="right">1.925</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.10</td> +<td align="right">1.407</td> +<td align="right">1.990</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.5.0</td> +<td align="left">1.2.10</td> +<td align="right">1.355</td> +<td align="right">1.976</td> +</tr> </tbody> </table> </div> @@ -700,6 +710,33 @@ for each test.</p> <td align="right">2.228</td> <td align="right">1.178</td> </tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.9</td> +<td align="right">0.754</td> +<td align="right">2.153</td> +<td align="right">1.139</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.10</td> +<td align="right">0.775</td> +<td align="right">2.199</td> +<td align="right">1.161</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.5.0</td> +<td align="left">1.2.10</td> +<td align="right">0.774</td> +<td align="right">2.128</td> +<td align="right">1.095</td> +</tr> </tbody> </table> </div> @@ -1059,32 +1096,66 @@ dataset, i.e. one fit for each test.</p> <td align="right">0.749</td> <td align="right">0.999</td> </tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.9</td> +<td align="right">0.424</td> +<td align="right">0.534</td> +<td align="right">0.560</td> +<td align="right">1.298</td> +<td align="right">0.735</td> +<td align="right">0.981</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.4.2</td> +<td align="left">1.2.10</td> +<td align="right">0.433</td> +<td align="right">0.541</td> +<td align="right">0.576</td> +<td align="right">1.307</td> +<td align="right">0.744</td> +<td align="right">0.988</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 9 7950X</td> +<td align="left">4.5.0</td> +<td align="left">1.2.10</td> +<td align="right">0.407</td> +<td align="right">0.519</td> +<td align="right">0.544</td> +<td align="right">1.266</td> +<td align="right">0.738</td> +<td align="right">0.977</td> +</tr> </tbody> </table> </div> </div> - 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fa-github fa-lg"></span> - - </a> -</li> +<ul class="navbar-nav"> +<li class="nav-item"><form class="form-inline" role="search"> + <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../../search.json"> +</form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> </ul> </div> - + </div> </nav><div class="container template-article"> @@ -93,11 +78,12 @@ <div class="row"> <main id="main" class="col-md-9"><div class="page-header"> - <img src="" class="logo" alt=""><h1>Performance benefit by using compiled model definitions in mkin</h1> + + <h1>Performance benefit by using compiled model definitions in mkin</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 data-toc-skip class="date">2023-11-16</h4> + <h4 data-toc-skip class="date">2025-05-12</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/compiled_models.rmd" class="external-link"><code>vignettes/web_only/compiled_models.rmd</code></a></small> <div class="d-none name"><code>compiled_models.rmd</code></div> @@ -175,10 +161,10 @@ solution is also implemented, which is included in the tests below.</p> <span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="st">"R package rbenchmark is not available"</span><span class="op">)</span></span> <span><span class="op">}</span></span></code></pre></div> <pre><code><span><span class="co">## test replications relative elapsed</span></span> -<span><span class="co">## 4 analytical 1 1.000 0.109</span></span> -<span><span class="co">## 3 deSolve, compiled 1 1.284 0.140</span></span> -<span><span class="co">## 2 Eigenvalue based 1 1.670 0.182</span></span> -<span><span class="co">## 1 deSolve, not compiled 1 21.927 2.390</span></span></code></pre> +<span><span class="co">## 4 analytical 1 1.000 0.111</span></span> +<span><span class="co">## 3 deSolve, compiled 1 1.270 0.141</span></span> +<span><span class="co">## 2 Eigenvalue based 1 1.658 0.184</span></span> +<span><span class="co">## 1 deSolve, not compiled 1 21.973 2.439</span></span></code></pre> <p>We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.</p> </div> @@ -209,38 +195,36 @@ compiled code is available.</p> <span><span class="op">}</span></span></code></pre></div> <pre><code><span><span class="co">## Temporary DLL for differentials generated and loaded</span></span></code></pre> <pre><code><span><span class="co">## test replications relative elapsed</span></span> -<span><span class="co">## 2 deSolve, compiled 1 1.000 0.181</span></span> -<span><span class="co">## 1 deSolve, not compiled 1 23.646 4.280</span></span></code></pre> +<span><span class="co">## 2 deSolve, compiled 1 1.000 0.182</span></span> +<span><span class="co">## 1 deSolve, not compiled 1 23.808 4.333</span></span></code></pre> <p>Here we get a performance benefit of a factor of 24 using the version of the differential equation model compiled from C code!</p> -<p>This vignette was built with mkin 1.2.6 on</p> -<pre><code><span><span class="co">## R version 4.3.2 (2023-10-31)</span></span> -<span><span class="co">## Platform: x86_64-pc-linux-gnu (64-bit)</span></span> +<p>This vignette was built with mkin 1.2.10 on</p> +<pre><code><span><span class="co">## R version 4.5.0 (2025-04-11)</span></span> +<span><span class="co">## Platform: x86_64-pc-linux-gnu</span></span> <span><span class="co">## Running under: Debian GNU/Linux 12 (bookworm)</span></span></code></pre> <pre><code><span><span class="co">## CPU model: AMD Ryzen 9 7950X 16-Core Processor</span></span></code></pre> </div> - </main><aside 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<small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/dimethenamid_2018.rmd" class="external-link"><code>vignettes/web_only/dimethenamid_2018.rmd</code></a></small> <div class="d-none name"><code>dimethenamid_2018.rmd</code></div> @@ -413,11 +399,11 @@ DMTA_0 98.24165 96.29190 100.1914 k1 0.06421 0.03352 0.0949 k2 0.00866 0.00617 0.0111 g 0.95340 0.91218 0.9946 -a.1 1.06463 0.86503 1.2642 -b.1 0.02964 0.02259 0.0367 -SD.DMTA_0 2.03611 0.40416 3.6681 +a.1 1.06463 0.87979 1.2495 +b.1 0.02964 0.02266 0.0366 +SD.DMTA_0 2.03611 0.40361 3.6686 SD.k1 0.59534 0.25692 0.9338 -SD.k2 0.00042 -73.01372 73.0146 +SD.k2 0.00042 -73.00540 73.0062 SD.g 1.04234 0.37189 1.7128</code></pre> <p>Doubling the number of iterations in the first phase of the algorithm leads to a slightly lower likelihood, and therefore to slightly higher @@ -576,13 +562,13 @@ satisfactory precision.</p> </h2> <div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/sessionInfo.html" class="external-link">sessionInfo</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -599,23 +585,21 @@ attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: -[1] saemix_3.2 npde_3.3 nlme_3.1-163 mkin_1.2.6 knitr_1.42 +[1] saemix_3.3 npde_3.5 nlme_3.1-168 mkin_1.2.10 knitr_1.49 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.4 -[13] DBI_1.1.3 mclust_6.0.0 gridExtra_2.3 purrr_1.0.1 -[17] fansi_1.0.4 scales_1.2.1 codetools_0.2-19 textshaping_0.3.6 -[21] jquerylib_0.1.4 cli_3.6.1 rlang_1.1.1 munsell_0.5.0 -[25] cachem_1.0.8 yaml_2.3.7 tools_4.3.2 parallel_4.3.2 -[29] memoise_2.0.1 dplyr_1.1.2 colorspace_2.1-0 ggplot2_3.4.2 -[33] vctrs_0.6.2 R6_2.5.1 zoo_1.8-12 lifecycle_1.0.3 -[37] stringr_1.5.0 fs_1.6.2 MASS_7.3-60 ragg_1.2.5 -[41] pkgconfig_2.0.3 desc_1.4.2 pkgdown_2.0.7 bslib_0.4.2 -[45] pillar_1.9.0 gtable_0.3.3 glue_1.6.2 systemfonts_1.0.4 -[49] highr_0.10 xfun_0.39 tibble_3.2.1 lmtest_0.9-40 -[53] tidyselect_1.2.0 htmltools_0.5.5 rmarkdown_2.21 compiler_4.3.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 parallel_4.5.0 gridExtra_2.3 jquerylib_0.1.4 + [9] systemfonts_1.2.1 scales_1.3.0 textshaping_1.0.0 yaml_2.3.10 +[13] fastmap_1.2.0 lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 +[17] generics_0.1.3 lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 +[21] tibble_3.2.1 desc_1.4.3 munsell_0.5.1 bslib_0.9.0 +[25] pillar_1.10.1 rlang_1.1.5 cachem_1.1.0 xfun_0.51 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.5.0 mclust_6.1.1 +[37] lifecycle_1.0.4 vctrs_0.6.5 evaluate_1.0.3 glue_1.8.0 +[41] codetools_0.2-20 ragg_1.3.3 zoo_1.8-13 colorspace_2.1-1 +[45] rmarkdown_2.29 tools_4.5.0 pkgconfig_2.0.3 htmltools_0.5.8.1</code></pre> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a> @@ -640,28 +624,26 @@ November 2017</span>.”</span> <a href="https://open.efsa.europa.eu/study-inven </div> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this 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+ + <h4 data-toc-skip class="date">Last change 13 May 2025 +(rebuilt 2025-05-14)</h4> + + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/mesotrione_parent_2023.rmd" class="external-link"><code>vignettes/web_only/mesotrione_parent_2023.rmd</code></a></small> + <div class="d-none name"><code>mesotrione_parent_2023.rmd</code></div> + </div> + + + +<div class="section level2"> +<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> +</h2> +<p>The purpose of this document is to test demonstrate how nonlinear +hierarchical models (NLHM) based on the parent degradation models SFO, +FOMC, DFOP and HS can be fitted with the mkin package, also considering +the influence of covariates like soil pH on different degradation +parameters. Because in some other case studies, the SFORB +parameterisation of biexponential decline has shown some advantages over +the DFOP parameterisation, SFORB was included in the list of tested +models as well.</p> +<p>The mkin package is used in version 1.2.10, which is contains the +functions that were used for the evaluations. The <code>saemix</code> +package is used as a backend for fitting the NLHM, but is also loaded to +make the convergence plot function available.</p> +<p>This document is processed with the <code>knitr</code> package, which +also provides the <code>kable</code> function that is used to improve +the display of tabular data in R markdown documents. For parallel +processing, the <code>parallel</code> package is used.</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="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://yihui.org/knitr/" class="external-link">knitr</a></span><span class="op">)</span></span> +<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">saemix</span><span class="op">)</span></span> +<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="va">n_cores</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">detectCores</a></span><span class="op">(</span><span class="op">)</span></span> +<span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Sys.info.html" class="external-link">Sys.info</a></span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="st">"sysname"</span><span class="op">]</span> <span class="op">==</span> <span class="st">"Windows"</span><span class="op">)</span> <span class="op">{</span></span> +<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="va">n_cores</span><span class="op">)</span></span> +<span><span class="op">}</span> <span class="kw">else</span> <span class="op">{</span></span> +<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">makeForkCluster</a></span><span class="op">(</span><span class="va">n_cores</span><span class="op">)</span></span> +<span><span class="op">}</span></span></code></pre></div> +<div class="section level3"> +<h3 id="test-data">Test data<a class="anchor" aria-label="anchor" href="#test-data"></a> +</h3> +<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">data_file</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.file.html" class="external-link">system.file</a></span><span class="op">(</span></span> +<span> <span class="st">"testdata"</span>, <span class="st">"mesotrione_soil_efsa_2016.xlsx"</span>, package <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span></span> +<span><span class="va">meso_ds</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/read_spreadsheet.html">read_spreadsheet</a></span><span class="op">(</span><span class="va">data_file</span>, parent_only <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<p>The following tables show the covariate data and the 18 datasets that +were read in from the spreadsheet file.</p> +<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">pH</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attr.html" class="external-link">attr</a></span><span class="op">(</span><span class="va">meso_ds</span>, <span class="st">"covariates"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="va">pH</span>, caption <span class="op">=</span> <span class="st">"Covariate data"</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<caption>Covariate data</caption> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">pH</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">Richmond</td> +<td align="right">6.2</td> +</tr> +<tr class="even"> +<td align="left">Richmond 2</td> +<td align="right">6.2</td> +</tr> +<tr class="odd"> +<td align="left">ERTC</td> +<td align="right">6.4</td> +</tr> +<tr class="even"> +<td align="left">Toulouse</td> +<td align="right">7.7</td> +</tr> +<tr class="odd"> +<td align="left">Picket Piece</td> +<td align="right">7.1</td> +</tr> +<tr class="even"> +<td align="left">721</td> +<td align="right">5.6</td> +</tr> +<tr class="odd"> +<td align="left">722</td> +<td align="right">5.7</td> +</tr> +<tr class="even"> +<td align="left">723</td> +<td align="right">5.4</td> +</tr> +<tr class="odd"> +<td align="left">724</td> +<td align="right">4.8</td> +</tr> +<tr class="even"> +<td align="left">725</td> +<td align="right">5.8</td> +</tr> +<tr class="odd"> +<td align="left">727</td> +<td align="right">5.1</td> +</tr> +<tr class="even"> +<td align="left">728</td> +<td align="right">5.9</td> +</tr> +<tr class="odd"> +<td align="left">729</td> +<td align="right">5.6</td> +</tr> +<tr class="even"> +<td align="left">730</td> +<td align="right">5.3</td> +</tr> +<tr class="odd"> +<td align="left">731</td> +<td align="right">6.1</td> +</tr> +<tr class="even"> +<td align="left">732</td> +<td align="right">5.0</td> +</tr> +<tr class="odd"> +<td align="left">741</td> +<td align="right">5.7</td> +</tr> +<tr class="even"> +<td align="left">742</td> +<td align="right">7.2</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="kw">for</span> <span class="op">(</span><span class="va">ds_name</span> <span class="kw">in</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">meso_ds</span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span></span> +<span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mkin_long_to_wide.html">mkin_long_to_wide</a></span><span class="op">(</span><span class="va">meso_ds</span><span class="op">[[</span><span class="va">ds_name</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>,</span> +<span> caption <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="va">ds_name</span><span class="op">)</span>,</span> +<span> booktabs <span class="op">=</span> <span class="cn">TRUE</span>, row.names <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="op">}</span></span></code></pre></div> +<table class="table"> +<caption>Dataset Richmond</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">91.00</td> +</tr> +<tr class="even"> +<td align="right">1.179050</td> +<td align="right">86.70</td> +</tr> +<tr class="odd"> +<td align="right">3.537149</td> +<td align="right">73.60</td> +</tr> +<tr class="even"> +<td align="right">7.074299</td> +<td align="right">61.50</td> +</tr> +<tr class="odd"> +<td align="right">10.611448</td> +<td align="right">55.70</td> +</tr> +<tr class="even"> +<td align="right">15.327647</td> +<td align="right">47.70</td> +</tr> +<tr class="odd"> +<td align="right">17.685747</td> +<td align="right">39.50</td> +</tr> +<tr class="even"> +<td align="right">24.760046</td> +<td align="right">29.80</td> +</tr> +<tr class="odd"> +<td align="right">35.371494</td> +<td align="right">19.60</td> +</tr> +<tr class="even"> +<td align="right">68.384889</td> +<td align="right">5.67</td> +</tr> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">97.90</td> +</tr> +<tr class="even"> +<td align="right">1.179050</td> +<td align="right">96.40</td> +</tr> +<tr class="odd"> +<td align="right">3.537149</td> +<td align="right">89.10</td> +</tr> +<tr class="even"> +<td align="right">7.074299</td> +<td align="right">74.40</td> +</tr> +<tr class="odd"> +<td align="right">10.611448</td> +<td align="right">57.40</td> +</tr> +<tr class="even"> +<td align="right">15.327647</td> +<td align="right">46.30</td> +</tr> +<tr class="odd"> +<td align="right">18.864797</td> +<td align="right">35.50</td> +</tr> +<tr class="even"> +<td align="right">27.118146</td> +<td align="right">27.20</td> +</tr> +<tr class="odd"> +<td align="right">35.371494</td> +<td align="right">19.10</td> +</tr> +<tr class="even"> +<td align="right">74.280138</td> +<td align="right">6.50</td> +</tr> +<tr class="odd"> +<td align="right">108.472582</td> +<td align="right">3.40</td> +</tr> +<tr class="even"> +<td align="right">142.665027</td> +<td align="right">2.20</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Richmond 2</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">96.0</td> +</tr> +<tr class="even"> +<td align="right">2.422004</td> +<td align="right">82.4</td> +</tr> +<tr class="odd"> +<td align="right">5.651343</td> +<td align="right">71.2</td> +</tr> +<tr class="even"> +<td align="right">8.073348</td> +<td align="right">53.1</td> +</tr> +<tr class="odd"> +<td align="right">11.302687</td> +<td align="right">48.5</td> +</tr> +<tr class="even"> +<td align="right">16.954030</td> +<td align="right">33.4</td> +</tr> +<tr class="odd"> +<td align="right">22.605373</td> +<td align="right">24.2</td> +</tr> +<tr class="even"> +<td align="right">45.210746</td> +<td align="right">11.9</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset ERTC</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">99.9</td> +</tr> +<tr class="even"> +<td align="right">2.755193</td> +<td align="right">80.0</td> +</tr> +<tr class="odd"> +<td align="right">6.428782</td> +<td align="right">42.1</td> +</tr> +<tr class="even"> +<td align="right">9.183975</td> +<td align="right">50.1</td> +</tr> +<tr class="odd"> +<td align="right">12.857565</td> +<td align="right">28.4</td> +</tr> +<tr class="even"> +<td align="right">19.286347</td> +<td align="right">39.8</td> +</tr> +<tr class="odd"> +<td align="right">25.715130</td> +<td align="right">29.9</td> +</tr> +<tr class="even"> +<td align="right">51.430259</td> +<td align="right">2.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Toulouse</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">96.8</td> +</tr> +<tr class="even"> +<td align="right">2.897983</td> +<td align="right">63.3</td> +</tr> +<tr class="odd"> +<td align="right">6.761960</td> +<td align="right">22.3</td> +</tr> +<tr class="even"> +<td align="right">9.659942</td> +<td align="right">16.6</td> +</tr> +<tr class="odd"> +<td align="right">13.523919</td> +<td align="right">16.1</td> +</tr> +<tr class="even"> +<td align="right">20.285879</td> +<td align="right">17.2</td> +</tr> +<tr class="odd"> +<td align="right">27.047838</td> +<td align="right">1.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Picket Piece</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">102.0</td> +</tr> +<tr class="even"> +<td align="right">2.841195</td> +<td align="right">73.7</td> +</tr> +<tr class="odd"> +<td align="right">6.629454</td> +<td align="right">35.5</td> +</tr> +<tr class="even"> +<td align="right">9.470649</td> +<td align="right">31.8</td> +</tr> +<tr class="odd"> +<td align="right">13.258909</td> +<td align="right">18.0</td> +</tr> +<tr class="even"> +<td align="right">19.888364</td> +<td align="right">3.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 721</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">86.4</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">61.4</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">49.8</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">41.0</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">35.1</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 722</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">52.1</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">37.4</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">21.2</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">14.3</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 723</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">89.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">70.8</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">51.1</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">42.7</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">26.