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- </header><div class="row"> - <div class="col-md-9 contents"> - <div class="page-header toc-ignore"> - <h1 data-toc-skip>Testing hierarchical pathway kinetics with -residue data on cyantraniliprole</h1> + +<div class="row"> + <main id="main" class="col-md-9"><div class="page-header"> + + <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 19 Mai 2023</h4> + <h4 data-toc-skip class="date">Last change on 13 February +2023, last compiled on 16 Februar 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="hidden name"><code>2022_cyan_pathway.rmd</code></div> - + <div class="d-none name"><code>2022_cyan_pathway.rmd</code></div> </div> @@ -156,7 +104,7 @@ 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 1.2.5 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 @@ -1357,9 +1305,9 @@ when the two-component error model is used.</p> <tr class="odd"> <td align="left">SFORB tc</td> <td align="right">10</td> -<td align="right">700.1</td> -<td align="right">696.2</td> -<td align="right">-340.1</td> +<td align="right">700.0</td> +<td align="right">696.1</td> +<td align="right">-340.0</td> </tr> <tr class="even"> <td align="left">HS tc</td> @@ -1448,7 +1396,7 @@ pathway fits are performed for all datasets.</p> <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> </tr> <tr class="even"> @@ -1512,7 +1460,7 @@ pathway fits are performed for all datasets.</p> <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">dfop_path_1</td> @@ -1525,7 +1473,7 @@ pathway fits are performed for all datasets.</p> <tr class="even"> <td align="left">sforb_path_1</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> @@ -1536,7 +1484,7 @@ pathway fits are performed for all datasets.</p> <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> </tr> </tbody> </table> @@ -1565,7 +1513,7 @@ which is currently under development.</p> <tbody> <tr class="odd"> <td align="left">sfo_path_1</td> -<td align="left">Fth, FO</td> +<td align="left">FO</td> <td align="left">Fth, FO</td> </tr> <tr class="even"> @@ -1585,8 +1533,8 @@ which is currently under development.</p> </tr> <tr class="odd"> <td align="left">hs_path_1</td> -<td align="left">Fth, FO</td> -<td align="left">Fth, FO</td> +<td align="left">FO</td> +<td align="left">E</td> </tr> </tbody> </table> @@ -1635,14 +1583,62 @@ sd(f_JCZ38_qlogis)</td> <tr class="odd"> <td align="left">hs_path_1</td> <td align="left">NA</td> -<td align="left">NA</td> +<td align="left">E</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> @@ -1655,30 +1651,30 @@ or SFORB for the parent compound provide the best fit.</p> <tr class="odd"> <td align="left">sfo_path_1 const</td> <td align="right">16</td> -<td align="right">2692.8</td> -<td align="right">2686.6</td> -<td align="right">-1330.4</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">sfo_path_1 tc</td> <td align="right">17</td> -<td align="right">2657.7</td> -<td align="right">2651.1</td> -<td align="right">-1311.9</td> +<td align="right">2657.6</td> +<td align="right">2651.0</td> +<td align="right">-1311.8</td> </tr> <tr class="odd"> <td align="left">fomc_path_1 const</td> <td align="right">18</td> -<td align="right">2427.8</td> -<td align="right">2420.8</td> -<td align="right">-1195.9</td> +<td align="right">2427.9</td> +<td align="right">2420.9</td> +<td align="right">-1196.0</td> </tr> <tr class="even"> <td align="left">fomc_path_1 tc</td> <td