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 724</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">89.4</td> +</tr> +<tr class="even"> +<td align="right">9.008208</td> +<td align="right">65.2</td> +</tr> +<tr class="odd"> +<td align="right">18.016415</td> +<td align="right">55.8</td> +</tr> +<tr class="even"> +<td align="right">27.024623</td> +<td align="right">46.0</td> +</tr> +<tr class="odd"> +<td align="right">36.032831</td> +<td align="right">41.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 725</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">89.0</td> +</tr> +<tr class="even"> +<td align="right">10.99058</td> +<td align="right">35.4</td> +</tr> +<tr class="odd"> +<td align="right">21.98116</td> +<td align="right">18.6</td> +</tr> +<tr class="even"> +<td align="right">32.97174</td> +<td align="right">11.6</td> +</tr> +<tr class="odd"> +<td align="right">43.96232</td> +<td align="right">7.6</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 727</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.3</td> +</tr> +<tr class="even"> +<td align="right">10.96104</td> +<td align="right">63.2</td> +</tr> +<tr class="odd"> +<td align="right">21.92209</td> +<td align="right">51.1</td> +</tr> +<tr class="even"> +<td align="right">32.88313</td> +<td align="right">42.0</td> +</tr> +<tr class="odd"> +<td align="right">43.84417</td> +<td align="right">40.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 728</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.8</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">43.6</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">22.0</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">15.9</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">8.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 729</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.6</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">60.5</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">43.5</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">28.4</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">20.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 730</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.7</td> +</tr> +<tr class="even"> +<td align="right">11.07446</td> +<td align="right">58.9</td> +</tr> +<tr class="odd"> +<td align="right">22.14893</td> +<td align="right">44.0</td> +</tr> +<tr class="even"> +<td align="right">33.22339</td> +<td align="right">46.0</td> +</tr> +<tr class="odd"> +<td align="right">44.29785</td> +<td align="right">29.3</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 731</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.1</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">64.4</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">45.3</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">33.6</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">23.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 732</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">58.2</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">40.1</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">33.1</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">25.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 741</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">10.84712</td> +<td align="right">68.7</td> +</tr> +<tr class="odd"> +<td align="right">21.69424</td> +<td align="right">58.0</td> +</tr> +<tr class="even"> +<td align="right">32.54136</td> +<td align="right">52.2</td> +</tr> +<tr class="odd"> +<td align="right">43.38848</td> +<td align="right">48.0</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 742</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.0</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">60.9</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">36.2</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">18.3</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">8.7</td> +</tr> +</tbody> +</table> +</div> +</div> +<div class="section level2"> +<h2 id="separate-evaluations">Separate evaluations<a class="anchor" aria-label="anchor" href="#separate-evaluations"></a> +</h2> +<p>In order to obtain suitable starting parameters for the NLHM fits, +separate fits of the five models to the data for each soil are generated +using the <code>mmkin</code> function from the mkin package. In a first +step, constant variance is assumed. Convergence is checked with the +<code>status</code> function.</p> +<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">deg_mods</span> <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="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"SFORB"</span>, <span class="st">"HS"</span><span class="op">)</span></span> +<span><span class="va">f_sep_const</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span></span> +<span> <span class="va">deg_mods</span>,</span> +<span> <span class="va">meso_ds</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"const"</span>,</span> +<span> cluster <span class="op">=</span> <span class="va">cl</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">Richmond</th> +<th align="left">Richmond 2</th> +<th align="left">ERTC</th> +<th align="left">Toulouse</th> +<th align="left">Picket Piece</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">18</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="10%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">721</th> +<th align="left">722</th> +<th align="left">723</th> +<th align="left">724</th> +<th align="left">725</th> +<th align="left">727</th> +<th align="left">728</th> +<th align="left">729</th> +<th align="left">730</th> +<th align="left">731</th> +<th align="left">732</th> +<th align="left">741</th> +<th align="left">742</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>In the tables above, OK indicates convergence and C indicates failure +to converge. Most separate fits with constant variance converged, with +the exception of two FOMC fits, one SFORB fit and one HS fit.</p> +<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_sep_tc</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_sep_const</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_tc</span><span class="op">[</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">Richmond</th> +<th align="left">Richmond 2</th> +<th align="left">ERTC</th> +<th align="left">Toulouse</th> +<th align="left">Picket Piece</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_tc</span><span class="op">[</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">18</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="10%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">721</th> +<th align="left">722</th> +<th align="left">723</th> +<th align="left">724</th> +<th align="left">725</th> +<th align="left">727</th> +<th align="left">728</th> +<th align="left">729</th> +<th align="left">730</th> +<th align="left">731</th> +<th align="left">732</th> +<th align="left">741</th> +<th align="left">742</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>With the two-component error model, the set of fits that did not +converge is larger, with convergence problems appearing for a number of +non-SFO fits.</p> +</div> +<div class="section level2"> +<h2 id="hierarchical-models-without-covariate">Hierarchical models without covariate<a class="anchor" aria-label="anchor" href="#hierarchical-models-without-covariate"></a> +</h2> +<p>The following code fits hierarchical kinetic models for the ten +combinations of the five different degradation models with the two +different error models in parallel.</p> +<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_1</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mhmkin.html">mhmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_sep_const</span>, <span class="va">f_sep_tc</span><span class="op">)</span>, cluster <span class="op">=</span> <span class="va">cl</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>All fits terminate without errors (status OK).</p> +<div class="sourceCode" id="cb12"><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_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">npar</th> +<th align="right">AIC</th> +<th align="right">BIC</th> +<th align="right">Lik</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO const</td> +<td align="right">5</td> +<td align="right">800.0</td> +<td align="right">804.5</td> +<td align="right">-395.0</td> +</tr> +<tr class="even"> +<td align="left">SFO tc</td> +<td align="right">6</td> +<td align="right">801.9</td> +<td align="right">807.2</td> +<td align="right">-394.9</td> +</tr> +<tr class="odd"> +<td align="left">FOMC const</td> +<td align="right">7</td> +<td align="right">787.4</td> +<td align="right">793.6</td> +<td align="right">-386.7</td> +</tr> +<tr class="even"> +<td align="left">FOMC tc</td> +<td align="right">8</td> +<td align="right">788.9</td> +<td align="right">796.1</td> +<td align="right">-386.5</td> +</tr> +<tr class="odd"> +<td align="left">DFOP const</td> +<td align="right">9</td> +<td align="right">787.6</td> +<td align="right">795.6</td> +<td align="right">-384.8</td> +</tr> +<tr class="even"> +<td align="left">SFORB const</td> +<td align="right">9</td> +<td align="right">787.4</td> +<td align="right">795.4</td> +<td align="right">-384.7</td> +</tr> +<tr class="odd"> +<td align="left">HS const</td> +<td align="right">9</td> +<td align="right">781.9</td> +<td align="right">789.9</td> +<td align="right">-382.0</td> +</tr> +<tr class="even"> +<td align="left">DFOP tc</td> +<td align="right">10</td> +<td align="right">787.4</td> +<td align="right">796.3</td> +<td align="right">-383.7</td> +</tr> +<tr class="odd"> +<td align="left">SFORB tc</td> +<td align="right">10</td> +<td align="right">795.8</td> +<td align="right">804.7</td> +<td align="right">-387.9</td> +</tr> +<tr class="even"> +<td align="left">HS tc</td> +<td align="right">10</td> +<td align="right">783.7</td> +<td align="right">792.7</td> +<td align="right">-381.9</td> +</tr> +</tbody> +</table> +<p>The model comparisons show that the fits with constant variance are +consistently preferable to the corresponding fits with two-component +error for these data. This is confirmed by the fact that the parameter +<code>b.1</code> (the relative standard deviation in the fits obtained +with the saemix package), is ill-defined in all fits.</p> +<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="6%"> +<col width="44%"> +<col width="49%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">sd(meso_0)</td> +<td align="left">sd(meso_0), b.1</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">sd(meso_0), sd(log_beta)</td> +<td align="left">sd(meso_0), sd(log_beta), b.1</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">sd(meso_0), sd(log_k1)</td> +<td align="left">sd(meso_0), sd(g_qlogis), b.1</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">sd(meso_free_0), sd(log_k_meso_free_bound)</td> +<td align="left">sd(meso_free_0), sd(log_k_meso_free_bound), b.1</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">sd(meso_0)</td> +<td align="left">sd(meso_0), b.1</td> +</tr> +</tbody> +</table> +<p>For obtaining fits with only well-defined random effects, we update +the set of fits, excluding random effects that were ill-defined +according to the <code>illparms</code> function.</p> +<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_2</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_1</span>, no_random_effect <span class="op">=</span> <span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>The updated fits terminate without errors.</p> +<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +</tbody> +</table> +<p>No ill-defined errors remain in the fits with constant variance.</p> +</div> +<div class="section level2"> +<h2 id="hierarchical-models-with-covariate">Hierarchical models with covariate<a class="anchor" aria-label="anchor" href="#hierarchical-models-with-covariate"></a> +</h2> +<p>In the following sections, hierarchical fits including a model for +the influence of pH on selected degradation parameters are shown for all +parent models. Constant variance is selected as the error model based on +the fits without covariate effects. Random effects that were ill-defined +in the fits without pH influence are excluded. A potential influence of +the soil pH is only included for parameters with a well-defined random +effect, because experience has shown that only for such parameters a +significant pH effect could be found.</p> +<div class="section level3"> +<h3 id="sfo">SFO<a class="anchor" aria-label="anchor" href="#sfo"></a> +</h3> +<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sfo_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="st">"meso_0"</span>, covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">91.35</td> +<td align="right">89.27</td> +<td align="right">93.43</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso</td> +<td align="right">-6.66</td> +<td align="right">-7.97</td> +<td align="right">-5.35</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso)</td> +<td align="right">0.59</td> +<td align="right">0.37</td> +<td align="right">0.81</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">5.48</td> +<td align="right">4.71</td> +<td align="right">6.24</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso</td> +<td align="right">0.35</td> +<td align="right">0.23</td> +<td align="right">0.47</td> +</tr> +</tbody> +</table> +<p>The parameter showing the pH influence in the above table is +<code>beta_pH(log_k_meso)</code>. Its confidence interval does not +include zero, indicating that the influence of soil pH on the log of the +degradation rate constant is significantly greater than zero.</p> +<div class="sourceCode" id="cb18"><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_2</span><span class="op">[[</span><span class="st">"SFO"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">sfo_pH</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["SFO", "const"]] 4 797.56 801.12 -394.78 +sfo_pH 5 783.09 787.54 -386.54 16.473 1 4.934e-05 *** +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>The comparison with the SFO fit without covariate effect confirms +that considering the soil pH improves the model, both by comparison of +AIC and BIC and by the likelihood ratio test.</p> +<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_files/figure-html/unnamed-chunk-8-1.png" width="700" style="display: block; margin: auto;"></p> +<p>Endpoints for a model with covariates are by default calculated for +the median of the covariate values. This quantile can be adapted, or a +specific covariate value can be given as shown below.</p> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 +meso 18.52069 61.52441</code></pre> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span>, covariate_quantile <span class="op">=</span> <span class="fl">0.9</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +90% 7.13 + +$distimes + DT50 DT90 +meso 8.237019 27.36278</code></pre> +<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7.0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 +meso 8.89035 29.5331</code></pre> +</div> +<div class="section level3"> +<h3 id="fomc">FOMC<a class="anchor" aria-label="anchor" href="#fomc"></a> +</h3> +<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">fomc_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="st">"meso_0"</span>, covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_alpha</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fomc_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">92.84</td> +<td align="right">90.75</td> +<td align="right">94.93</td> +</tr> +<tr class="even"> +<td align="left">log_alpha</td> +<td align="right">-2.21</td> +<td align="right">-3.49</td> +<td align="right">-0.92</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_alpha)</td> +<td align="right">0.58</td> +<td align="right">0.37</td> +<td align="right">0.79</td> +</tr> +<tr class="even"> +<td align="left">log_beta</td> +<td align="right">4.21</td> +<td align="right">3.44</td> +<td align="right">4.99</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">5.03</td> +<td align="right">4.32</td> +<td align="right">5.73</td> +</tr> +<tr class="even"> +<td align="left">SD.log_alpha</td> +<td align="right">0.00</td> +<td align="right">-23.77</td> +<td align="right">23.78</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_beta</td> +<td align="right">0.37</td> +<td align="right">0.01</td> +<td align="right">0.74</td> +</tr> +</tbody> +</table> +<p>As in the case of SFO, the confidence interval of the slope parameter +(here <code>beta_pH(log_alpha)</code>) quantifying the influence of soil +pH does not include zero, and the model comparison clearly indicates +that the model with covariate influence is preferable. However, the +random effect for <code>alpha</code> is not well-defined any more after +inclusion of the covariate effect (the confidence interval of +<code>SD.log_alpha</code> includes zero).</p> +<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">fomc_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_alpha)"</code></pre> +<p>Therefore, the model is updated without this random effect, and no +ill-defined parameters remain.</p> +<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">fomc_pH_2</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">fomc_pH</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_alpha"</span><span class="op">)</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">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb32"><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_2</span><span class="op">[[</span><span class="st">"FOMC"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">fomc_pH</span>, <span class="va">fomc_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["FOMC", "const"]] 5 783.25 787.71 -386.63 +fomc_pH_2 6 767.49 772.83 -377.75 17.762 1 2.503e-05 *** +fomc_pH 7 770.07 776.30 -378.04 0.000 1 1 +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>Model comparison indicates that including pH dependence significantly +improves the fit, and that the reduced model with covariate influence +results in the most preferable FOMC fit.</p> +<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.05</td> +<td align="right">90.98</td> +<td align="right">95.13</td> +</tr> +<tr class="even"> +<td align="left">log_alpha</td> +<td align="right">-2.91</td> +<td align="right">-4.18</td> +<td align="right">-1.63</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_alpha)</td> +<td align="right">0.66</td> +<td align="right">0.44</td> +<td align="right">0.87</td> +</tr> +<tr class="even"> +<td align="left">log_beta</td> +<td align="right">3.95</td> +<td align="right">3.29</td> +<td align="right">4.62</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.98</td> +<td align="right">4.28</td> +<td align="right">5.68</td> +</tr> +<tr class="even"> +<td align="left">SD.log_beta</td> +<td align="right">0.40</td> +<td align="right">0.26</td> +<td align="right">0.54</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_files/figure-html/unnamed-chunk-14-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back +meso 17.30248 82.91343 24.95943</code></pre> +<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fomc_pH_2</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back +meso 6.986239 27.02927 8.136621</code></pre> +</div> +<div class="section level3"> +<h3 id="dfop">DFOP<a class="anchor" aria-label="anchor" href="#dfop"></a> +</h3> +<p>In the DFOP fits without covariate effects, random effects for two +degradation parameters (<code>k2</code> and <code>g</code>) were +identifiable.</p> +<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.61</td> +<td align="right">91.58</td> +<td align="right">95.63</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-1.53</td> +<td align="right">-2.27</td> +<td align="right">-0.79</td> +</tr> +<tr class="odd"> +<td align="left">log_k2</td> +<td align="right">-3.42</td> +<td align="right">-3.73</td> +<td align="right">-3.11</td> +</tr> +<tr class="even"> +<td align="left">g_qlogis</td> +<td align="right">-1.67</td> +<td align="right">-2.57</td> +<td align="right">-0.77</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.74</td> +<td align="right">4.02</td> +<td align="right">5.45</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.60</td> +<td align="right">0.38</td> +<td align="right">0.81</td> +</tr> +<tr class="odd"> +<td align="left">SD.g_qlogis</td> +<td align="right">0.94</td> +<td align="right">0.33</td> +<td align="right">1.54</td> +</tr> +</tbody> +</table> +<p>A fit with pH dependent degradation parameters was obtained by +excluding the same random effects as in the refined DFOP fit without +covariate influence, and including covariate models for the two +identifiable parameters <code>k2</code> and <code>g</code>.</p> +<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">g_qlogis</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<p>The corresponding parameters for the influence of soil pH are +<code>beta_pH(log_k2)</code> for the influence of soil pH on +<code>k2</code>, and <code>beta_pH(g_qlogis)</code> for its influence on +<code>g</code>.</p> +<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">dfop_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">92.84</td> +<td align="right">90.85</td> +<td align="right">94.84</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-2.82</td> +<td align="right">-3.09</td> +<td align="right">-2.54</td> +</tr> +<tr class="odd"> +<td align="left">log_k2</td> +<td align="right">-11.48</td> +<td align="right">-15.32</td> +<td align="right">-7.64</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">1.31</td> +<td align="right">0.69</td> +<td align="right">1.92</td> +</tr> +<tr class="odd"> +<td align="left">g_qlogis</td> +<td align="right">3.13</td> +<td align="right">0.47</td> +<td align="right">5.80</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(g_qlogis)</td> +<td align="right">-0.57</td> +<td align="right">-1.04</td> +<td align="right">-0.09</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.96</td> +<td align="right">4.26</td> +<td align="right">5.65</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.76</td> +<td align="right">0.47</td> +<td align="right">1.05</td> +</tr> +<tr class="odd"> +<td align="left">SD.g_qlogis</td> +<td align="right">0.01</td> +<td align="right">-9.96</td> +<td align="right">9.97</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">dfop_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(g_qlogis)"</code></pre> +<p>Confidence intervals for neither of them include zero, indicating a +significant difference from zero. However, the random effect for +<code>g</code> is now ill-defined. The fit is updated without this +ill-defined random effect.</p> +<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_2</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">dfop_pH</span>,</span> +<span> no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span>, <span class="st">"g_qlogis"</span><span class="op">)</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">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "beta_pH(g_qlogis)"</code></pre> +<p>Now, the slope parameter for the pH effect on <code>g</code> is +ill-defined. Therefore, another attempt is made without the +corresponding covariate model.</p> +<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_3</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">dfop_pH_3</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(g_qlogis)"</code></pre> +<p>As the random effect for <code>g</code> is again ill-defined, the fit +is repeated without it.</p> +<div class="sourceCode" id="cb49"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_4</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">dfop_pH_3</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span>, <span class="st">"g_qlogis"</span><span class="op">)</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">dfop_pH_4</span><span class="op">)</span></span></code></pre></div> +<p>While no ill-defined parameters remain, model comparison suggests +that the previous model <code>dfop_pH_2</code> with two pH dependent +parameters is preferable, based on information criteria as well as based +on the likelihood ratio test.</p> +<div class="sourceCode" id="cb50"><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_2</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dfop_pH</span>, <span class="va">dfop_pH_2</span>, <span class="va">dfop_pH_3</span>, <span class="va">dfop_pH_4</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik +f_saem_2[["DFOP", "const"]] 7 782.94 789.18 -384.47 +dfop_pH_4 7 767.35 773.58 -376.68 +dfop_pH_2 8 765.14 772.26 -374.57 +dfop_pH_3 8 769.00 776.12 -376.50 +dfop_pH 9 769.10 777.11 -375.55</code></pre> +<div class="sourceCode" id="cb52"><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">dfop_pH_2</span>, <span class="va">dfop_pH_4</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +dfop_pH_4 7 767.35 773.58 -376.68 +dfop_pH_2 8 765.14 772.26 -374.57 4.2153 1 0.04006 * +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>When focussing on parameter identifiability using the test if the +confidence interval includes zero, <code>dfop_pH_4</code> would still be +the preferred model. However, it should be kept in mind that parameter +confidence intervals are constructed using a simple linearisation of the +likelihood. As the confidence interval of the random effect for +<code>g</code> only marginally includes zero, it is suggested that this +is acceptable, and that <code>dfop_pH_2</code> can be considered the +most preferable model.</p> +<div class="sourceCode" id="cb54"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_files/figure-html/unnamed-chunk-19-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb55"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.36876 73.51841 22.13125 4.191901 23.98672</code></pre> +<div class="sourceCode" id="cb57"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.346428 28.34437 8.532507 4.191901 8.753618</code></pre> +</div> +<div class="section level3"> +<h3 id="sforb">SFORB<a class="anchor" aria-label="anchor" href="#sforb"></a> +</h3> +<div class="sourceCode" id="cb59"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sforb_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"SFORB"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_free_0"</span>, <span class="st">"log_k_meso_free_bound"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso_free</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k_meso_bound_free</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb60"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sforb_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_free_0</td> +<td align="right">93.42</td> +<td align="right">91.32</td> +<td align="right">95.52</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free</td> +<td align="right">-5.37</td> +<td align="right">-6.94</td> +<td align="right">-3.81</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso_free)</td> +<td align="right">0.42</td> +<td align="right">0.18</td> +<td align="right">0.67</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free_bound</td> +<td align="right">-3.49</td> +<td align="right">-4.92</td> +<td align="right">-2.05</td> +</tr> +<tr class="odd"> +<td align="left">log_k_meso_bound_free</td> +<td align="right">-9.98</td> +<td align="right">-19.22</td> +<td align="right">-0.74</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(log_k_meso_bound_free)</td> +<td align="right">1.23</td> +<td align="right">-0.21</td> +<td align="right">2.67</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.90</td> +<td align="right">4.18</td> +<td align="right">5.63</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k_meso_free</td> +<td align="right">0.35</td> +<td align="right">0.23</td> +<td align="right">0.47</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso_bound_free</td> +<td align="right">0.13</td> +<td align="right">-1.95</td> +<td align="right">2.20</td> +</tr> +</tbody> +</table> +<p>The confidence interval of +<code>beta_pH(log_k_meso_bound_free)</code> includes zero, indicating +that the influence of soil pH on <code>k_meso_bound_free</code> cannot +reliably be quantified. Also, the confidence interval for the random +effect on this parameter (<code>SD.log_k_meso_bound_free</code>) +includes zero.</p> +<p>Using the <code>illparms</code> function, these ill-defined +parameters can be found more conveniently.</p> +<div class="sourceCode" id="cb61"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">sforb_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_k_meso_bound_free)" "beta_pH(log_k_meso_bound_free)"</code></pre> +<p>To remove the ill-defined parameters, a second variant of the SFORB +model with pH influence is fitted. No ill-defined parameters remain.</p> +<div class="sourceCode" id="cb63"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sforb_pH_2</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">sforb_pH</span>,</span> +<span> no_random_effect <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="st">"meso_free_0"</span>, <span class="st">"log_k_meso_free_bound"</span>, <span class="st">"log_k_meso_bound_free"</span><span class="op">)</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso_free</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<p>The model comparison of the SFORB fits includes the refined model +without covariate effect, and both versions of the SFORB fit with +covariate effect.</p> +<div class="sourceCode" id="cb64"><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_2</span><span class="op">[[</span><span class="st">"SFORB"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">sforb_pH</span>, <span class="va">sforb_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["SFORB", "const"]] 7 783.40 789.63 -384.70 +sforb_pH_2 7 770.94 777.17 -378.47 12.4616 0 +sforb_pH 9 768.81 776.83 -375.41 6.1258 2 0.04675 * +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>The first model including pH influence is preferable based on +information criteria and the likelihood ratio test. However, as it is +not fully identifiable, the second model is selected.</p> +<div class="sourceCode" id="cb66"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_free_0</td> +<td align="right">93.32</td> +<td align="right">91.16</td> +<td align="right">95.48</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free</td> +<td align="right">-6.15</td> +<td align="right">-7.43</td> +<td align="right">-4.86</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso_free)</td> +<td align="right">0.54</td> +<td align="right">0.33</td> +<td align="right">0.75</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free_bound</td> +<td align="right">-3.80</td> +<td align="right">-5.20</td> +<td align="right">-2.40</td> +</tr> +<tr class="odd"> +<td align="left">log_k_meso_bound_free</td> +<td align="right">-2.95</td> +<td align="right">-4.26</td> +<td align="right">-1.64</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">5.08</td> +<td align="right">4.38</td> +<td align="right">5.79</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso_free</td> +<td align="right">0.33</td> +<td align="right">0.22</td> +<td align="right">0.45</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb67"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_files/figure-html/unnamed-chunk-25-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb68"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$ff +meso_free + 1 + +$SFORB + meso_b1 meso_b2 meso_g +0.09735824 0.02631699 0.31602120 + +$distimes + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.86549 73.15824 22.02282 7.119554 26.33839</code></pre> +<div class="sourceCode" id="cb70"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sforb_pH_2</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$ff +meso_free + 1 + +$SFORB + meso_b1 meso_b2 meso_g +0.13315233 0.03795988 0.61186191 + +$distimes + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 7.932495 36.93311 11.11797 5.205671 18.26</code></pre> +</div> +<div class="section level3"> +<h3 id="hs">HS<a class="anchor" aria-label="anchor" href="#hs"></a> +</h3> +<div class="sourceCode" id="cb72"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">hs_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"HS"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_0"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k1</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_tb</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb73"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">hs_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.33</td> +<td align="right">91.47</td> +<td align="right">95.19</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-5.81</td> +<td align="right">-7.27</td> +<td align="right">-4.36</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k1)</td> +<td align="right">0.47</td> +<td align="right">0.23</td> +<td align="right">0.72</td> +</tr> +<tr class="even"> +<td align="left">log_k2</td> +<td align="right">-6.80</td> +<td align="right">-8.76</td> +<td align="right">-4.83</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">0.54</td> +<td align="right">0.21</td> +<td align="right">0.87</td> +</tr> +<tr class="even"> +<td align="left">log_tb</td> +<td align="right">3.25</td> +<td align="right">1.25</td> +<td align="right">5.25</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_tb)</td> +<td align="right">-0.10</td> +<td align="right">-0.43</td> +<td align="right">0.23</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">4.49</td> +<td align="right">3.78</td> +<td align="right">5.21</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k1</td> +<td align="right">0.37</td> +<td align="right">0.24</td> +<td align="right">0.51</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.29</td> +<td align="right">0.10</td> +<td align="right">0.48</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_tb</td> +<td align="right">0.25</td> +<td align="right">-0.07</td> +<td align="right">0.57</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb74"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">hs_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_tb)" "beta_pH(log_tb)"</code></pre> +<p>According to the output of the <code>illparms</code> function, the +random effect on the break time <code>tb</code> cannot reliably be +quantified, neither can the influence of soil pH on <code>tb</code>. The +fit is repeated without the corresponding covariate model, and no +ill-defined parameters remain.</p> +<div class="sourceCode" id="cb76"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">hs_pH_2</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">hs_pH</span>, covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k1</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<p>Model comparison confirms that this model is preferable to the fit +without covariate influence, and also to the first version with +covariate influence.</p> +<div class="sourceCode" id="cb77"><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_2</span><span class="op">[[</span><span class="st">"HS"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">hs_pH</span>, <span class="va">hs_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["HS", "const"]] 8 780.08 787.20 -382.04 +hs_pH_2 10 766.47 775.37 -373.23 17.606 2 0.0001503 *** +hs_pH 11 769.80 779.59 -373.90 0.000 1 1.0000000 +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<div class="sourceCode" id="cb79"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.33</td> +<td align="right">91.50</td> +<td align="right">95.15</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-5.68</td> +<td align="right">-7.09</td> +<td align="right">-4.27</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k1)</td> +<td align="right">0.46</td> +<td align="right">0.22</td> +<td align="right">0.69</td> +</tr> +<tr class="even"> +<td align="left">log_k2</td> +<td align="right">-6.61</td> +<td align="right">-8.34</td> +<td align="right">-4.88</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">0.50</td> +<td align="right">0.21</td> +<td align="right">0.79</td> +</tr> +<tr class="even"> +<td align="left">log_tb</td> +<td align="right">2.70</td> +<td align="right">2.33</td> +<td align="right">3.08</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.45</td> +<td align="right">3.74</td> +<td align="right">5.16</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k1</td> +<td align="right">0.36</td> +<td align="right">0.22</td> +<td align="right">0.49</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k2</td> +<td align="right">0.23</td> +<td align="right">0.02</td> +<td align="right">0.43</td> +</tr> +<tr class="even"> +<td align="left">SD.log_tb</td> +<td align="right">0.55</td> +<td align="right">0.25</td> +<td align="right">0.85</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb80"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_files/figure-html/unnamed-chunk-30-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb81"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 14.68725 82.45287 24.82079 14.68725 29.29299</code></pre> +<div class="sourceCode" id="cb83"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">hs_pH_2</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.298536 38.85371 11.69613 8.298536 15.71561</code></pre> +</div> +<div class="section level3"> +<h3 id="comparison-across-parent-models">Comparison across parent models<a class="anchor" aria-label="anchor" href="#comparison-across-parent-models"></a> +</h3> +<p>After model reduction for all models with pH influence, they are +compared with each other.</p> +<div class="sourceCode" id="cb85"><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">sfo_pH</span>, <span class="va">fomc_pH_2</span>, <span class="va">dfop_pH_2</span>, <span class="va">dfop_pH_4</span>, <span class="va">sforb_pH_2</span>, <span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik +sfo_pH 5 783.09 787.54 -386.54 +fomc_pH_2 6 767.49 772.83 -377.75 +dfop_pH_4 7 767.35 773.58 -376.68 +sforb_pH_2 7 770.94 777.17 -378.47 +dfop_pH_2 8 765.14 772.26 -374.57 +hs_pH_2 10 766.47 775.37 -373.23</code></pre> +<p>The DFOP model with pH influence on <code>k2</code> and +<code>g</code> and a random effect only on <code>k2</code> is finally +selected as the best fit.</p> +<p>The endpoints resulting from this model are listed below. Please +refer to the Appendix for a detailed listing.</p> +<div class="sourceCode" id="cb87"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.36876 73.51841 22.13125 4.191901 23.98672</code></pre> +<div class="sourceCode" id="cb89"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span>, covariates <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>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.346428 28.34437 8.532507 4.191901 8.753618</code></pre> +</div> +</div> +<div class="section level2"> +<h2 id="conclusions">Conclusions<a class="anchor" aria-label="anchor" href="#conclusions"></a> +</h2> +<p>These evaluations demonstrate that covariate effects can be included +for all types of parent degradation models. These models can then be +further refined to make them fully identifiable.