align="right">19</td> -<td align="right">2423.4</td> -<td align="right">2416.0</td> -<td align="right">-1192.7</td> +<td align="right">2423.6</td> +<td align="right">2416.2</td> +<td align="right">-1192.8</td> </tr> <tr class="odd"> <td align="left">dfop_path_1 const</td> @@ -1695,45 +1691,31 @@ 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">2427.3</td> -<td align="right">2419.5</td> -<td align="right">-1193.7</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">2390.2</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">2399.8</td> -<td align="right">2392.0</td> -<td align="right">-1179.9</td> -</tr> -<tr class="even"> -<td align="left">hs_path_1 tc</td> -<td align="right">21</td> -<td align="right">2422.3</td> -<td align="right">2414.1</td> -<td align="right">-1190.2</td> +<td align="right">2399.9</td> +<td align="right">2392.1</td> +<td align="right">-1180.0</td> </tr> </tbody> </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"> @@ -1743,7 +1725,7 @@ 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"> @@ -1757,7 +1739,7 @@ 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> @@ -1828,14 +1810,14 @@ alternative pathway fits.</p> <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> </tr> </tbody> </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"> @@ -1851,7 +1833,7 @@ the fits to the Sassafras soil data.</p> <tr class="odd"> <td align="left">fomc_path_2</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> @@ -1859,7 +1841,7 @@ the fits to the Sassafras soil data.</p> <tr class="even"> <td align="left">dfop_path_2</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> @@ -1869,7 +1851,7 @@ the fits to the Sassafras soil data.</p> <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> </tr> </tbody> @@ -1877,11 +1859,11 @@ 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"> @@ -1892,8 +1874,8 @@ parent and the Sassafras dataset.</p> <tbody> <tr class="odd"> <td align="left">fomc_path_2</td> +<td align="left">E</td> <td align="left">OK</td> -<td align="left">FO</td> </tr> <tr class="even"> <td align="left">dfop_path_2</td> @@ -1908,8 +1890,9 @@ 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> @@ -1925,8 +1908,8 @@ successfully.</p> <tbody> <tr class="odd"> <td align="left">fomc_path_2</td> -<td align="left">sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)</td> -<td align="left">NA</td> +<td align="left">E</td> +<td align="left">sd(f_JSE76_qlogis)</td> </tr> <tr class="even"> <td align="left">dfop_path_2</td> @@ -1940,11 +1923,12 @@ 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> @@ -1955,32 +1939,52 @@ JCZ38 are ill-defined.</p> </tr></thead> <tbody> <tr class="odd"> -<td align="left">fomc_path_2 const</td> -<td align="right">20</td> -<td align="right">2308.3</td> -<td align="right">2300.5</td> -<td align="right">-1134.2</td> -</tr> -<tr class="even"> <td align="left">fomc_path_2 tc</td> <td align="right">21</td> -<td align="right">2248.3</td> -<td align="right">2240.1</td> -<td align="right">-1103.2</td> +<td align="right">2249.0</td> +<td align="right">2240.8</td> +<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">2289.6</td> -<td align="right">2281.0</td> -<td align="right">-1122.8</td> +<td align="right">2288.4</td> +<td align="right">2279.8</td> +<td align="right">-1122.2</td> </tr> <tr class="even"> <td align="left">sforb_path_2 const</td> <td align="right">22</td> -<td align="right">2284.1</td> -<td align="right">2275.5</td> -<td align="right">-1120.0</td> +<td align="right">2283.3</td> +<td align="right">2274.7</td> +<td align="right">-1119.7</td> </tr> <tr class="odd"> <td align="left">dfop_path_2 tc</td> @@ -1992,9 +1996,9 @@ JCZ38 are ill-defined.