</p> +</div> +<div class="section level2"> +<h2 id="appendix">Appendix<a class="anchor" aria-label="anchor" href="#appendix"></a> +</h2> +<div class="section level3"> +<h3 id="hierarchical-fit-listings">Hierarchical fit listings<a class="anchor" aria-label="anchor" href="#hierarchical-fit-listings"></a> +</h3> +<div class="section level4"> +<h4 id="fits-without-covariate-effects">Fits without covariate effects<a class="anchor" aria-label="anchor" href="#fits-without-covariate-effects"></a> +</h4> +<caption> +Hierarchical SFO fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:12:46 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - k_meso * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 0.71 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k_meso + 90.832 -3.192 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k_meso +meso_0 6.752 0.0000 +log_k_meso 0.000 0.9155 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 800 804.5 -395 + +Optimised parameters: + est. lower upper +meso_0 92.0705 89.9917 94.1493 +log_k_meso -3.1641 -3.4286 -2.8996 +a.1 5.4628 4.6421 6.2835 +SD.meso_0 0.0611 -98.3545 98.4767 +SD.log_k_meso 0.5616 0.3734 0.7499 + +Correlation: + meso_0 +log_k_meso 0.1132 + +Random effects: + est. lower upper +SD.meso_0 0.0611 -98.3545 98.4767 +SD.log_k_meso 0.5616 0.3734 0.7499 + +Variance model: + est. lower upper +a.1 5.463 4.642 6.284 + +Backtransformed parameters: + est. lower upper +meso_0 92.07053 89.99172 94.14933 +k_meso 0.04225 0.03243 0.05505 + +Estimated disappearance times: + DT50 DT90 +meso 16.41 54.5 + +</code></pre> +<p></p> +<caption> +Hierarchical FOMC fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:12:46 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 0.842 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.4 793.6 -386.7 + +Optimised parameters: + est. lower upper +meso_0 93.5648 91.42864 95.7009 +log_alpha 0.7645 0.28068 1.2484 +log_beta 3.6597 3.05999 4.2594 +a.1 5.0708 4.29823 5.8435 +SD.meso_0 0.1691 -34.01517 34.3535 +SD.log_alpha 0.3764 0.05834 0.6945 +SD.log_beta 0.3903 -0.06074 0.8414 + +Correlation: + meso_0 log_lph +log_alpha -0.2839 +log_beta -0.3443 0.8855 + +Random effects: + est. lower upper +SD.meso_0 0.1691 -34.01517 34.3535 +SD.log_alpha 0.3764 0.05834 0.6945 +SD.log_beta 0.3903 -0.06074 0.8414 + +Variance model: + est. lower upper +a.1 5.071 4.298 5.843 + +Backtransformed parameters: + est. lower upper +meso_0 93.565 91.429 95.701 +alpha 2.148 1.324 3.485 +beta 38.850 21.327 70.770 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 14.8 74.64 22.47 + +</code></pre> +<p></p> +<caption> +Hierarchical DFOP fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:12:47 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.168 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.6 795.6 -384.8 + +Optimised parameters: + est. lower upper +meso_0 93.6684 91.63599 95.7008 +log_k1 -1.7354 -2.61433 -0.8565 +log_k2 -3.4015 -3.73323 -3.0697 +g_qlogis -1.6341 -2.66133 -0.6069 +a.1 4.7803 4.01269 5.5479 +SD.meso_0 0.1661 -30.97086 31.3031 +SD.log_k1 0.1127 -2.59680 2.8223 +SD.log_k2 0.6394 0.41499 0.8638 +SD.g_qlogis 0.8166 0.09785 1.5353 + +Correlation: + meso_0 log_k1 log_k2 +log_k1 0.1757 +log_k2 0.0199 0.2990 +g_qlogis 0.0813 -0.7431 -0.3826 + +Random effects: + est. lower upper +SD.meso_0 0.1661 -30.97086 31.3031 +SD.log_k1 0.1127 -2.59680 2.8223 +SD.log_k2 0.6394 0.41499 0.8638 +SD.g_qlogis 0.8166 0.09785 1.5353 + +Variance model: + est. lower upper +a.1 4.78 4.013 5.548 + +Backtransformed parameters: + est. lower upper +meso_0 93.66841 91.63599 95.70082 +k1 0.17633 0.07322 0.42466 +k2 0.03332 0.02392 0.04643 +g 0.16327 0.06529 0.35277 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 16.04 63.75 19.19 3.931 20.8 + +</code></pre> +<p></p> +<caption> +Hierarchical SFORB fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:12:47 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.256 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.4 795.4 -384.7 + +Optimised parameters: + est. lower upper +meso_free_0 93.6285 91.6262 95.631 +log_k_meso_free -2.8314 -3.1375 -2.525 +log_k_meso_free_bound -3.2213 -4.4695 -1.973 +log_k_meso_bound_free -2.4246 -3.5668 -1.282 +a.1 4.7372 3.9542 5.520 +SD.meso_free_0 0.1634 -32.7769 33.104 +SD.log_k_meso_free 0.4885 0.3080 0.669 +SD.log_k_meso_free_bound 0.2876 -1.7955 2.371 +SD.log_k_meso_bound_free 0.9942 0.2181 1.770 + +Correlation: + ms_fr_0 lg_k_m_ lg_k_ms_f_ +log_k_meso_free 0.2332 +log_k_meso_free_bound 0.1100 0.5964 +log_k_meso_bound_free -0.0413 0.3697 0.8025 + +Random effects: + est. lower upper +SD.meso_free_0 0.1634 -32.7769 33.104 +SD.log_k_meso_free 0.4885 0.3080 0.669 +SD.log_k_meso_free_bound 0.2876 -1.7955 2.371 +SD.log_k_meso_bound_free 0.9942 0.2181 1.770 + +Variance model: + est. lower upper +a.1 4.737 3.954 5.52 + +Backtransformed parameters: + est. lower upper +meso_free_0 93.62849 91.62622 95.63075 +k_meso_free 0.05893 0.04339 0.08004 +k_meso_free_bound 0.03990 0.01145 0.13903 +k_meso_bound_free 0.08851 0.02825 0.27736 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g +0.15333 0.03402 0.20881 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 14.79 60.81 18.3 4.521 20.37 + +</code></pre> +<p></p> +<caption> +Hierarchical HS fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:12:48 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.653 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 781.9 789.9 -382 + +Optimised parameters: + est. lower upper +meso_0 93.34242 91.4730 95.2118 +log_k1 -2.77312 -3.0826 -2.4637 +log_k2 -3.61854 -3.8430 -3.3941 +log_tb 2.00266 1.3357 2.6696 +a.1 4.47693 3.7059 5.2479 +SD.meso_0 0.07963 -63.1661 63.3253 +SD.log_k1 0.47817 0.2467 0.7097 +SD.log_k2 0.39216 0.2137 0.5706 +SD.log_tb 0.94683 0.4208 1.4728 + +Correlation: + meso_0 log_k1 log_k2 +log_k1 0.1627 +log_k2 0.0063 -0.0301 +log_tb 0.0083 -0.3931 -0.1225 + +Random effects: + est. lower upper +SD.meso_0 0.07963 -63.1661 63.3253 +SD.log_k1 0.47817 0.2467 0.7097 +SD.log_k2 0.39216 0.2137 0.5706 +SD.log_tb 0.94683 0.4208 1.4728 + +Variance model: + est. lower upper +a.1 4.477 3.706 5.248 + +Backtransformed parameters: + est. lower upper +meso_0 93.34242 91.47303 95.21181 +k1 0.06247 0.04584 0.08512 +k2 0.02682 0.02143 0.03357 +tb 7.40872 3.80282 14.43376 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 16 76 22.88 11.1 25.84 + +</code></pre> +<p></p> +</div> +<div class="section level4"> +<h4 id="fits-with-covariate-effects">Fits with covariate effects<a class="anchor" aria-label="anchor" href="#fits-with-covariate-effects"></a> +</h4> +<caption> +Hierarchichal SFO fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:00 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - k_meso * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.343 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k_meso + 90.832 -3.192 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k_meso +meso_0 6.752 0.0000 +log_k_meso 0.000 0.9155 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 783.1 787.5 -386.5 + +Optimised parameters: + est. lower upper +meso_0 91.3481 89.2688 93.4275 +log_k_meso -6.6614 -7.9715 -5.3514 +beta_pH(log_k_meso) 0.5871 0.3684 0.8059 +a.1 5.4750 4.7085 6.2415 +SD.log_k_meso 0.3471 0.2258 0.4684 + +Correlation: + meso_0 lg_k_ms +log_k_meso 0.0414 +beta_pH(log_k_meso) -0.0183 -0.9917 + +Random effects: + est. lower upper +SD.log_k_meso 0.3471 0.2258 0.4684 + +Variance model: + est. lower upper +a.1 5.475 4.709 6.242 + +Backtransformed parameters: + est. lower upper +meso_0 91.348139 8.927e+01 93.427476 +k_meso 0.001279 3.452e-04 0.004741 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 +meso 18.52 61.52 + +</code></pre> +<p></p> +<caption> +Hierarchichal FOMC fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:03 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.897 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 770.1 776.3 -378 + +Optimised parameters: + est. lower upper +meso_0 92.840646 90.750461 94.9308 +log_alpha -2.206602 -3.494546 -0.9187 +beta_pH(log_alpha) 0.577505 0.369805 0.7852 +log_beta 4.214099 3.438851 4.9893 +a.1 5.027768 4.322028 5.7335 +SD.log_alpha 0.004034 -23.766993 23.7751 +SD.log_beta 0.374640 0.009252 0.7400 + +Correlation: + meso_0 log_lph bt_H(_) +log_alpha -0.0865 +beta_pH(log_alpha) -0.0789 -0.8704 +log_beta -0.3544 0.3302 0.1628 + +Random effects: + est. lower upper +SD.log_alpha 0.004034 -23.766993 23.78 +SD.log_beta 0.374640 0.009252 0.74 + +Variance model: + est. lower upper +a.1 5.028 4.322 5.734 + +Backtransformed parameters: + est. lower upper +meso_0 92.8406 90.75046 94.9308 +alpha 0.1101 0.03036 0.3991 +beta 67.6332 31.15113 146.8404 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 17.28 76.37 22.99 + +</code></pre> +<p></p> +<caption> +Refined hierarchichal FOMC fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:08 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 4.184 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 767.5 772.8 -377.7 + +Optimised parameters: + est. lower upper +meso_0 93.0536 90.9771 95.1300 +log_alpha -2.9054 -4.1803 -1.6304 +beta_pH(log_alpha) 0.6590 0.4437 0.8744 +log_beta 3.9549 3.2860 4.6239 +a.1 4.9784 4.2815 5.6754 +SD.log_beta 0.4019 0.2632 0.5406 + +Correlation: + meso_0 log_lph bt_H(_) +log_alpha -0.0397 +beta_pH(log_alpha) -0.0899 -0.9146 +log_beta -0.3473 0.2038 0.1919 + +Random effects: + est. lower upper +SD.log_beta 0.4019 0.2632 0.5406 + +Variance model: + est. lower upper +a.1 4.978 4.281 5.675 + +Backtransformed parameters: + est. lower upper +meso_0 93.05359 90.97713 95.1300 +alpha 0.05473 0.01529 0.1958 +beta 52.19251 26.73597 101.8874 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 17.3 82.91 24.96 + +</code></pre> +<p></p> +<caption> +Hierarchichal DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:11 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 2.18 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 769.1 777.1 -375.5 + +Optimised parameters: + est. lower upper +meso_0 92.843344 90.8464 94.84028 +log_k1 -2.815685 -3.0888 -2.54261 +log_k2 -11.479779 -15.3203 -7.63923 +beta_pH(log_k2) 1.308417 0.6948 1.92203 +g_qlogis 3.133036 0.4657 5.80035 +beta_pH(g_qlogis) -0.565988 -1.0394 -0.09262 +a.1 4.955518 4.2597 5.65135 +SD.log_k2 0.758963 0.4685 1.04943 +SD.g_qlogis 0.005215 -9.9561 9.96656 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) g_qlogs +log_k1 0.2706 +log_k2 -0.0571 0.1096 +beta_pH(log_k2) 0.0554 -0.1291 -0.9937 +g_qlogis -0.1125 -0.5062 -0.1305 0.1294 +beta_pH(g_qlogis) 0.1267 0.4226 0.0419 -0.0438 -0.9864 + +Random effects: + est. lower upper +SD.log_k2 0.758963 0.4685 1.049 +SD.g_qlogis 0.005215 -9.9561 9.967 + +Variance model: + est. lower upper +a.1 4.956 4.26 5.651 + +Backtransformed parameters: + est. lower upper +meso_0 9.284e+01 9.085e+01 9.484e+01 +k1 5.986e-02 4.556e-02 7.866e-02 +k2 1.034e-05 2.221e-07 4.812e-04 +g 9.582e-01 6.144e-01 9.970e-01 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 20.23 88.45 26.62 11.58 36.23 + +</code></pre> +<p></p> +<caption> +Refined hierarchical DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:14 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 2.424 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 765.1 772.3 -374.6 + +Optimised parameters: + est. lower upper +meso_0 93.3333 91.2427 95.42394 +log_k1 -1.7997 -2.9124 -0.68698 +log_k2 -8.1810 -10.1819 -6.18008 +beta_pH(log_k2) 0.8064 0.4903 1.12257 +g_qlogis 3.3513 -1.1792 7.88182 +beta_pH(g_qlogis) -0.8672 -1.7661 0.03177 +a.1 4.9158 4.2277 5.60390 +SD.log_k2 0.3946 0.2565 0.53281 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) g_qlogs +log_k1 0.1730 +log_k2 0.0442 0.5370 +beta_pH(log_k2) -0.0392 -0.4880 -0.9923 +g_qlogis -0.1536 0.1431 -0.1129 0.1432 +beta_pH(g_qlogis) 0.1504 -0.3151 -0.0196 -0.0212 -0.9798 + +Random effects: + est. lower upper +SD.log_k2 0.3946 0.2565 0.5328 + +Variance model: + est. lower upper +a.1 4.916 4.228 5.604 + +Backtransformed parameters: + est. lower upper +meso_0 9.333e+01 9.124e+01 95.42394 +k1 1.654e-01 5.435e-02 0.50309 +k2 2.799e-04 3.785e-05 0.00207 +g 9.661e-01 2.352e-01 0.99962 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.37 73.52 22.13 4.192 23.99 + +</code></pre> +<p></p> +<caption> +Further refined hierarchical DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:23 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 3.211 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 767.4 773.6 -376.7 + +Optimised parameters: + est. lower upper +meso_0 93.3011 91.1905 95.4118 +log_k1 -2.1487 -2.7607 -1.5367 +log_k2 -8.1039 -10.4225 -5.7853 +beta_pH(log_k2) 0.7821 0.4126 1.1517 +g_qlogis -1.0373 -1.9337 -0.1409 +a.1 5.0095 4.3082 5.7108 +SD.log_k2 0.4622 0.3009 0.6235 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) +log_k1 0.2179 +log_k2 0.0337 0.5791 +beta_pH(log_k2) -0.0326 -0.5546 -0.9932 +g_qlogis 0.0237 -0.8479 -0.6571 0.6123 + +Random effects: + est. lower upper +SD.log_k2 0.4622 0.3009 0.6235 + +Variance model: + est. lower upper +a.1 5.009 4.308 5.711 + +Backtransformed parameters: + est. lower upper +meso_0 9.330e+01 9.119e+01 95.411751 +k1 1.166e-01 6.325e-02 0.215084 +k2 3.024e-04 2.975e-05 0.003072 +g 2.617e-01 1.263e-01 0.464832 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 17.09 73.67 22.18 5.943 25.54 + +</code></pre> +<p></p> +<caption> +Hierarchichal SFORB fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:26 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 2.649 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 768.8 776.8 -375.4 + +Optimised parameters: + est. lower upper +meso_free_0 93.4204 91.3213 95.5195 +log_k_meso_free -5.3742 -6.9366 -3.8117 +beta_pH(log_k_meso_free) 0.4232 0.1769 0.6695 +log_k_meso_free_bound -3.4889 -4.9243 -2.0535 +log_k_meso_bound_free -9.9797 -19.2232 -0.7362 +beta_pH(log_k_meso_bound_free) 1.2290 -0.2107 2.6687 +a.1 4.9031 4.1795 5.6268 +SD.log_k_meso_free 0.3454 0.2252 0.4656 +SD.log_k_meso_bound_free 0.1277 -1.9459 2.2012 + +Correlation: + ms_fr_0 lg_k_m_ b_H(___) lg_k_ms_f_ lg_k_ms_b_ +log_k_meso_free 0.1493 +beta_pH(log_k_meso_free) -0.0930 -0.9854 +log_k_meso_free_bound 0.2439 0.4621 -0.3492 +log_k_meso_bound_free 0.2188 0.1292 -0.0339 0.7287 +beta_pH(log_k_meso_bound_free) -0.2216 -0.0797 -0.0111 -0.6566 -0.9934 + +Random effects: + est. lower upper +SD.log_k_meso_free 0.3454 0.2252 0.4656 +SD.log_k_meso_bound_free 0.1277 -1.9459 2.2012 + +Variance model: + est. lower upper +a.1 4.903 4.18 5.627 + +Backtransformed parameters: + est. lower upper +meso_free_0 9.342e+01 9.132e+01 95.51946 +k_meso_free 4.635e-03 9.716e-04 0.02211 +k_meso_free_bound 3.054e-02 7.268e-03 0.12829 +k_meso_bound_free 4.633e-05 4.482e-09 0.47894 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g + 0.1121 0.0256 0.3148 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.42 75.2 22.64 6.185 27.08 + +</code></pre> +<p> </p> +<caption> +Refined hierarchichal SFORB fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:30 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 3.186 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 770.9 777.2 -378.5 + +Optimised parameters: + est. lower upper +meso_free_0 93.3196 91.1633 95.4760 +log_k_meso_free -6.1460 -7.4306 -4.8614 +beta_pH(log_k_meso_free) 0.5435 0.3329 0.7542 +log_k_meso_free_bound -3.8001 -5.2027 -2.3975 +log_k_meso_bound_free -2.9462 -4.2565 -1.6359 +a.1 5.0825 4.3793 5.7856 +SD.log_k_meso_free 0.3338 0.2175 0.4502 + +Correlation: + ms_fr_0 lg_k_m_ b_H(___ lg_k_ms_f_ +log_k_meso_free 0.1086 +beta_pH(log_k_meso_free) -0.0426 -0.9821 +log_k_meso_free_bound 0.2513 0.1717 -0.0409 +log_k_meso_bound_free 0.1297 0.1171 -0.0139 0.9224 + +Random effects: + est. lower upper +SD.log_k_meso_free 0.3338 0.2175 0.4502 + +Variance model: + est. lower upper +a.1 5.082 4.379 5.786 + +Backtransformed parameters: + est. lower upper +meso_free_0 93.319649 9.116e+01 95.47601 +k_meso_free 0.002142 5.928e-04 0.00774 +k_meso_free_bound 0.022369 5.502e-03 0.09095 +k_meso_bound_free 0.052539 1.417e-02 0.19478 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g +0.09736 0.02632 0.31602 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.87 73.16 22.02 7.12 26.34 + +</code></pre> +<p> </p> +<caption> +Hierarchichal HS fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:32 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.833 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 769.8 779.6 -373.9 + +Optimised parameters: + est. lower upper +meso_0 93.32599 91.4658 95.1862 +log_k1 -5.81463 -7.2710 -4.3583 +beta_pH(log_k1) 0.47472 0.2334 0.7160 +log_k2 -6.79633 -8.7605 -4.8322 +beta_pH(log_k2) 0.54151 0.2124 0.8706 +log_tb 3.24674 1.2470 5.2465 +beta_pH(log_tb) -0.09889 -0.4258 0.2280 +a.1 4.49487 3.7766 5.2132 +SD.log_k1 0.37191 0.2370 0.5068 +SD.log_k2 0.29210 0.0994 0.4848 +SD.log_tb 0.25353 -0.0664 0.5735 + +Correlation: + meso_0 log_k1 b_H(_1) log_k2 b_H(_2) log_tb +log_k1 0.0744 +beta_pH(log_k1) -0.0452 -0.9915 +log_k2 0.0066 -0.0363 0.0376 +beta_pH(log_k2) -0.0071 0.0372 -0.0391 -0.9939 +log_tb -0.0238 -0.1483 0.1362 -0.3836 0.3696 +beta_pH(log_tb) 0.0097 0.1359 -0.1265 0.3736 -0.3653 -0.9905 + +Random effects: + est. lower upper +SD.log_k1 0.3719 0.2370 0.5068 +SD.log_k2 0.2921 0.0994 0.4848 +SD.log_tb 0.2535 -0.0664 0.5735 + +Variance model: + est. lower upper +a.1 4.495 3.777 5.213 + +Backtransformed parameters: + est. lower upper +meso_0 93.325994 9.147e+01 9.519e+01 +k1 0.002984 6.954e-04 1.280e-02 +k2 0.001118 1.568e-04 7.969e-03 +tb 25.706437 3.480e+00 1.899e+02 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 15.65 79.63 23.97 15.16 27.55 + +</code></pre> +<p> </p> +<caption> +Refined hierarchichal HS fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Wed May 14 05:13:35 2025 +Date of summary: Wed May 14 05:13:35 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.852 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 766.5 775.4 -373.2 + +Optimised parameters: + est. lower upper +meso_0 93.3251 91.49823 95.1520 +log_k1 -5.6796 -7.08789 -4.2714 +beta_pH(log_k1) 0.4567 0.22400 0.6894 +log_k2 -6.6083 -8.33839 -4.8781 +beta_pH(log_k2) 0.4982 0.20644 0.7899 +log_tb 2.7040 2.33033 3.0777 +a.1 4.4452 3.73537 5.1551 +SD.log_k1 0.3570 0.22104 0.4930 +SD.log_k2 0.2252 0.01864 0.4318 +SD.log_tb 0.5488 0.24560 0.8521 + +Correlation: + meso_0 log_k1 b_H(_1) log_k2 b_H(_2) +log_k1 0.0740 +beta_pH(log_k1) -0.0453 -0.9912 +log_k2 0.0115 -0.0650 0.0661 +beta_pH(log_k2) -0.0116 0.0649 -0.0667 -0.9936 +log_tb -0.0658 -0.1135 0.0913 -0.1500 0.1210 + +Random effects: + est. lower upper +SD.log_k1 0.3570 0.22104 0.4930 +SD.log_k2 0.2252 0.01864 0.4318 +SD.log_tb 0.5488 0.24560 0.8521 + +Variance model: + est. lower upper +a.1 4.445 3.735 5.155 + +Backtransformed parameters: + est. lower upper +meso_0 93.325134 9.150e+01 95.152036 +k1 0.003415 8.352e-04 0.013962 +k2 0.001349 2.392e-04 0.007611 +tb 14.939247 1.028e+01 21.707445 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 14.69 82.45 24.82 14.69 29.29 + +</code></pre> +<p></p> +</div> +</div> +<div class="section level3"> +<h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> +</h3> +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu +Running under: Debian GNU/Linux 12 (bookworm) + +Matrix products: default +BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 + +locale: + [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C + [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=de_DE.UTF-8 + [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 + [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C + [9] LC_ADDRESS=C LC_TELEPHONE=C +[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C + +time zone: Europe/Berlin +tzcode source: system (glibc) + +attached base packages: +[1] parallel stats graphics grDevices utils datasets methods +[8] base + +other attached packages: +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 + +loaded via a namespace (and not attached): + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.2.1 + [9] scales_1.3.0 textshaping_1.0.0 readxl_1.4.4 yaml_2.3.10 +[13] fastmap_1.2.0 lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 +[17] generics_0.1.3 lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 +[21] tibble_3.2.1 desc_1.4.3 munsell_0.5.1 bslib_0.9.0 +[25] pillar_1.10.1 rlang_1.1.5 cachem_1.1.0 xfun_0.51 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.5.0 mclust_6.1.1 +[37] lifecycle_1.0.4 nlme_3.1-168 vctrs_0.6.5 evaluate_1.0.3 +[41] glue_1.8.0 cellranger_1.1.0 codetools_0.2-20 ragg_1.3.3 +[45] zoo_1.8-13 colorspace_2.1-1 tools_4.5.0 pkgconfig_2.0.3 +[49] htmltools_0.5.8.1</code></pre> +</div> +<div class="section level3"> +<h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> +</h3> +<pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> +<pre><code>MemTotal: 64927780 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<h1>Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</h1> + <h4 data-toc-skip class="author">Johannes +Ranke</h4> + + <h4 data-toc-skip class="date">Last change 13 May 2025 +(rebuilt 2025-05-13)</h4> + + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/mesotrione_parent_2023_prebuilt.rmd" class="external-link"><code>vignettes/web_only/mesotrione_parent_2023_prebuilt.rmd</code></a></small> + <div class="d-none name"><code>mesotrione_parent_2023_prebuilt.rmd</code></div> + </div> + + + +<div class="section level2"> +<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> +</h2> +<p>The purpose of this document is to test demonstrate how nonlinear +hierarchical models (NLHM) based on the parent degradation models SFO, +FOMC, DFOP and HS can be fitted with the mkin package, also considering +the influence of covariates like soil pH on different degradation +parameters. Because in some other case studies, the SFORB +parameterisation of biexponential decline has shown some advantages over +the DFOP parameterisation, SFORB was included in the list of tested +models as well.</p> +<p>The mkin package is used in version 1.2.10, which is contains the +functions that were used for the evaluations. The <code>saemix</code> +package is used as a backend for fitting the NLHM, but is also loaded to +make the convergence plot function available.</p> +<p>This document is processed with the <code>knitr</code> package, which +also provides the <code>kable</code> function that is used to improve +the display of tabular data in R markdown documents. For parallel +processing, the <code>parallel</code> package is used.</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="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://yihui.org/knitr/" class="external-link">knitr</a></span><span class="op">)</span></span> +<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">saemix</span><span class="op">)</span></span> +<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="va">n_cores</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">detectCores</a></span><span class="op">(</span><span class="op">)</span></span> +<span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Sys.info.html" class="external-link">Sys.info</a></span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="st">"sysname"</span><span class="op">]</span> <span class="op">==</span> <span class="st">"Windows"</span><span class="op">)</span> <span class="op">{</span></span> +<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="va">n_cores</span><span class="op">)</span></span> +<span><span class="op">}</span> <span class="kw">else</span> <span class="op">{</span></span> +<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">makeForkCluster</a></span><span class="op">(</span><span class="va">n_cores</span><span class="op">)</span></span> +<span><span class="op">}</span></span></code></pre></div> +<div class="section level3"> +<h3 id="test-data">Test data<a class="anchor" aria-label="anchor" href="#test-data"></a> +</h3> +<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">data_file</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.file.html" class="external-link">system.file</a></span><span class="op">(</span></span> +<span> <span class="st">"testdata"</span>, <span class="st">"mesotrione_soil_efsa_2016.xlsx"</span>, package <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span></span> +<span><span class="va">meso_ds</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/read_spreadsheet.html">read_spreadsheet</a></span><span class="op">(</span><span class="va">data_file</span>, parent_only <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<p>The following tables show the covariate data and the 18 datasets that +were read in from the spreadsheet file.</p> +<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">pH</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attr.html" class="external-link">attr</a></span><span class="op">(</span><span class="va">meso_ds</span>, <span class="st">"covariates"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="va">pH</span>, caption <span class="op">=</span> <span class="st">"Covariate data"</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<caption>Covariate data</caption> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">pH</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">Richmond</td> +<td align="right">6.2</td> +</tr> +<tr class="even"> +<td align="left">Richmond 2</td> +<td align="right">6.2</td> +</tr> +<tr class="odd"> +<td align="left">ERTC</td> +<td align="right">6.4</td> +</tr> +<tr class="even"> +<td align="left">Toulouse</td> +<td align="right">7.7</td> +</tr> +<tr class="odd"> +<td align="left">Picket Piece</td> +<td align="right">7.1</td> +</tr> +<tr class="even"> +<td align="left">721</td> +<td align="right">5.6</td> +</tr> +<tr class="odd"> +<td align="left">722</td> +<td align="right">5.7</td> +</tr> +<tr class="even"> +<td align="left">723</td> +<td align="right">5.4</td> +</tr> +<tr class="odd"> +<td align="left">724</td> +<td align="right">4.8</td> +</tr> +<tr class="even"> +<td align="left">725</td> +<td align="right">5.8</td> +</tr> +<tr class="odd"> +<td align="left">727</td> +<td align="right">5.1</td> +</tr> +<tr class="even"> +<td align="left">728</td> +<td align="right">5.9</td> +</tr> +<tr class="odd"> +<td align="left">729</td> +<td align="right">5.6</td> +</tr> +<tr class="even"> +<td align="left">730</td> +<td align="right">5.3</td> +</tr> +<tr class="odd"> +<td align="left">731</td> +<td align="right">6.1</td> +</tr> +<tr class="even"> +<td align="left">732</td> +<td align="right">5.0</td> +</tr> +<tr class="odd"> +<td align="left">741</td> +<td align="right">5.7</td> +</tr> +<tr class="even"> +<td align="left">742</td> +<td align="right">7.2</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="kw">for</span> <span class="op">(</span><span class="va">ds_name</span> <span class="kw">in</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">meso_ds</span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span></span> +<span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mkin_long_to_wide.html">mkin_long_to_wide</a></span><span class="op">(</span><span class="va">meso_ds</span><span class="op">[[</span><span class="va">ds_name</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>,</span> +<span> caption <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="va">ds_name</span><span class="op">)</span>,</span> +<span> booktabs <span class="op">=</span> <span class="cn">TRUE</span>, row.names <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="op">}</span></span></code></pre></div> +<table class="table"> +<caption>Dataset Richmond</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">91.00</td> +</tr> +<tr class="even"> +<td align="right">1.179050</td> +<td align="right">86.70</td> +</tr> +<tr class="odd"> +<td align="right">3.537149</td> +<td align="right">73.60</td> +</tr> +<tr class="even"> +<td align="right">7.074299</td> +<td align="right">61.50</td> +</tr> +<tr class="odd"> +<td align="right">10.611448</td> +<td align="right">55.70</td> +</tr> +<tr class="even"> +<td align="right">15.327647</td> +<td align="right">47.70</td> +</tr> +<tr class="odd"> +<td align="right">17.685747</td> +<td align="right">39.50</td> +</tr> +<tr class="even"> +<td align="right">24.760046</td> +<td align="right">29.80</td> +</tr> +<tr class="odd"> +<td align="right">35.371494</td> +<td align="right">19.60</td> +</tr> +<tr class="even"> +<td align="right">68.384889</td> +<td align="right">5.67</td> +</tr> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">97.90</td> +</tr> +<tr class="even"> +<td align="right">1.179050</td> +<td align="right">96.40</td> +</tr> +<tr class="odd"> +<td align="right">3.537149</td> +<td align="right">89.10</td> +</tr> +<tr class="even"> +<td align="right">7.074299</td> +<td align="right">74.40</td> +</tr> +<tr class="odd"> +<td align="right">10.611448</td> +<td align="right">57.40</td> +</tr> +<tr class="even"> +<td align="right">15.327647</td> +<td align="right">46.30</td> +</tr> +<tr class="odd"> +<td align="right">18.864797</td> +<td align="right">35.50</td> +</tr> +<tr class="even"> +<td align="right">27.118146</td> +<td align="right">27.20</td> +</tr> +<tr class="odd"> +<td align="right">35.371494</td> +<td align="right">19.10</td> +</tr> +<tr class="even"> +<td align="right">74.280138</td> +<td align="right">6.50</td> +</tr> +<tr class="odd"> +<td align="right">108.472582</td> +<td align="right">3.40</td> +</tr> +<tr class="even"> +<td align="right">142.665027</td> +<td align="right">2.20</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Richmond 2</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">96.0</td> +</tr> +<tr class="even"> +<td align="right">2.422004</td> +<td align="right">82.4</td> +</tr> +<tr class="odd"> +<td align="right">5.651343</td> +<td align="right">71.2</td> +</tr> +<tr class="even"> +<td align="right">8.073348</td> +<td align="right">53.1</td> +</tr> +<tr class="odd"> +<td align="right">11.302687</td> +<td align="right">48.5</td> +</tr> +<tr class="even"> +<td align="right">16.954030</td> +<td align="right">33.4</td> +</tr> +<tr class="odd"> +<td align="right">22.605373</td> +<td align="right">24.2</td> +</tr> +<tr class="even"> +<td align="right">45.210746</td> +<td align="right">11.9</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset ERTC</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">99.9</td> +</tr> +<tr class="even"> +<td align="right">2.755193</td> +<td align="right">80.0</td> +</tr> +<tr class="odd"> +<td align="right">6.428782</td> +<td align="right">42.1</td> +</tr> +<tr class="even"> +<td align="right">9.183975</td> +<td align="right">50.1</td> +</tr> +<tr class="odd"> +<td align="right">12.857565</td> +<td align="right">28.4</td> +</tr> +<tr class="even"> +<td align="right">19.286347</td> +<td align="right">39.8</td> +</tr> +<tr class="odd"> +<td align="right">25.715130</td> +<td align="right">29.9</td> +</tr> +<tr class="even"> +<td align="right">51.430259</td> +<td align="right">2.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Toulouse</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">96.8</td> +</tr> +<tr class="even"> +<td align="right">2.897983</td> +<td align="right">63.3</td> +</tr> +<tr class="odd"> +<td align="right">6.761960</td> +<td align="right">22.3</td> +</tr> +<tr class="even"> +<td align="right">9.659942</td> +<td align="right">16.6</td> +</tr> +<tr class="odd"> +<td align="right">13.523919</td> +<td align="right">16.1</td> +</tr> +<tr class="even"> +<td align="right">20.285879</td> +<td align="right">17.2</td> +</tr> +<tr class="odd"> +<td align="right">27.047838</td> +<td align="right">1.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset Picket Piece</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">102.0</td> +</tr> +<tr class="even"> +<td align="right">2.841195</td> +<td align="right">73.7</td> +</tr> +<tr class="odd"> +<td align="right">6.629454</td> +<td align="right">35.5</td> +</tr> +<tr class="even"> +<td align="right">9.470649</td> +<td align="right">31.8</td> +</tr> +<tr class="odd"> +<td align="right">13.258909</td> +<td align="right">18.0</td> +</tr> +<tr class="even"> +<td align="right">19.888364</td> +<td align="right">3.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 721</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">86.4</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">61.4</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">49.8</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">41.0</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">35.1</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 722</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">52.1</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">37.4</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">21.2</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">14.3</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 723</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">89.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">70.8</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">51.1</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">42.7</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">26.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 724</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.000000</td> +<td align="right">89.4</td> +</tr> +<tr class="even"> +<td align="right">9.008208</td> +<td align="right">65.2</td> +</tr> +<tr class="odd"> +<td align="right">18.016415</td> +<td align="right">55.8</td> +</tr> +<tr class="even"> +<td align="right">27.024623</td> +<td align="right">46.0</td> +</tr> +<tr class="odd"> +<td align="right">36.032831</td> +<td align="right">41.7</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 725</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">89.0</td> +</tr> +<tr class="even"> +<td align="right">10.99058</td> +<td align="right">35.4</td> +</tr> +<tr class="odd"> +<td align="right">21.98116</td> +<td align="right">18.6</td> +</tr> +<tr class="even"> +<td align="right">32.97174</td> +<td align="right">11.6</td> +</tr> +<tr class="odd"> +<td align="right">43.96232</td> +<td align="right">7.6</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 727</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.3</td> +</tr> +<tr class="even"> +<td align="right">10.96104</td> +<td align="right">63.2</td> +</tr> +<tr class="odd"> +<td align="right">21.92209</td> +<td align="right">51.1</td> +</tr> +<tr class="even"> +<td align="right">32.88313</td> +<td align="right">42.0</td> +</tr> +<tr class="odd"> +<td align="right">43.84417</td> +<td align="right">40.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 728</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.8</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">43.6</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">22.0</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">15.9</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">8.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 729</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">91.6</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">60.5</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">43.5</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">28.4</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">20.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 730</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.7</td> +</tr> +<tr class="even"> +<td align="right">11.07446</td> +<td align="right">58.9</td> +</tr> +<tr class="odd"> +<td align="right">22.14893</td> +<td align="right">44.0</td> +</tr> +<tr class="even"> +<td align="right">33.22339</td> +<td align="right">46.0</td> +</tr> +<tr class="odd"> +<td align="right">44.29785</td> +<td align="right">29.3</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 731</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.1</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">64.4</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">45.3</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">33.6</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">23.5</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 732</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">58.2</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">40.1</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">33.1</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">25.8</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 741</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">90.3</td> +</tr> +<tr class="even"> +<td align="right">10.84712</td> +<td align="right">68.7</td> +</tr> +<tr class="odd"> +<td align="right">21.69424</td> +<td align="right">58.0</td> +</tr> +<tr class="even"> +<td align="right">32.54136</td> +<td align="right">52.2</td> +</tr> +<tr class="odd"> +<td align="right">43.38848</td> +<td align="right">48.0</td> +</tr> +</tbody> +</table> +<table class="table"> +<caption>Dataset 742</caption> +<thead><tr class="header"> +<th align="right">time</th> +<th align="right">meso</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="right">0.00000</td> +<td align="right">92.0</td> +</tr> +<tr class="even"> +<td align="right">11.24366</td> +<td align="right">60.9</td> +</tr> +<tr class="odd"> +<td align="right">22.48733</td> +<td align="right">36.2</td> +</tr> +<tr class="even"> +<td align="right">33.73099</td> +<td align="right">18.3</td> +</tr> +<tr class="odd"> +<td align="right">44.97466</td> +<td align="right">8.7</td> +</tr> +</tbody> +</table> +</div> +</div> +<div class="section level2"> +<h2 id="separate-evaluations">Separate evaluations<a class="anchor" aria-label="anchor" href="#separate-evaluations"></a> +</h2> +<p>In order to obtain suitable starting parameters for the NLHM fits, +separate fits of the five models to the data for each soil are generated +using the <code>mmkin</code> function from the mkin package. In a first +step, constant variance is assumed. Convergence is checked with the +<code>status</code> function.</p> +<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">deg_mods</span> <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="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"SFORB"</span>, <span class="st">"HS"</span><span class="op">)</span></span> +<span><span class="va">f_sep_const</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span></span> +<span> <span class="va">deg_mods</span>,</span> +<span> <span class="va">meso_ds</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"const"</span>,</span> +<span> cluster <span class="op">=</span> <span class="va">cl</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">Richmond</th> +<th align="left">Richmond 2</th> +<th align="left">ERTC</th> +<th align="left">Toulouse</th> +<th align="left">Picket Piece</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">18</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="10%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">721</th> +<th align="left">722</th> +<th align="left">723</th> +<th align="left">724</th> +<th align="left">725</th> +<th align="left">727</th> +<th align="left">728</th> +<th align="left">729</th> +<th align="left">730</th> +<th align="left">731</th> +<th align="left">732</th> +<th align="left">741</th> +<th align="left">742</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>In the tables above, OK indicates convergence and C indicates failure +to converge. Most separate fits with constant variance converged, with +the exception of two FOMC fits, one SFORB fit and one HS fit.</p> +<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_sep_tc</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_sep_const</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_tc</span><span class="op">[</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">Richmond</th> +<th align="left">Richmond 2</th> +<th align="left">ERTC</th> +<th align="left">Toulouse</th> +<th align="left">Picket Piece</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_sep_tc</span><span class="op">[</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">18</span><span class="op">]</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="10%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +<col width="6%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">721</th> +<th align="left">722</th> +<th align="left">723</th> +<th align="left">724</th> +<th align="left">725</th> +<th align="left">727</th> +<th align="left">728</th> +<th align="left">729</th> +<th align="left">730</th> +<th align="left">731</th> +<th align="left">732</th> +<th align="left">741</th> +<th align="left">742</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">C</td> +<td align="left">OK</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>With the two-component error model, the set of fits that did not +converge is larger, with convergence problems appearing for a number of +non-SFO fits.</p> +</div> +<div class="section level2"> +<h2 id="hierarchical-models-without-covariate">Hierarchical models without covariate<a class="anchor" aria-label="anchor" href="#hierarchical-models-without-covariate"></a> +</h2> +<p>The following code fits hierarchical kinetic models for the ten +combinations of the five different degradation models with the two +different error models in parallel.</p> +<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_1</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mhmkin.html">mhmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_sep_const</span>, <span class="va">f_sep_tc</span><span class="op">)</span>, cluster <span class="op">=</span> <span class="va">cl</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>All fits terminate without errors (status OK).</p> +<div class="sourceCode" id="cb12"><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_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">npar</th> +<th align="right">AIC</th> +<th align="right">BIC</th> +<th align="right">Lik</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO const</td> +<td align="right">5</td> +<td align="right">800.0</td> +<td align="right">804.5</td> +<td align="right">-395.0</td> +</tr> +<tr class="even"> +<td align="left">SFO tc</td> +<td align="right">6</td> +<td align="right">801.9</td> +<td align="right">807.2</td> +<td align="right">-394.9</td> +</tr> +<tr class="odd"> +<td align="left">FOMC const</td> +<td align="right">7</td> +<td align="right">787.4</td> +<td align="right">793.6</td> +<td align="right">-386.7</td> +</tr> +<tr class="even"> +<td align="left">FOMC tc</td> +<td align="right">8</td> +<td align="right">788.9</td> +<td align="right">796.1</td> +<td align="right">-386.5</td> +</tr> +<tr class="odd"> +<td align="left">DFOP const</td> +<td align="right">9</td> +<td align="right">787.6</td> +<td align="right">795.6</td> +<td align="right">-384.8</td> +</tr> +<tr class="even"> +<td align="left">SFORB const</td> +<td align="right">9</td> +<td align="right">787.4</td> +<td align="right">795.4</td> +<td align="right">-384.7</td> +</tr> +<tr class="odd"> +<td align="left">HS const</td> +<td align="right">9</td> +<td align="right">781.9</td> +<td align="right">789.9</td> +<td align="right">-382.0</td> +</tr> +<tr class="even"> +<td align="left">DFOP tc</td> +<td align="right">10</td> +<td align="right">787.4</td> +<td align="right">796.3</td> +<td align="right">-383.7</td> +</tr> +<tr class="odd"> +<td align="left">SFORB tc</td> +<td align="right">10</td> +<td align="right">795.8</td> +<td align="right">804.7</td> +<td align="right">-387.9</td> +</tr> +<tr class="even"> +<td align="left">HS tc</td> +<td align="right">10</td> +<td align="right">783.7</td> +<td align="right">792.7</td> +<td align="right">-381.9</td> +</tr> +</tbody> +</table> +<p>The model comparisons show that the fits with constant variance are +consistently preferable to the corresponding fits with two-component +error for these data. This is confirmed by the fact that the parameter +<code>b.1</code> (the relative standard deviation in the fits obtained +with the saemix package), is ill-defined in all fits.