</p> <tr class="even"> <td align="left">sforb_path_2 tc</td> <td align="right">22</td> -<td align="right">2240.4</td> -<td align="right">2231.8</td> -<td align="right">-1098.2</td> +<td align="right">2239.7</td> +<td align="right">2231.1</td> +<td align="right">-1097.9</td> </tr> </tbody> </table> @@ -2004,21 +2008,21 @@ 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"> @@ -2036,7 +2040,7 @@ 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> @@ -2051,7 +2055,7 @@ 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"> @@ -2081,7 +2085,7 @@ 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"> @@ -2107,8 +2111,8 @@ 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> @@ -2121,37 +2125,64 @@ confidence intervals for the optimised parameters are available.</p> <tr class="odd"> <td align="left">fomc_path_2 tc</td> <td align="right">19</td> -<td align="right">2250.9</td> -<td align="right">2243.5</td> -<td align="right">-1106.5</td> +<td align="right">2249.1</td> +<td align="right">2241.6</td> +<td align="right">-1105.5</td> </tr> <tr class="even"> -<td align="left">dfop_path_2 const</td> +<td align="left">dfop_path_2 tc</td> <td align="right">20</td> -<td align="right">2281.7</td> -<td align="right">2273.9</td> -<td align="right">-1120.8</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 const</td> +<td align="left">sforb_path_2 tc</td> <td align="right">20</td> -<td align="right">2279.5</td> -<td align="right">2271.7</td> -<td align="right">-1119.7</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="even"> -<td align="left">dfop_path_2 tc</td> +<td align="left">sforb_path_2 const</td> <td align="right">20</td> -<td align="right">2231.5</td> -<td align="right">2223.7</td> -<td align="right">-1095.8</td> +<td align="right">2279.7</td> +<td align="right">2271.9</td> +<td align="right">-1119.9</td> </tr> <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="even"> <td align="left">sforb_path_2 tc</td> <td align="right">20</td> -<td align="right">2235.7</td> -<td align="right">2227.9</td> -<td align="right">-1097.9</td> +<td align="right">2241.3</td> +<td align="right">2233.5</td> +<td align="right">-1100.7</td> </tr> </tbody> </table> @@ -2159,7 +2190,7 @@ 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> @@ -2187,21 +2218,21 @@ 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"> @@ -2219,11 +2250,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:42:02 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:42:26 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - k_cyan * cyan @@ -2236,7 +2267,7 @@ Data: Model predictions using solution type deSolve -Fitted in 443.997 s +Fitted in 437.151 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -2245,7 +2276,7 @@ Starting values for degradation parameters: cyan_0 log_k_cyan log_k_JCZ38 log_k_J9Z38 log_k_JSE76 95.3304 -3.8459 -3.1305 -5.0678 -5.3196 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis - 0.8158 22.5404 10.4289 + 0.8158 23.5335 11.8774 Fixed degradation parameter values: None @@ -2267,8 +2298,8 @@ log_k_JCZ38 0.0000 0.000 0.00 log_k_J9Z38 0.0000 0.000 0.00 log_k_JSE76 0.0000 0.000 0.00 f_cyan_ilr_1 0.7714 0.000 0.00 -f_cyan_ilr_2 0.0000 8.684 0.00 -f_JCZ38_qlogis 0.0000 0.000 13.48 +f_cyan_ilr_2 0.0000 9.247 0.00 +f_JCZ38_qlogis 0.0000 0.000 16.61 Starting values for error model parameters: a.1 @@ -2278,68 +2309,68 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2693 2687 -1330 + 2693 2687 -1331 Optimised parameters: - est. lower upper -cyan_0 95.0946 NA NA -log_k_cyan -3.8544 NA NA -log_k_JCZ38 -3.0402 NA NA -log_k_J9Z38 -5.0109 NA NA -log_k_JSE76 -5.2857 NA NA -f_cyan_ilr_1 0.8069 NA NA -f_cyan_ilr_2 16.6623 NA NA -f_JCZ38_qlogis 1.3602 NA NA -a.1 4.8326 NA NA -SD.log_k_cyan 0.5842 NA NA -SD.log_k_JCZ38 1.2680 NA NA -SD.log_k_J9Z38 0.3626 NA NA -SD.log_k_JSE76 0.5244 NA NA -SD.f_cyan_ilr_1 0.2752 NA NA -SD.f_cyan_ilr_2 2.3556 NA NA -SD.f_JCZ38_qlogis 0.2400 NA NA + est. lower upper +cyan_0 95.1279 9.354e+01 9.671e+01 +log_k_cyan -3.8527 -4.367e+00 -3.338e+00 +log_k_JCZ38 -3.0381 -4.187e+00 -1.889e+00 +log_k_J9Z38 -5.0095 -5.623e+00 -4.396e+00 +log_k_JSE76 -5.3357 -6.025e+00 -4.646e+00 +f_cyan_ilr_1 0.8050 5.174e-01 1.093e+00 +f_cyan_ilr_2 12.4820 -1.050e+06 1.051e+06 +f_JCZ38_qlogis 1.2912 3.561e-01 2.226e+00 +a.1 4.8393 NA NA +SD.log_k_cyan 0.5840 NA NA +SD.log_k_JCZ38 1.2740 NA NA +SD.log_k_J9Z38 0.3172 NA NA +SD.log_k_JSE76 0.5677 NA NA +SD.f_cyan_ilr_1 0.2623 NA NA +SD.f_cyan_ilr_2 1.3724 NA NA +SD.f_JCZ38_qlogis 0.1464 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_cyan 0.5842 NA NA -SD.log_k_JCZ38 1.2680 NA NA -SD.log_k_J9Z38 0.3626 NA NA -SD.log_k_JSE76 0.5244 NA NA -SD.f_cyan_ilr_1 0.2752 NA NA -SD.f_cyan_ilr_2 2.3556 NA NA -SD.f_JCZ38_qlogis 0.2400 NA NA +SD.log_k_cyan 0.5840 NA NA +SD.log_k_JCZ38 1.2740 NA NA +SD.log_k_J9Z38 0.3172 NA NA +SD.log_k_JSE76 0.5677 NA NA +SD.f_cyan_ilr_1 0.2623 NA NA +SD.f_cyan_ilr_2 1.3724 NA NA +SD.f_JCZ38_qlogis 0.1464 NA NA Variance model: est. lower upper -a.1 4.833 NA NA +a.1 4.839 NA NA Backtransformed parameters: - est. lower upper -cyan_0 95.094581 NA NA -k_cyan 0.021186 NA NA -k_JCZ38 0.047825 NA NA -k_J9Z38 0.006665 NA NA -k_JSE76 0.005063 NA NA -f_cyan_to_JCZ38 0.757885 NA NA -f_cyan_to_J9Z38 0.242115 NA NA -f_JCZ38_to_JSE76 0.795792 NA NA + est. lower upper +cyan_0 95.127935 93.542456 96.713413 +k_cyan 0.021221 0.012687 0.035497 +k_JCZ38 0.047924 0.015189 0.151213 +k_J9Z38 0.006674 0.003612 0.012332 +k_JSE76 0.004817 0.002417 0.009601 +f_cyan_to_JCZ38 0.757402 NA NA +f_cyan_to_J9Z38 0.242597 NA NA +f_JCZ38_to_JSE76 0.784347 0.588098 0.902582 Resulting formation fractions: ff -cyan_JCZ38 7.579e-01 -cyan_J9Z38 2.421e-01 -cyan_sink 5.877e-10 -JCZ38_JSE76 7.958e-01 -JCZ38_sink 2.042e-01 +cyan_JCZ38 7.574e-01 +cyan_J9Z38 2.426e-01 +cyan_sink 9.839e-08 +JCZ38_JSE76 7.843e-01 +JCZ38_sink 2.157e-01 Estimated disappearance times: DT50 DT90 -cyan 32.72 108.68 -JCZ38 14.49 48.15 -J9Z38 103.99 345.46 -JSE76 136.90 454.76 +cyan 32.66 108.50 +JCZ38 14.46 48.05 +J9Z38 103.86 345.00 +JSE76 143.91 478.04 </code></pre> <p></p> @@ -2347,11 +2378,11 @@ JSE76 136.90 454.76 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:42:01 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:42:06 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - k_cyan * cyan @@ -2364,7 +2395,7 @@ Data: Model predictions using solution type deSolve -Fitted in 442.545 s +Fitted in 417.143 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -2373,7 +2404,7 @@ Starting values for degradation parameters: cyan_0 log_k_cyan log_k_JCZ38 log_k_J9Z38 log_k_JSE76 