</p> +<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<colgroup> +<col width="6%"> +<col width="44%"> +<col width="49%"> +</colgroup> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">sd(meso_0)</td> +<td align="left">sd(meso_0), b.1</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">sd(meso_0), sd(log_beta)</td> +<td align="left">sd(meso_0), sd(log_beta), b.1</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">sd(meso_0), sd(log_k1)</td> +<td align="left">sd(meso_0), sd(g_qlogis), b.1</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">sd(meso_free_0), sd(log_k_meso_free_bound)</td> +<td align="left">sd(meso_free_0), sd(log_k_meso_free_bound), b.1</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">sd(meso_0)</td> +<td align="left">sd(meso_0), b.1</td> +</tr> +</tbody> +</table> +<p>For obtaining fits with only well-defined random effects, we update +the set of fits, excluding random effects that were ill-defined +according to the <code>illparms</code> function.</p> +<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_2</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_1</span>, no_random_effect <span class="op">=</span> <span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_1</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/status.html">status</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left">OK</td> +<td align="left">OK</td> +</tr> +</tbody> +</table> +<p>The updated fits terminate without errors.</p> +<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">)</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="left">const</th> +<th align="left">tc</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">SFO</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="even"> +<td align="left">FOMC</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="odd"> +<td align="left">DFOP</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="even"> +<td align="left">SFORB</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +<tr class="odd"> +<td align="left">HS</td> +<td align="left"></td> +<td align="left">b.1</td> +</tr> +</tbody> +</table> +<p>No ill-defined errors remain in the fits with constant variance.</p> +</div> +<div class="section level2"> +<h2 id="hierarchical-models-with-covariate">Hierarchical models with covariate<a class="anchor" aria-label="anchor" href="#hierarchical-models-with-covariate"></a> +</h2> +<p>In the following sections, hierarchical fits including a model for +the influence of pH on selected degradation parameters are shown for all +parent models. Constant variance is selected as the error model based on +the fits without covariate effects. Random effects that were ill-defined +in the fits without pH influence are excluded. A potential influence of +the soil pH is only included for parameters with a well-defined random +effect, because experience has shown that only for such parameters a +significant pH effect could be found.</p> +<div class="section level3"> +<h3 id="sfo">SFO<a class="anchor" aria-label="anchor" href="#sfo"></a> +</h3> +<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sfo_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="st">"meso_0"</span>, covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">91.35</td> +<td align="right">89.27</td> +<td align="right">93.43</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso</td> +<td align="right">-6.66</td> +<td align="right">-7.97</td> +<td align="right">-5.35</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso)</td> +<td align="right">0.59</td> +<td align="right">0.37</td> +<td align="right">0.81</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">5.48</td> +<td align="right">4.71</td> +<td align="right">6.24</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso</td> +<td align="right">0.35</td> +<td align="right">0.23</td> +<td align="right">0.47</td> +</tr> +</tbody> +</table> +<p>The parameter showing the pH influence in the above table is +<code>beta_pH(log_k_meso)</code>. Its confidence interval does not +include zero, indicating that the influence of soil pH on the log of the +degradation rate constant is significantly greater than zero.</p> +<div class="sourceCode" id="cb18"><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_2</span><span class="op">[[</span><span class="st">"SFO"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">sfo_pH</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["SFO", "const"]] 4 797.56 801.12 -394.78 +sfo_pH 5 783.09 787.54 -386.54 16.473 1 4.934e-05 *** +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>The comparison with the SFO fit without covariate effect confirms +that considering the soil pH improves the model, both by comparison of +AIC and BIC and by the likelihood ratio test.</p> +<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_prebuilt_files/figure-html/unnamed-chunk-8-1.png" width="700" style="display: block; margin: auto;"></p> +<p>Endpoints for a model with covariates are by default calculated for +the median of the covariate values. This quantile can be adapted, or a +specific covariate value can be given as shown below.</p> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 +meso 18.52069 61.52441</code></pre> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span>, covariate_quantile <span class="op">=</span> <span class="fl">0.9</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +90% 7.13 + +$distimes + DT50 DT90 +meso 8.237019 27.36278</code></pre> +<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sfo_pH</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7.0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 +meso 8.89035 29.5331</code></pre> +</div> +<div class="section level3"> +<h3 id="fomc">FOMC<a class="anchor" aria-label="anchor" href="#fomc"></a> +</h3> +<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">fomc_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="st">"meso_0"</span>, covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_alpha</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fomc_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">92.84</td> +<td align="right">90.75</td> +<td align="right">94.93</td> +</tr> +<tr class="even"> +<td align="left">log_alpha</td> +<td align="right">-2.21</td> +<td align="right">-3.49</td> +<td align="right">-0.92</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_alpha)</td> +<td align="right">0.58</td> +<td align="right">0.37</td> +<td align="right">0.79</td> +</tr> +<tr class="even"> +<td align="left">log_beta</td> +<td align="right">4.21</td> +<td align="right">3.44</td> +<td align="right">4.99</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">5.03</td> +<td align="right">4.32</td> +<td align="right">5.73</td> +</tr> +<tr class="even"> +<td align="left">SD.log_alpha</td> +<td align="right">0.00</td> +<td align="right">-23.77</td> +<td align="right">23.78</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_beta</td> +<td align="right">0.37</td> +<td align="right">0.01</td> +<td align="right">0.74</td> +</tr> +</tbody> +</table> +<p>As in the case of SFO, the confidence interval of the slope parameter +(here <code>beta_pH(log_alpha)</code>) quantifying the influence of soil +pH does not include zero, and the model comparison clearly indicates +that the model with covariate influence is preferable. However, the +random effect for <code>alpha</code> is not well-defined any more after +inclusion of the covariate effect (the confidence interval of +<code>SD.log_alpha</code> includes zero).</p> +<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">fomc_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_alpha)"</code></pre> +<p>Therefore, the model is updated without this random effect, and no +ill-defined parameters remain.</p> +<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">fomc_pH_2</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">fomc_pH</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_alpha"</span><span class="op">)</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">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb32"><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_2</span><span class="op">[[</span><span class="st">"FOMC"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">fomc_pH</span>, <span class="va">fomc_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["FOMC", "const"]] 5 783.25 787.71 -386.63 +fomc_pH_2 6 767.49 772.83 -377.75 17.762 1 2.503e-05 *** +fomc_pH 7 770.07 776.30 -378.04 0.000 1 1 +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>Model comparison indicates that including pH dependence significantly +improves the fit, and that the reduced model with covariate influence +results in the most preferable FOMC fit.</p> +<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.05</td> +<td align="right">90.98</td> +<td align="right">95.13</td> +</tr> +<tr class="even"> +<td align="left">log_alpha</td> +<td align="right">-2.91</td> +<td align="right">-4.18</td> +<td align="right">-1.63</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_alpha)</td> +<td align="right">0.66</td> +<td align="right">0.44</td> +<td align="right">0.87</td> +</tr> +<tr class="even"> +<td align="left">log_beta</td> +<td align="right">3.95</td> +<td align="right">3.29</td> +<td align="right">4.62</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.98</td> +<td align="right">4.28</td> +<td align="right">5.68</td> +</tr> +<tr class="even"> +<td align="left">SD.log_beta</td> +<td align="right">0.40</td> +<td align="right">0.26</td> +<td align="right">0.54</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_prebuilt_files/figure-html/unnamed-chunk-14-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fomc_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back +meso 17.30248 82.91343 24.95943</code></pre> +<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fomc_pH_2</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back +meso 6.986239 27.02927 8.136621</code></pre> +</div> +<div class="section level3"> +<h3 id="dfop">DFOP<a class="anchor" aria-label="anchor" href="#dfop"></a> +</h3> +<p>In the DFOP fits without covariate effects, random effects for two +degradation parameters (<code>k2</code> and <code>g</code>) were +identifiable.</p> +<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_2</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.61</td> +<td align="right">91.58</td> +<td align="right">95.63</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-1.53</td> +<td align="right">-2.27</td> +<td align="right">-0.79</td> +</tr> +<tr class="odd"> +<td align="left">log_k2</td> +<td align="right">-3.42</td> +<td align="right">-3.73</td> +<td align="right">-3.11</td> +</tr> +<tr class="even"> +<td align="left">g_qlogis</td> +<td align="right">-1.67</td> +<td align="right">-2.57</td> +<td align="right">-0.77</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.74</td> +<td align="right">4.02</td> +<td align="right">5.45</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.60</td> +<td align="right">0.38</td> +<td align="right">0.81</td> +</tr> +<tr class="odd"> +<td align="left">SD.g_qlogis</td> +<td align="right">0.94</td> +<td align="right">0.33</td> +<td align="right">1.54</td> +</tr> +</tbody> +</table> +<p>A fit with pH dependent degradation parameters was obtained by +excluding the same random effects as in the refined DFOP fit without +covariate influence, and including covariate models for the two +identifiable parameters <code>k2</code> and <code>g</code>.</p> +<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">g_qlogis</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<p>The corresponding parameters for the influence of soil pH are +<code>beta_pH(log_k2)</code> for the influence of soil pH on +<code>k2</code>, and <code>beta_pH(g_qlogis)</code> for its influence on +<code>g</code>.</p> +<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">dfop_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">92.84</td> +<td align="right">90.85</td> +<td align="right">94.84</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-2.82</td> +<td align="right">-3.09</td> +<td align="right">-2.54</td> +</tr> +<tr class="odd"> +<td align="left">log_k2</td> +<td align="right">-11.48</td> +<td align="right">-15.32</td> +<td align="right">-7.64</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">1.31</td> +<td align="right">0.69</td> +<td align="right">1.92</td> +</tr> +<tr class="odd"> +<td align="left">g_qlogis</td> +<td align="right">3.13</td> +<td align="right">0.47</td> +<td align="right">5.80</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(g_qlogis)</td> +<td align="right">-0.57</td> +<td align="right">-1.04</td> +<td align="right">-0.09</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.96</td> +<td align="right">4.26</td> +<td align="right">5.65</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.76</td> +<td align="right">0.47</td> +<td align="right">1.05</td> +</tr> +<tr class="odd"> +<td align="left">SD.g_qlogis</td> +<td align="right">0.01</td> +<td align="right">-9.96</td> +<td align="right">9.97</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">dfop_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(g_qlogis)"</code></pre> +<p>Confidence intervals for neither of them include zero, indicating a +significant difference from zero. However, the random effect for +<code>g</code> is now ill-defined. The fit is updated without this +ill-defined random effect.</p> +<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_2</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">dfop_pH</span>,</span> +<span> no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span>, <span class="st">"g_qlogis"</span><span class="op">)</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">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "beta_pH(g_qlogis)"</code></pre> +<p>Now, the slope parameter for the pH effect on <code>g</code> is +ill-defined. Therefore, another attempt is made without the +corresponding covariate model.</p> +<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_3</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">dfop_pH_3</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(g_qlogis)"</code></pre> +<p>As the random effect for <code>g</code> is again ill-defined, the fit +is repeated without it.</p> +<div class="sourceCode" id="cb49"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">dfop_pH_4</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">dfop_pH_3</span>, no_random_effect <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="st">"meso_0"</span>, <span class="st">"log_k1"</span>, <span class="st">"g_qlogis"</span><span class="op">)</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">dfop_pH_4</span><span class="op">)</span></span></code></pre></div> +<p>While no ill-defined parameters remain, model comparison suggests +that the previous model <code>dfop_pH_2</code> with two pH dependent +parameters is preferable, based on information criteria as well as based +on the likelihood ratio test.</p> +<div class="sourceCode" id="cb50"><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_2</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dfop_pH</span>, <span class="va">dfop_pH_2</span>, <span class="va">dfop_pH_3</span>, <span class="va">dfop_pH_4</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik +f_saem_2[["DFOP", "const"]] 7 782.94 789.18 -384.47 +dfop_pH_4 7 767.35 773.58 -376.68 +dfop_pH_2 8 765.14 772.26 -374.57 +dfop_pH_3 8 769.00 776.12 -376.50 +dfop_pH 9 769.10 777.11 -375.55</code></pre> +<div class="sourceCode" id="cb52"><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">dfop_pH_2</span>, <span class="va">dfop_pH_4</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +dfop_pH_4 7 767.35 773.58 -376.68 +dfop_pH_2 8 765.14 772.26 -374.57 4.2153 1 0.04006 * +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>When focussing on parameter identifiability using the test if the +confidence interval includes zero, <code>dfop_pH_4</code> would still be +the preferred model. However, it should be kept in mind that parameter +confidence intervals are constructed using a simple linearisation of the +likelihood. As the confidence interval of the random effect for +<code>g</code> only marginally includes zero, it is suggested that this +is acceptable, and that <code>dfop_pH_2</code> can be considered the +most preferable model.</p> +<div class="sourceCode" id="cb54"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_prebuilt_files/figure-html/unnamed-chunk-19-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb55"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.36876 73.51841 22.13125 4.191901 23.98672</code></pre> +<div class="sourceCode" id="cb57"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.346428 28.34437 8.532507 4.191901 8.753618</code></pre> +</div> +<div class="section level3"> +<h3 id="sforb">SFORB<a class="anchor" aria-label="anchor" href="#sforb"></a> +</h3> +<div class="sourceCode" id="cb59"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sforb_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"SFORB"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"meso_free_0"</span>, <span class="st">"log_k_meso_free_bound"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso_free</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k_meso_bound_free</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb60"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sforb_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_free_0</td> +<td align="right">93.42</td> +<td align="right">91.32</td> +<td align="right">95.52</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free</td> +<td align="right">-5.37</td> +<td align="right">-6.94</td> +<td align="right">-3.81</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso_free)</td> +<td align="right">0.42</td> +<td align="right">0.18</td> +<td align="right">0.67</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free_bound</td> +<td align="right">-3.49</td> +<td align="right">-4.92</td> +<td align="right">-2.05</td> +</tr> +<tr class="odd"> +<td align="left">log_k_meso_bound_free</td> +<td align="right">-9.98</td> +<td align="right">-19.22</td> +<td align="right">-0.74</td> +</tr> +<tr class="even"> +<td align="left">beta_pH(log_k_meso_bound_free)</td> +<td align="right">1.23</td> +<td align="right">-0.21</td> +<td align="right">2.67</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.90</td> +<td align="right">4.18</td> +<td align="right">5.63</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k_meso_free</td> +<td align="right">0.35</td> +<td align="right">0.23</td> +<td align="right">0.47</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso_bound_free</td> +<td align="right">0.13</td> +<td align="right">-1.95</td> +<td align="right">2.20</td> +</tr> +</tbody> +</table> +<p>The confidence interval of +<code>beta_pH(log_k_meso_bound_free)</code> includes zero, indicating +that the influence of soil pH on <code>k_meso_bound_free</code> cannot +reliably be quantified. Also, the confidence interval for the random +effect on this parameter (<code>SD.log_k_meso_bound_free</code>) +includes zero.</p> +<p>Using the <code>illparms</code> function, these ill-defined +parameters can be found more conveniently.</p> +<div class="sourceCode" id="cb61"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">sforb_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_k_meso_bound_free)" "beta_pH(log_k_meso_bound_free)"</code></pre> +<p>To remove the ill-defined parameters, a second variant of the SFORB +model with pH influence is fitted. No ill-defined parameters remain.</p> +<div class="sourceCode" id="cb63"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">sforb_pH_2</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">sforb_pH</span>,</span> +<span> no_random_effect <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="st">"meso_free_0"</span>, <span class="st">"log_k_meso_free_bound"</span>, <span class="st">"log_k_meso_bound_free"</span><span class="op">)</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k_meso_free</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<p>The model comparison of the SFORB fits includes the refined model +without covariate effect, and both versions of the SFORB fit with +covariate effect.</p> +<div class="sourceCode" id="cb64"><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_2</span><span class="op">[[</span><span class="st">"SFORB"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">sforb_pH</span>, <span class="va">sforb_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["SFORB", "const"]] 7 783.40 789.63 -384.70 +sforb_pH_2 7 770.94 777.17 -378.47 12.4616 0 +sforb_pH 9 768.81 776.83 -375.41 6.1258 2 0.04675 * +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<p>The first model including pH influence is preferable based on +information criteria and the likelihood ratio test. However, as it is +not fully identifiable, the second model is selected.</p> +<div class="sourceCode" id="cb66"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_free_0</td> +<td align="right">93.32</td> +<td align="right">91.16</td> +<td align="right">95.48</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free</td> +<td align="right">-6.15</td> +<td align="right">-7.43</td> +<td align="right">-4.86</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k_meso_free)</td> +<td align="right">0.54</td> +<td align="right">0.33</td> +<td align="right">0.75</td> +</tr> +<tr class="even"> +<td align="left">log_k_meso_free_bound</td> +<td align="right">-3.80</td> +<td align="right">-5.20</td> +<td align="right">-2.40</td> +</tr> +<tr class="odd"> +<td align="left">log_k_meso_bound_free</td> +<td align="right">-2.95</td> +<td align="right">-4.26</td> +<td align="right">-1.64</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">5.08</td> +<td align="right">4.38</td> +<td align="right">5.79</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k_meso_free</td> +<td align="right">0.33</td> +<td align="right">0.22</td> +<td align="right">0.45</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb67"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_prebuilt_files/figure-html/unnamed-chunk-25-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb68"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sforb_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$ff +meso_free + 1 + +$SFORB + meso_b1 meso_b2 meso_g +0.09735824 0.02631699 0.31602120 + +$distimes + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.86549 73.15824 22.02282 7.119554 26.33839</code></pre> +<div class="sourceCode" id="cb70"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">sforb_pH_2</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$ff +meso_free + 1 + +$SFORB + meso_b1 meso_b2 meso_g +0.13315233 0.03795988 0.61186191 + +$distimes + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 7.932495 36.93311 11.11797 5.205671 18.26</code></pre> +</div> +<div class="section level3"> +<h3 id="hs">HS<a class="anchor" aria-label="anchor" href="#hs"></a> +</h3> +<div class="sourceCode" id="cb72"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">hs_pH</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_sep_const</span><span class="op">[</span><span class="st">"HS"</span>, <span class="op">]</span>, no_random_effect <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"meso_0"</span><span class="op">)</span>,</span> +<span> covariates <span class="op">=</span> <span class="va">pH</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k1</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_tb</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<div class="sourceCode" id="cb73"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">hs_pH</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.33</td> +<td align="right">91.47</td> +<td align="right">95.19</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-5.81</td> +<td align="right">-7.27</td> +<td align="right">-4.36</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k1)</td> +<td align="right">0.47</td> +<td align="right">0.23</td> +<td align="right">0.72</td> +</tr> +<tr class="even"> +<td align="left">log_k2</td> +<td align="right">-6.80</td> +<td align="right">-8.76</td> +<td align="right">-4.83</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">0.54</td> +<td align="right">0.21</td> +<td align="right">0.87</td> +</tr> +<tr class="even"> +<td align="left">log_tb</td> +<td align="right">3.25</td> +<td align="right">1.25</td> +<td align="right">5.25</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_tb)</td> +<td align="right">-0.10</td> +<td align="right">-0.43</td> +<td align="right">0.23</td> +</tr> +<tr class="even"> +<td align="left">a.1</td> +<td align="right">4.49</td> +<td align="right">3.78</td> +<td align="right">5.21</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k1</td> +<td align="right">0.37</td> +<td align="right">0.24</td> +<td align="right">0.51</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k2</td> +<td align="right">0.29</td> +<td align="right">0.10</td> +<td align="right">0.48</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_tb</td> +<td align="right">0.25</td> +<td align="right">-0.07</td> +<td align="right">0.57</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb74"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">hs_pH</span><span class="op">)</span></span></code></pre></div> +<pre><code>[1] "sd(log_tb)" "beta_pH(log_tb)"</code></pre> +<p>According to the output of the <code>illparms</code> function, the +random effect on the break time <code>tb</code> cannot reliably be +quantified, neither can the influence of soil pH on <code>tb</code>. The +fit is repeated without the corresponding covariate model, and no +ill-defined parameters remain.</p> +<div class="sourceCode" id="cb76"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">hs_pH_2</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">hs_pH</span>, covariate_models <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">log_k1</span> <span class="op">~</span> <span class="va">pH</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="va">pH</span><span class="op">)</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">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<p>Model comparison confirms that this model is preferable to the fit +without covariate influence, and also to the first version with +covariate influence.</p> +<div class="sourceCode" id="cb77"><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_2</span><span class="op">[[</span><span class="st">"HS"</span>, <span class="st">"const"</span><span class="op">]</span><span class="op">]</span>, <span class="va">hs_pH</span>, <span class="va">hs_pH_2</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik Chisq Df Pr(>Chisq) +f_saem_2[["HS", "const"]] 8 780.08 787.20 -382.04 +hs_pH_2 10 766.47 775.37 -373.23 17.606 2 0.0001503 *** +hs_pH 11 769.80 779.59 -373.90 0.000 1 1.0000000 +--- +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre> +<div class="sourceCode" id="cb79"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span><span class="op">$</span><span class="va">confint_trans</span> <span class="op">|></span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div> +<table class="table"> +<thead><tr class="header"> +<th align="left"></th> +<th align="right">est.</th> +<th align="right">lower</th> +<th align="right">upper</th> +</tr></thead> +<tbody> +<tr class="odd"> +<td align="left">meso_0</td> +<td align="right">93.33</td> +<td align="right">91.50</td> +<td align="right">95.15</td> +</tr> +<tr class="even"> +<td align="left">log_k1</td> +<td align="right">-5.68</td> +<td align="right">-7.09</td> +<td align="right">-4.27</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k1)</td> +<td align="right">0.46</td> +<td align="right">0.22</td> +<td align="right">0.69</td> +</tr> +<tr class="even"> +<td align="left">log_k2</td> +<td align="right">-6.61</td> +<td align="right">-8.34</td> +<td align="right">-4.88</td> +</tr> +<tr class="odd"> +<td align="left">beta_pH(log_k2)</td> +<td align="right">0.50</td> +<td align="right">0.21</td> +<td align="right">0.79</td> +</tr> +<tr class="even"> +<td align="left">log_tb</td> +<td align="right">2.70</td> +<td align="right">2.33</td> +<td align="right">3.08</td> +</tr> +<tr class="odd"> +<td align="left">a.1</td> +<td align="right">4.45</td> +<td align="right">3.74</td> +<td align="right">5.16</td> +</tr> +<tr class="even"> +<td align="left">SD.log_k1</td> +<td align="right">0.36</td> +<td align="right">0.22</td> +<td align="right">0.49</td> +</tr> +<tr class="odd"> +<td align="left">SD.log_k2</td> +<td align="right">0.23</td> +<td align="right">0.02</td> +<td align="right">0.43</td> +</tr> +<tr class="even"> +<td align="left">SD.log_tb</td> +<td align="right">0.55</td> +<td align="right">0.25</td> +<td align="right">0.85</td> +</tr> +</tbody> +</table> +<div class="sourceCode" id="cb80"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<p><img src="mesotrione_parent_2023_prebuilt_files/figure-html/unnamed-chunk-30-1.png" width="700" style="display: block; margin: auto;"></p> +<div class="sourceCode" id="cb81"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 14.68725 82.45287 24.82079 14.68725 29.29299</code></pre> +<div class="sourceCode" id="cb83"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">hs_pH_2</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.298536 38.85371 11.69613 8.298536 15.71561</code></pre> +</div> +<div class="section level3"> +<h3 id="comparison-across-parent-models">Comparison across parent models<a class="anchor" aria-label="anchor" href="#comparison-across-parent-models"></a> +</h3> +<p>After model reduction for all models with pH influence, they are +compared with each other.</p> +<div class="sourceCode" id="cb85"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">sfo_pH</span>, <span class="va">fomc_pH_2</span>, <span class="va">dfop_pH_2</span>, <span class="va">dfop_pH_4</span>, <span class="va">sforb_pH_2</span>, <span class="va">hs_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>Data: 116 observations of 1 variable(s) grouped in 18 datasets + + npar AIC BIC Lik +sfo_pH 5 783.09 787.54 -386.54 +fomc_pH_2 6 767.49 772.83 -377.75 +dfop_pH_4 7 767.35 773.58 -376.68 +sforb_pH_2 7 770.94 777.17 -378.47 +dfop_pH_2 8 765.14 772.26 -374.57 +hs_pH_2 10 766.47 775.37 -373.23</code></pre> +<p>The DFOP model with pH influence on <code>k2</code> and +<code>g</code> and a random effect only on <code>k2</code> is finally +selected as the best fit.</p> +<p>The endpoints resulting from this model are listed below. Please +refer to the Appendix for a detailed listing.</p> +<div class="sourceCode" id="cb87"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +50% 5.75 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.36876 73.51841 22.13125 4.191901 23.98672</code></pre> +<div class="sourceCode" id="cb89"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">dfop_pH_2</span>, covariates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>pH <span class="op">=</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<pre><code>$covariates + pH +User 7 + +$distimes + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 8.346428 28.34437 8.532507 4.191901 8.753618</code></pre> +</div> +</div> +<div class="section level2"> +<h2 id="conclusions">Conclusions<a class="anchor" aria-label="anchor" href="#conclusions"></a> +</h2> +<p>These evaluations demonstrate that covariate effects can be included +for all types of parent degradation models. These models can then be +further refined to make them fully identifiable.</p> +</div> +<div class="section level2"> +<h2 id="appendix">Appendix<a class="anchor" aria-label="anchor" href="#appendix"></a> +</h2> +<div class="section level3"> +<h3 id="hierarchical-fit-listings">Hierarchical fit listings<a class="anchor" aria-label="anchor" href="#hierarchical-fit-listings"></a> +</h3> +<div class="section level4"> +<h4 id="fits-without-covariate-effects">Fits without covariate effects<a class="anchor" aria-label="anchor" href="#fits-without-covariate-effects"></a> +</h4> +<caption> +Hierarchical SFO fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:35 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - k_meso * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 0.682 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k_meso + 90.832 -3.192 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k_meso +meso_0 6.752 0.0000 +log_k_meso 0.000 0.9155 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 800 804.5 -395 + +Optimised parameters: + est. lower upper +meso_0 92.0705 89.9917 94.1493 +log_k_meso -3.1641 -3.4286 -2.8996 +a.1 5.4628 4.6421 6.2835 +SD.meso_0 0.0611 -98.3545 98.4767 +SD.log_k_meso 0.5616 0.3734 0.7499 + +Correlation: + meso_0 +log_k_meso 0.1132 + +Random effects: + est. lower upper +SD.meso_0 0.0611 -98.3545 98.4767 +SD.log_k_meso 0.5616 0.3734 0.7499 + +Variance model: + est. lower upper +a.1 5.463 4.642 6.284 + +Backtransformed parameters: + est. lower upper +meso_0 92.07053 89.99172 94.14933 +k_meso 0.04225 0.03243 0.05505 + +Estimated disappearance times: + DT50 DT90 +meso 16.41 54.5 + +</code></pre> +<p></p> +<caption> +Hierarchical FOMC fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:35 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 0.817 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.4 793.6 -386.7 + +Optimised parameters: + est. lower upper +meso_0 93.5648 91.42864 95.7009 +log_alpha 0.7645 0.28068 1.2484 +log_beta 3.6597 3.05999 4.2594 +a.1 5.0708 4.29823 5.8435 +SD.meso_0 0.1691 -34.01517 34.3535 +SD.log_alpha 0.3764 0.05834 0.6945 +SD.log_beta 0.3903 -0.06074 0.8414 + +Correlation: + meso_0 log_lph +log_alpha -0.2839 +log_beta -0.3443 0.8855 + +Random effects: + est. lower upper +SD.meso_0 0.1691 -34.01517 34.3535 +SD.log_alpha 0.3764 0.05834 0.6945 +SD.log_beta 0.3903 -0.06074 0.8414 + +Variance model: + est. lower upper +a.1 5.071 4.298 5.843 + +Backtransformed parameters: + est. lower upper +meso_0 93.565 91.429 95.701 +alpha 2.148 1.324 3.485 +beta 38.850 21.327 70.770 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 14.8 74.64 22.47 + +</code></pre> +<p></p> +<caption> +Hierarchical DFOP fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:35 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.188 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.6 795.6 -384.8 + +Optimised parameters: + est. lower upper +meso_0 93.6684 91.63599 95.7008 +log_k1 -1.7354 -2.61433 -0.8565 +log_k2 -3.4015 -3.73323 -3.0697 +g_qlogis -1.6341 -2.66133 -0.6069 +a.1 4.7803 4.01269 5.5479 +SD.meso_0 0.1661 -30.97086 31.3031 +SD.log_k1 0.1127 -2.59680 2.8223 +SD.log_k2 0.6394 0.41499 0.8638 +SD.g_qlogis 0.8166 0.09785 1.5353 + +Correlation: + meso_0 log_k1 log_k2 +log_k1 0.1757 +log_k2 0.0199 0.2990 +g_qlogis 0.0813 -0.7431 -0.3826 + +Random effects: + est. lower upper +SD.meso_0 0.1661 -30.97086 31.3031 +SD.log_k1 0.1127 -2.59680 2.8223 +SD.log_k2 0.6394 0.41499 0.8638 +SD.g_qlogis 0.8166 0.09785 1.5353 + +Variance model: + est. lower upper +a.1 4.78 4.013 5.548 + +Backtransformed parameters: + est. lower upper +meso_0 93.66841 91.63599 95.70082 +k1 0.17633 0.07322 0.42466 +k2 0.03332 0.02392 0.04643 +g 0.16327 0.06529 0.35277 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 16.04 63.75 19.19 3.931 20.8 + +</code></pre> +<p></p> +<caption> +Hierarchical SFORB fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:35 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.223 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 787.4 795.4 -384.7 + +Optimised parameters: + est. lower upper +meso_free_0 93.6285 91.6262 95.631 +log_k_meso_free -2.8314 -3.1375 -2.525 +log_k_meso_free_bound -3.2213 -4.4695 -1.973 +log_k_meso_bound_free -2.4246 -3.5668 -1.282 +a.1 4.7372 3.9542 5.520 +SD.meso_free_0 0.1634 -32.7769 33.104 +SD.log_k_meso_free 0.4885 0.3080 0.669 +SD.log_k_meso_free_bound 0.2876 -1.7955 2.371 +SD.log_k_meso_bound_free 0.9942 0.2181 1.770 + +Correlation: + ms_fr_0 lg_k_m_ lg_k_ms_f_ +log_k_meso_free 0.2332 +log_k_meso_free_bound 0.1100 0.5964 +log_k_meso_bound_free -0.0413 0.3697 0.8025 + +Random effects: + est. lower upper +SD.meso_free_0 0.1634 -32.7769 33.104 +SD.log_k_meso_free 0.4885 0.3080 0.669 +SD.log_k_meso_free_bound 0.2876 -1.7955 2.371 +SD.log_k_meso_bound_free 0.9942 0.2181 1.770 + +Variance model: + est. lower upper +a.1 4.737 3.954 5.52 + +Backtransformed parameters: + est. lower upper +meso_free_0 93.62849 91.62622 95.63075 +k_meso_free 0.05893 0.04339 0.08004 +k_meso_free_bound 0.03990 0.01145 0.13903 +k_meso_bound_free 0.08851 0.02825 0.27736 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g +0.15333 0.03402 0.20881 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 14.79 60.81 18.3 4.521 20.37 + +</code></pre> +<p></p> +<caption> +Hierarchical HS fit with constant variance +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:36 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.307 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 781.9 789.9 -382 + +Optimised parameters: + est. lower upper +meso_0 93.34242 91.4730 95.2118 +log_k1 -2.77312 -3.0826 -2.4637 +log_k2 -3.61854 -3.8430 -3.3941 +log_tb 2.00266 1.3357 2.6696 +a.1 4.47693 3.7059 5.2479 +SD.meso_0 0.07963 -63.1661 63.3253 +SD.log_k1 0.47817 0.2467 0.7097 +SD.log_k2 0.39216 0.2137 0.5706 +SD.log_tb 0.94683 0.4208 1.4728 + +Correlation: + meso_0 log_k1 log_k2 +log_k1 0.1627 +log_k2 0.0063 -0.0301 +log_tb 0.0083 -0.3931 -0.1225 + +Random effects: + est. lower upper +SD.meso_0 0.07963 -63.1661 63.3253 +SD.log_k1 0.47817 0.2467 0.7097 +SD.log_k2 0.39216 0.2137 0.5706 +SD.log_tb 0.94683 0.4208 1.4728 + +Variance model: + est. lower upper +a.1 4.477 3.706 5.248 + +Backtransformed parameters: + est. lower upper +meso_0 93.34242 91.47303 95.21181 +k1 0.06247 0.04584 0.08512 +k2 0.02682 0.02143 0.03357 +tb 7.40872 3.80282 14.43376 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 16 76 22.88 11.1 25.84 + +</code></pre> +<p></p> +</div> +<div class="section level4"> +<h4 id="fits-with-covariate-effects">Fits with covariate effects<a class="anchor" aria-label="anchor" href="#fits-with-covariate-effects"></a> +</h4> +<caption> +Hierarchichal SFO fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:49 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - k_meso * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.739 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k_meso + 90.832 -3.192 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k_meso +meso_0 6.752 0.0000 +log_k_meso 0.000 0.9155 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 783.1 787.5 -386.5 + +Optimised parameters: + est. lower upper +meso_0 91.3481 89.2688 93.4275 +log_k_meso -6.6614 -7.9715 -5.3514 +beta_pH(log_k_meso) 0.5871 0.3684 0.8059 +a.1 5.4750 4.7085 6.2415 +SD.log_k_meso 0.3471 0.2258 0.4684 + +Correlation: + meso_0 lg_k_ms +log_k_meso 0.0414 +beta_pH(log_k_meso) -0.0183 -0.9917 + +Random effects: + est. lower upper +SD.log_k_meso 0.3471 0.2258 0.4684 + +Variance model: + est. lower upper +a.1 5.475 4.709 6.242 + +Backtransformed parameters: + est. lower upper +meso_0 91.348139 8.927e+01 93.427476 +k_meso 0.001279 3.452e-04 0.004741 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 +meso 18.52 61.52 + +</code></pre> +<p></p> +<caption> +Hierarchichal FOMC fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:51 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.076 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 770.1 776.3 -378 + +Optimised parameters: + est. lower upper +meso_0 92.840646 90.750461 94.9308 +log_alpha -2.206602 -3.494546 -0.9187 +beta_pH(log_alpha) 0.577505 0.369805 0.7852 +log_beta 4.214099 3.438851 4.9893 +a.1 5.027768 4.322028 5.7335 +SD.log_alpha 0.004034 -23.766993 23.7751 +SD.log_beta 0.374640 0.009252 0.7400 + +Correlation: + meso_0 log_lph bt_H(_) +log_alpha -0.0865 +beta_pH(log_alpha) -0.0789 -0.8704 +log_beta -0.3544 0.3302 0.1628 + +Random effects: + est. lower upper +SD.log_alpha 0.004034 -23.766993 23.78 +SD.log_beta 0.374640 0.009252 0.74 + +Variance model: + est. lower upper +a.1 5.028 4.322 5.734 + +Backtransformed parameters: + est. lower upper +meso_0 92.8406 90.75046 94.9308 +alpha 0.1101 0.03036 0.3991 +beta 67.6332 31.15113 146.8404 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 17.28 76.37 22.99 + +</code></pre> +<p></p> +<caption> +Refined hierarchichal FOMC fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:55 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - (alpha/beta) * 1/((time/beta) + 1) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 3.361 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_alpha log_beta + 93.0520 0.6008 