96.0039 -3.8907 -3.1276 -5.0069 -4.9367 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis - 0.7937 20.0030 15.1336 + 0.7937 22.3422 17.8932 Fixed degradation parameter values: None @@ -2395,8 +2426,8 @@ log_k_JCZ38 0.0000 0.000 0.00 log_k_J9Z38 0.0000 0.000 0.00 log_k_JSE76 0.0000 0.000 0.00 f_cyan_ilr_1 0.7598 0.000 0.00 -f_cyan_ilr_2 0.0000 7.334 0.00 -f_JCZ38_qlogis 0.0000 0.000 11.78 +f_cyan_ilr_2 0.0000 8.939 0.00 +f_JCZ38_qlogis 0.0000 0.000 14.49 Starting values for error model parameters: a.1 b.1 @@ -2410,66 +2441,66 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -cyan_0 94.72923 NA NA -log_k_cyan -3.91670 NA NA -log_k_JCZ38 -3.12917 NA NA -log_k_J9Z38 -5.06070 NA NA -log_k_JSE76 -5.09254 NA NA -f_cyan_ilr_1 0.81116 NA NA -f_cyan_ilr_2 39.97850 NA NA -f_JCZ38_qlogis 3.09728 NA NA -a.1 3.95044 NA NA -b.1 0.07998 NA NA -SD.log_k_cyan 0.58855 NA NA -SD.log_k_JCZ38 1.29753 NA NA -SD.log_k_J9Z38 0.62851 NA NA -SD.log_k_JSE76 0.37235 NA NA -SD.f_cyan_ilr_1 0.37346 NA NA -SD.f_cyan_ilr_2 1.41667 NA NA -SD.f_JCZ38_qlogis 1.81467 NA NA +cyan_0 94.81681 NA NA +log_k_cyan -3.91558 NA NA +log_k_JCZ38 -3.12715 NA NA +log_k_J9Z38 -5.04840 NA NA +log_k_JSE76 -5.10443 NA NA +f_cyan_ilr_1 0.80760 NA NA +f_cyan_ilr_2 48.66960 NA NA +f_JCZ38_qlogis 3.03397 NA NA +a.1 3.93879 NA NA +b.1 0.08057 NA NA +SD.log_k_cyan 0.58921 NA NA +SD.log_k_JCZ38 1.29813 NA NA +SD.log_k_J9Z38 0.68372 NA NA +SD.log_k_JSE76 0.35128 NA NA +SD.f_cyan_ilr_1 0.38352 NA NA +SD.f_cyan_ilr_2 4.98884 NA NA +SD.f_JCZ38_qlogis 1.75636 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_cyan 0.5886 NA NA -SD.log_k_JCZ38 1.2975 NA NA -SD.log_k_J9Z38 0.6285 NA NA -SD.log_k_JSE76 0.3724 NA NA -SD.f_cyan_ilr_1 0.3735 NA NA -SD.f_cyan_ilr_2 1.4167 NA NA -SD.f_JCZ38_qlogis 1.8147 NA NA +SD.log_k_cyan 0.5892 NA NA +SD.log_k_JCZ38 1.2981 NA NA +SD.log_k_J9Z38 0.6837 NA NA +SD.log_k_JSE76 0.3513 NA NA +SD.f_cyan_ilr_1 0.3835 NA NA +SD.f_cyan_ilr_2 4.9888 NA NA +SD.f_JCZ38_qlogis 1.7564 NA NA Variance model: est. lower upper -a.1 3.95044 NA NA -b.1 0.07998 NA NA +a.1 3.93879 NA NA +b.1 0.08057 NA NA Backtransformed parameters: - est. lower upper -cyan_0 94.729229 NA NA -k_cyan 0.019907 NA NA -k_JCZ38 0.043754 NA NA -k_J9Z38 0.006341 NA NA -k_JSE76 0.006142 NA NA -f_cyan_to_JCZ38 0.758991 NA NA -f_cyan_to_J9Z38 0.241009 NA NA -f_JCZ38_to_JSE76 0.956781 NA NA + est. lower upper +cyan_0 94.81681 NA NA +k_cyan 0.01993 NA NA +k_JCZ38 0.04384 NA NA +k_J9Z38 0.00642 NA NA +k_JSE76 0.00607 NA NA +f_cyan_to_JCZ38 0.75807 NA NA +f_cyan_to_J9Z38 0.24193 NA NA +f_JCZ38_to_JSE76 0.95409 NA NA Resulting formation fractions: ff -cyan_JCZ38 0.75899 -cyan_J9Z38 0.24101 +cyan_JCZ38 0.75807 +cyan_J9Z38 0.24193 cyan_sink 0.00000 -JCZ38_JSE76 0.95678 -JCZ38_sink 0.04322 +JCZ38_JSE76 0.95409 +JCZ38_sink 0.04591 Estimated disappearance times: DT50 DT90 -cyan 34.82 115.67 -JCZ38 15.84 52.63 -J9Z38 109.31 363.12 -JSE76 112.85 374.87 +cyan 34.78 115.54 +JCZ38 15.81 52.52 +J9Z38 107.97 358.68 +JSE76 114.20 379.35 </code></pre> <p></p> @@ -2477,11 +2508,11 @@ JSE76 112.85 374.87 Hierarchical FOMC path 1 fit with constant variance </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:42:38 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:42:57 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -2496,7 +2527,7 @@ Data: Model predictions using solution type deSolve -Fitted in 479.463 s +Fitted in 468.609 