3.4176 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_alpha log_beta +meso_0 6.287 0.00 0.000 +log_alpha 0.000 1.53 0.000 +log_beta 0.000 0.00 1.724 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 767.5 772.8 -377.7 + +Optimised parameters: + est. lower upper +meso_0 93.0536 90.9771 95.1300 +log_alpha -2.9054 -4.1803 -1.6304 +beta_pH(log_alpha) 0.6590 0.4437 0.8744 +log_beta 3.9549 3.2860 4.6239 +a.1 4.9784 4.2815 5.6754 +SD.log_beta 0.4019 0.2632 0.5406 + +Correlation: + meso_0 log_lph bt_H(_) +log_alpha -0.0397 +beta_pH(log_alpha) -0.0899 -0.9146 +log_beta -0.3473 0.2038 0.1919 + +Random effects: + est. lower upper +SD.log_beta 0.4019 0.2632 0.5406 + +Variance model: + est. lower upper +a.1 4.978 4.281 5.675 + +Backtransformed parameters: + est. lower upper +meso_0 93.05359 90.97713 95.1300 +alpha 0.05473 0.01529 0.1958 +beta 52.19251 26.73597 101.8874 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back +meso 17.3 82.91 24.96 + +</code></pre> +<p></p> +<caption> +Hierarchichal DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 19:59:58 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.758 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 769.1 777.1 -375.5 + +Optimised parameters: + est. lower upper +meso_0 92.843344 90.8464 94.84028 +log_k1 -2.815685 -3.0888 -2.54261 +log_k2 -11.479779 -15.3203 -7.63923 +beta_pH(log_k2) 1.308417 0.6948 1.92203 +g_qlogis 3.133036 0.4657 5.80035 +beta_pH(g_qlogis) -0.565988 -1.0394 -0.09262 +a.1 4.955518 4.2597 5.65135 +SD.log_k2 0.758963 0.4685 1.04943 +SD.g_qlogis 0.005215 -9.9561 9.96656 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) g_qlogs +log_k1 0.2706 +log_k2 -0.0571 0.1096 +beta_pH(log_k2) 0.0554 -0.1291 -0.9937 +g_qlogis -0.1125 -0.5062 -0.1305 0.1294 +beta_pH(g_qlogis) 0.1267 0.4226 0.0419 -0.0438 -0.9864 + +Random effects: + est. lower upper +SD.log_k2 0.758963 0.4685 1.049 +SD.g_qlogis 0.005215 -9.9561 9.967 + +Variance model: + est. lower upper +a.1 4.956 4.26 5.651 + +Backtransformed parameters: + est. lower upper +meso_0 9.284e+01 9.085e+01 9.484e+01 +k1 5.986e-02 4.556e-02 7.866e-02 +k2 1.034e-05 2.221e-07 4.812e-04 +g 9.582e-01 6.144e-01 9.970e-01 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 20.23 88.45 26.62 11.58 36.23 + +</code></pre> +<p></p> +<caption> +Refined hierarchical DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:03 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 4.465 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 765.1 772.3 -374.6 + +Optimised parameters: + est. lower upper +meso_0 93.3333 91.2427 95.42394 +log_k1 -1.7997 -2.9124 -0.68698 +log_k2 -8.1810 -10.1819 -6.18008 +beta_pH(log_k2) 0.8064 0.4903 1.12257 +g_qlogis 3.3513 -1.1792 7.88182 +beta_pH(g_qlogis) -0.8672 -1.7661 0.03177 +a.1 4.9158 4.2277 5.60390 +SD.log_k2 0.3946 0.2565 0.53281 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) g_qlogs +log_k1 0.1730 +log_k2 0.0442 0.5370 +beta_pH(log_k2) -0.0392 -0.4880 -0.9923 +g_qlogis -0.1536 0.1431 -0.1129 0.1432 +beta_pH(g_qlogis) 0.1504 -0.3151 -0.0196 -0.0212 -0.9798 + +Random effects: + est. lower upper +SD.log_k2 0.3946 0.2565 0.5328 + +Variance model: + est. lower upper +a.1 4.916 4.228 5.604 + +Backtransformed parameters: + est. lower upper +meso_0 9.333e+01 9.124e+01 95.42394 +k1 1.654e-01 5.435e-02 0.50309 +k2 2.799e-04 3.785e-05 0.00207 +g 9.661e-01 2.352e-01 0.99962 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 18.37 73.52 22.13 4.192 23.99 + +</code></pre> +<p></p> +<caption> +Further refined hierarchical DFOP fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:10 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 2.781 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_0 log_k1 log_k2 g_qlogis +93.14689 -2.05241 -3.53079 -0.09522 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 g_qlogis +meso_0 6.418 0.000 0.000 0.00 +log_k1 0.000 1.018 0.000 0.00 +log_k2 0.000 0.000 1.694 0.00 +g_qlogis 0.000 0.000 0.000 2.37 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 767.4 773.6 -376.7 + +Optimised parameters: + est. lower upper +meso_0 93.3011 91.1905 95.4118 +log_k1 -2.1487 -2.7607 -1.5367 +log_k2 -8.1039 -10.4225 -5.7853 +beta_pH(log_k2) 0.7821 0.4126 1.1517 +g_qlogis -1.0373 -1.9337 -0.1409 +a.1 5.0095 4.3082 5.7108 +SD.log_k2 0.4622 0.3009 0.6235 + +Correlation: + meso_0 log_k1 log_k2 b_H(_2) +log_k1 0.2179 +log_k2 0.0337 0.5791 +beta_pH(log_k2) -0.0326 -0.5546 -0.9932 +g_qlogis 0.0237 -0.8479 -0.6571 0.6123 + +Random effects: + est. lower upper +SD.log_k2 0.4622 0.3009 0.6235 + +Variance model: + est. lower upper +a.1 5.009 4.308 5.711 + +Backtransformed parameters: + est. lower upper +meso_0 9.330e+01 9.119e+01 95.411751 +k1 1.166e-01 6.325e-02 0.215084 +k2 3.024e-04 2.975e-05 0.003072 +g 2.617e-01 1.263e-01 0.464832 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 17.09 73.67 22.18 5.943 25.54 + +</code></pre> +<p></p> +<caption> +Hierarchichal SFORB fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:14 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 3.54 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 768.8 776.8 -375.4 + +Optimised parameters: + est. lower upper +meso_free_0 93.4204 91.3213 95.5195 +log_k_meso_free -5.3742 -6.9366 -3.8117 +beta_pH(log_k_meso_free) 0.4232 0.1769 0.6695 +log_k_meso_free_bound -3.4889 -4.9243 -2.0535 +log_k_meso_bound_free -9.9797 -19.2232 -0.7362 +beta_pH(log_k_meso_bound_free) 1.2290 -0.2107 2.6687 +a.1 4.9031 4.1795 5.6268 +SD.log_k_meso_free 0.3454 0.2252 0.4656 +SD.log_k_meso_bound_free 0.1277 -1.9459 2.2012 + +Correlation: + ms_fr_0 lg_k_m_ b_H(___) lg_k_ms_f_ lg_k_ms_b_ +log_k_meso_free 0.1493 +beta_pH(log_k_meso_free) -0.0930 -0.9854 +log_k_meso_free_bound 0.2439 0.4621 -0.3492 +log_k_meso_bound_free 0.2188 0.1292 -0.0339 0.7287 +beta_pH(log_k_meso_bound_free) -0.2216 -0.0797 -0.0111 -0.6566 -0.9934 + +Random effects: + est. lower upper +SD.log_k_meso_free 0.3454 0.2252 0.4656 +SD.log_k_meso_bound_free 0.1277 -1.9459 2.2012 + +Variance model: + est. lower upper +a.1 4.903 4.18 5.627 + +Backtransformed parameters: + est. lower upper +meso_free_0 9.342e+01 9.132e+01 95.51946 +k_meso_free 4.635e-03 9.716e-04 0.02211 +k_meso_free_bound 3.054e-02 7.268e-03 0.12829 +k_meso_bound_free 4.633e-05 4.482e-09 0.47894 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g + 0.1121 0.0256 0.3148 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.42 75.2 22.64 6.185 27.08 + +</code></pre> +<p> </p> +<caption> +Refined hierarchichal SFORB fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:18 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso_free/dt = - k_meso_free * meso_free - k_meso_free_bound * + meso_free + k_meso_bound_free * meso_bound +d_meso_bound/dt = + k_meso_free_bound * meso_free - k_meso_bound_free * + meso_bound + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 2.815 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + meso_free_0 log_k_meso_free log_k_meso_free_bound + 93.147 -2.305 -4.230 +log_k_meso_bound_free + -3.761 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_free_0 log_k_meso_free log_k_meso_free_bound +meso_free_0 6.418 0.0000 0.000 +log_k_meso_free 0.000 0.9276 0.000 +log_k_meso_free_bound 0.000 0.0000 2.272 +log_k_meso_bound_free 0.000 0.0000 0.000 + log_k_meso_bound_free +meso_free_0 0.000 +log_k_meso_free 0.000 +log_k_meso_free_bound 0.000 +log_k_meso_bound_free 1.447 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 770.9 777.2 -378.5 + +Optimised parameters: + est. lower upper +meso_free_0 93.3196 91.1633 95.4760 +log_k_meso_free -6.1460 -7.4306 -4.8614 +beta_pH(log_k_meso_free) 0.5435 0.3329 0.7542 +log_k_meso_free_bound -3.8001 -5.2027 -2.3975 +log_k_meso_bound_free -2.9462 -4.2565 -1.6359 +a.1 5.0825 4.3793 5.7856 +SD.log_k_meso_free 0.3338 0.2175 0.4502 + +Correlation: + ms_fr_0 lg_k_m_ b_H(___ lg_k_ms_f_ +log_k_meso_free 0.1086 +beta_pH(log_k_meso_free) -0.0426 -0.9821 +log_k_meso_free_bound 0.2513 0.1717 -0.0409 +log_k_meso_bound_free 0.1297 0.1171 -0.0139 0.9224 + +Random effects: + est. lower upper +SD.log_k_meso_free 0.3338 0.2175 0.4502 + +Variance model: + est. lower upper +a.1 5.082 4.379 5.786 + +Backtransformed parameters: + est. lower upper +meso_free_0 93.319649 9.116e+01 95.47601 +k_meso_free 0.002142 5.928e-04 0.00774 +k_meso_free_bound 0.022369 5.502e-03 0.09095 +k_meso_bound_free 0.052539 1.417e-02 0.19478 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated Eigenvalues of SFORB model(s): +meso_b1 meso_b2 meso_g +0.09736 0.02632 0.31602 + +Resulting formation fractions: + ff +meso_free 1 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_meso_b1 DT50_meso_b2 +meso 16.87 73.16 22.02 7.12 26.34 + +</code></pre> +<p> </p> +<caption> +Hierarchichal HS fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:20 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.849 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 769.8 779.6 -373.9 + +Optimised parameters: + est. lower upper +meso_0 93.32599 91.4658 95.1862 +log_k1 -5.81463 -7.2710 -4.3583 +beta_pH(log_k1) 0.47472 0.2334 0.7160 +log_k2 -6.79633 -8.7605 -4.8322 +beta_pH(log_k2) 0.54151 0.2124 0.8706 +log_tb 3.24674 1.2470 5.2465 +beta_pH(log_tb) -0.09889 -0.4258 0.2280 +a.1 4.49487 3.7766 5.2132 +SD.log_k1 0.37191 0.2370 0.5068 +SD.log_k2 0.29210 0.0994 0.4848 +SD.log_tb 0.25353 -0.0664 0.5735 + +Correlation: + meso_0 log_k1 b_H(_1) log_k2 b_H(_2) log_tb +log_k1 0.0744 +beta_pH(log_k1) -0.0452 -0.9915 +log_k2 0.0066 -0.0363 0.0376 +beta_pH(log_k2) -0.0071 0.0372 -0.0391 -0.9939 +log_tb -0.0238 -0.1483 0.1362 -0.3836 0.3696 +beta_pH(log_tb) 0.0097 0.1359 -0.1265 0.3736 -0.3653 -0.9905 + +Random effects: + est. lower upper +SD.log_k1 0.3719 0.2370 0.5068 +SD.log_k2 0.2921 0.0994 0.4848 +SD.log_tb 0.2535 -0.0664 0.5735 + +Variance model: + est. lower upper +a.1 4.495 3.777 5.213 + +Backtransformed parameters: + est. lower upper +meso_0 93.325994 9.147e+01 9.519e+01 +k1 0.002984 6.954e-04 1.280e-02 +k2 0.001118 1.568e-04 7.969e-03 +tb 25.706437 3.480e+00 1.899e+02 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 15.65 79.63 23.97 15.16 27.55 + +</code></pre> +<p> </p> +<caption> +Refined hierarchichal HS fit with pH influence +</caption> +<pre><code> +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Tue May 13 20:00:22 2025 +Date of summary: Tue May 13 20:00:23 2025 + +Equations: +d_meso/dt = - ifelse(time <= tb, k1, k2) * meso + +Data: +116 observations of 1 variable(s) grouped in 18 datasets + +Model predictions using solution type analytical + +Fitted in 1.439 s +Using 300, 100 iterations and 3 chains + +Variance model: Constant variance + +Starting values for degradation parameters: +meso_0 log_k1 log_k2 log_tb +92.920 -2.409 -3.295 2.471 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + meso_0 log_k1 log_k2 log_tb +meso_0 6.477 0.0000 0.0000 0.00 +log_k1 0.000 0.8675 0.0000 0.00 +log_k2 0.000 0.0000 0.4035 0.00 +log_tb 0.000 0.0000 0.0000 1.16 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 766.5 775.4 -373.2 + +Optimised parameters: + est. lower upper +meso_0 93.3251 91.49823 95.1520 +log_k1 -5.6796 -7.08789 -4.2714 +beta_pH(log_k1) 0.4567 0.22400 0.6894 +log_k2 -6.6083 -8.33839 -4.8781 +beta_pH(log_k2) 0.4982 0.20644 0.7899 +log_tb 2.7040 2.33033 3.0777 +a.1 4.4452 3.73537 5.1551 +SD.log_k1 0.3570 0.22104 0.4930 +SD.log_k2 0.2252 0.01864 0.4318 +SD.log_tb 0.5488 0.24560 0.8521 + +Correlation: + meso_0 log_k1 b_H(_1) log_k2 b_H(_2) +log_k1 0.0740 +beta_pH(log_k1) -0.0453 -0.9912 +log_k2 0.0115 -0.0650 0.0661 +beta_pH(log_k2) -0.0116 0.0649 -0.0667 -0.9936 +log_tb -0.0658 -0.1135 0.0913 -0.1500 0.1210 + +Random effects: + est. lower upper +SD.log_k1 0.3570 0.22104 0.4930 +SD.log_k2 0.2252 0.01864 0.4318 +SD.log_tb 0.5488 0.24560 0.8521 + +Variance model: + est. lower upper +a.1 4.445 3.735 5.155 + +Backtransformed parameters: + est. lower upper +meso_0 93.325134 9.150e+01 95.152036 +k1 0.003415 8.352e-04 0.013962 +k2 0.001349 2.392e-04 0.007611 +tb 14.939247 1.028e+01 21.707445 + +Covariates used for endpoints below: + pH +50% 5.75 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +meso 14.69 82.45 24.82 14.69 29.29 + +</code></pre> +<p></p> +</div> +</div> +<div class="section level3"> +<h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> +</h3> +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu +Running under: Debian GNU/Linux 12 (bookworm) + +Matrix products: default +BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 + +locale: + [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C + [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=de_DE.UTF-8 + [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 + [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C + [9] LC_ADDRESS=C LC_TELEPHONE=C +[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C + +time zone: Europe/Berlin +tzcode source: system (glibc) + +attached base packages: +[1] parallel stats graphics grDevices utils datasets methods +[8] base + +other attached packages: +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 + +loaded via a namespace (and not attached): + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.2.1 + [9] scales_1.3.0 textshaping_1.0.0 readxl_1.4.4 yaml_2.3.10 +[13] fastmap_1.2.0 lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 +[17] generics_0.1.3 lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 +[21] tibble_3.2.1 desc_1.4.3 munsell_0.5.1 bslib_0.9.0 +[25] pillar_1.10.1 rlang_1.1.5 cachem_1.1.0 xfun_0.51 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.5.0 mclust_6.1.1 +[37] lifecycle_1.0.4 nlme_3.1-168 vctrs_0.6.5 evaluate_1.0.3 +[41] glue_1.8.0 cellranger_1.1.0 codetools_0.2-20 ragg_1.3.3 +[45] zoo_1.8-13 colorspace_2.1-1 tools_4.5.0 pkgconfig_2.0.3 +[49] htmltools_0.5.8.1</code></pre> +</div> +<div class="section level3"> +<h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> +</h3> +<pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> +<pre><code>MemTotal: 64927780 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kinetics with residue data on mesotrione</a></li> + <li><a class="dropdown-item" href="../../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/multistart.html">Short demo of the multistart method</a></li> + <li><hr class="dropdown-divider"></li> + <li><h6 class="dropdown-header" data-toc-skip>Performance</h6></li> + <li><a class="dropdown-item" href="../../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/benchmarks.html">Benchmark timings for mkin</a></li> + <li><a class="dropdown-item" href="../../articles/web_only/saem_benchmarks.html">Benchmark timings for 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-(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</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="d-none name"><code>multistart.rmd</code></div> @@ -167,28 +153,26 @@ 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> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/web_only/multistart_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/multistart_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd6..00000000 --- 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<h1>Benchmark timings for saem.mmkin</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change 17 February 2023 -(rebuilt 2023-11-16)</h4> +(rebuilt 2025-05-12)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/saem_benchmarks.rmd" class="external-link"><code>vignettes/web_only/saem_benchmarks.rmd</code></a></small> <div class="d-none name"><code>saem_benchmarks.rmd</code></div> @@ -293,11 +279,11 @@ systems. All trademarks belong to their respective owners.</p> <h3 id="parent-only-1">Parent only<a class="anchor" aria-label="anchor" href="#parent-only-1"></a> </h3> <p>Constant variance for SFO, DFOP, SFORB and HS.</p> -<table style="width:100%;" class="table"> +<table class="table"> <colgroup> <col width="48%"> <col width="7%"> -<col width="7%"> +<col width="8%"> <col width="8%"> <col width="7%"> <col width="7%"> @@ -405,14 +391,44 @@ systems. All trademarks belong to their respective owners.</p> <td align="right">2.406</td> <td align="right">2.478</td> </tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.9</td> +<td align="left">3.3</td> +<td align="right">1.086</td> +<td align="right">1.991</td> +<td align="right">1.949</td> +<td align="right">2.411</td> +</tr> +<tr class="odd"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">1.115</td> +<td align="right">2.263</td> +<td align="right">1.991</td> +<td align="right">2.193</td> +</tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">1.876</td> +<td align="right">1.922</td> +<td align="right">2.423</td> +<td align="right">1.849</td> +</tr> </tbody> </table> <p>Two-component error fits for SFO, DFOP, SFORB and HS.</p> -<table style="width:100%;" class="table"> +<table class="table"> <colgroup> <col width="48%"> <col width="7%"> -<col width="7%"> +<col width="8%"> <col width="8%"> <col width="7%"> <col width="7%"> @@ -520,6 +536,36 @@ systems. All trademarks belong to their respective owners.</p> <td align="right">3.669</td> <td align="right">3.153</td> </tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.9</td> +<td align="left">3.3</td> +<td align="right">2.426</td> +<td align="right">3.196</td> +<td align="right">3.256</td> +<td align="right">3.322</td> +</tr> +<tr class="odd"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">2.380</td> +<td align="right">3.147</td> +<td align="right">3.131</td> +<td align="right">3.331</td> +</tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">2.397</td> +<td align="right">3.443</td> +<td align="right">3.414</td> +<td align="right">3.311</td> +</tr> </tbody> </table> </div> @@ -527,11 +573,11 @@ systems. All trademarks belong to their respective owners.</p> <h3 id="one-metabolite-1">One metabolite<a class="anchor" aria-label="anchor" href="#one-metabolite-1"></a> </h3> <p>Two-component error for DFOP-SFO and SFORB-SFO.</p> -<table class="table"> +<table style="width:100%;" class="table"> <colgroup> -<col width="54%"> -<col width="8%"> -<col width="8%"> +<col width="53%"> +<col width="7%"> +<col width="9%"> <col width="9%"> <col width="9%"> <col width="10%"> @@ -617,6 +663,30 @@ systems. All trademarks belong to their respective owners.</p> <td align="right">12.007</td> <td align="right">286.757</td> </tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.9</td> +<td align="left">3.3</td> +<td align="right">12.420</td> +<td align="right">289.338</td> +</tr> +<tr class="odd"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">11.581</td> +<td align="right">296.184</td> +</tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">12.067</td> +<td align="right">278.742</td> +</tr> </tbody> </table> </div> @@ -624,13 +694,13 @@ systems. All trademarks belong to their respective owners.</p> <h3 id="three-metabolites-1">Three metabolites<a class="anchor" aria-label="anchor" href="#three-metabolites-1"></a> </h3> <p>Two-component error for SFORB-SFO3-plus</p> -<table style="width:100%;" class="table"> +<table class="table"> <colgroup> -<col width="59%"> -<col width="8%"> +<col width="58%"> <col width="8%"> <col width="10%"> -<col width="13%"> +<col width="10%"> +<col width="12%"> </colgroup> <thead><tr class="header"> <th align="left">CPU</th> @@ -703,32 +773,51 @@ systems. All trademarks belong to their respective owners.</p> <td align="left">3.2</td> <td align="right">480.577</td> </tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.9</td> +<td align="left">3.3</td> +<td align="right">485.836</td> +</tr> +<tr class="odd"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">486.856</td> +</tr> +<tr class="even"> +<td align="left">Ryzen 9 7950X</td> +<td align="left">Linux</td> +<td align="left">1.2.10</td> +<td align="left">3.3</td> +<td align="right">474.550</td> +</tr> </tbody> </table> </div> </div> - </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </nav></aside> </div> <footer><div class="pkgdown-footer-left"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown-footer-right"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> </footer> </div> - - + + </body> </html> diff --git a/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd6..00000000 --- a/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js +++ /dev/null @@ -1,15 +0,0 @@ -// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> -// v0.0.1 -// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. - -document.addEventListener('DOMContentLoaded', function() { - const codeList = document.getElementsByClassName("sourceCode"); - for (var i = 0; i < codeList.length; i++) { - var linkList = codeList[i].getElementsByTagName('a'); - for (var j = 0; j < linkList.length; j++) { - if (linkList[j].innerHTML === "") { - linkList[j].setAttribute('aria-hidden', 'true'); - } - } - } -}); |