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -2505,7 +2536,7 @@ Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 101.2314 -3.3680 -5.1108 -5.9416 0.7144 f_cyan_ilr_2 f_JCZ38_qlogis log_alpha log_beta - 7.3870 15.7604 -0.1791 2.9811 + 7.0229 14.9234 -0.1791 2.9811 Fixed degradation parameter values: None @@ -2527,8 +2558,8 @@ log_k_JCZ38 0.00 0.00 0.0000 0.0000 log_k_J9Z38 0.00 0.00 0.0000 0.0000 log_k_JSE76 0.00 0.00 0.0000 0.0000 f_cyan_ilr_1 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 12.33 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.00 20.42 0.0000 0.0000 +f_cyan_ilr_2 11.57 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 18.81 0.0000 0.0000 log_alpha 0.00 0.00 0.4144 0.0000 log_beta 0.00 0.00 0.0000 0.5077 @@ -2543,78 +2574,78 @@ Likelihood computed by importance sampling 2428 2421 -1196 Optimised parameters: - est. lower upper -cyan_0 101.0225 98.306270 103.7387 -log_k_JCZ38 -3.3786 -4.770657 -1.9866 -log_k_J9Z38 -5.2603 -5.902085 -4.6186 -log_k_JSE76 -6.1427 -7.318336 -4.9671 -f_cyan_ilr_1 0.7437 0.421215 1.0663 -f_cyan_ilr_2 0.9108 0.267977 1.5537 -f_JCZ38_qlogis 2.0487 0.524897 3.5724 -log_alpha -0.2268 -0.618049 0.1644 -log_beta 2.8986 2.700701 3.0964 -a.1 3.4058 3.169913 3.6416 -SD.cyan_0 2.5279 0.454190 4.6016 -SD.log_k_JCZ38 1.5636 0.572824 2.5543 -SD.log_k_J9Z38 0.5316 -0.004405 1.0677 -SD.log_k_JSE76 0.9903 0.106325 1.8742 -SD.f_cyan_ilr_1 0.3464 0.112066 0.5807 -SD.f_cyan_ilr_2 0.2804 -0.393900 0.9546 -SD.f_JCZ38_qlogis 0.9416 -0.152986 2.0362 -SD.log_alpha 0.4273 0.161044 0.6936 + est. lower upper +cyan_0 101.1664 98.51265 103.8202 +log_k_JCZ38 -3.3883 -4.78250 -1.9941 +log_k_J9Z38 -5.3087 -5.91564 -4.7017 +log_k_JSE76 -6.1313 -7.30061 -4.9619 +f_cyan_ilr_1 0.7456 0.43782 1.0534 +f_cyan_ilr_2 0.8181 0.24956 1.3866 +f_JCZ38_qlogis 2.0467 0.61165 3.4817 +log_alpha -0.2391 -0.62806 0.1499 +log_beta 2.8739 2.67664 3.0711 +a.1 3.4160 3.17960 3.6525 +SD.cyan_0 2.4355 0.40399 4.4671 +SD.log_k_JCZ38 1.5654 0.57311 2.5576 +SD.log_k_J9Z38 0.4645 -0.06533 0.9943 +SD.log_k_JSE76 0.9841 0.10738 1.8609 +SD.f_cyan_ilr_1 0.3285 0.10546 0.5515 +SD.f_cyan_ilr_2 0.2276 -0.38711 0.8424 +SD.f_JCZ38_qlogis 0.8340 -0.20970 1.8777 +SD.log_alpha 0.4250 0.16017 0.6898 Correlation: cyan_0 l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 log_lph -log_k_JCZ38 -0.0156 -log_k_J9Z38 -0.0493 0.0073 -log_k_JSE76 -0.0329 0.0018 0.0069 -f_cyan_ilr_1 -0.0086 0.0180 -0.1406 0.0012 -f_cyan_ilr_2 -0.2629 0.0779 0.2826 0.0274 0.0099 -f_JCZ38_qlogis 0.0713 -0.0747 -0.0505 0.1169 -0.1022 -0.4893 -log_alpha -0.0556 0.0120 0.0336 0.0193 0.0036 0.0840 -0.0489 -log_beta -0.2898 0.0460 0.1305 0.0768 0.0190 0.4071 -0.1981 0.2772 +log_k_JCZ38 -0.0159 +log_k_J9Z38 -0.0546 0.0080 +log_k_JSE76 -0.0337 0.0016 0.0074 +f_cyan_ilr_1 -0.0095 0.0194 -0.1573 0.0003 +f_cyan_ilr_2 -0.2733 0.0799 0.3059 0.0263 0.0125 +f_JCZ38_qlogis 0.0755 -0.0783 -0.0516 0.1222 -0.1155 -0.5231 +log_alpha -0.0567 0.0120 0.0351 0.0189 0.0040 0.0829 -0.0502 +log_beta -0.2980 0.0461 0.1382 0.0758 0.0209 0.4079 -0.2053 0.2759 Random effects: - est. lower upper -SD.cyan_0 2.5279 0.454190 4.6016 -SD.log_k_JCZ38 1.5636 0.572824 2.5543 -SD.log_k_J9Z38 0.5316 -0.004405 1.0677 -SD.log_k_JSE76 0.9903 0.106325 1.8742 -SD.f_cyan_ilr_1 0.3464 0.112066 0.5807 -SD.f_cyan_ilr_2 0.2804 -0.393900 0.9546 -SD.f_JCZ38_qlogis 0.9416 -0.152986 2.0362 -SD.log_alpha 0.4273 0.161044 0.6936 + est. lower upper +SD.cyan_0 2.4355 0.40399 4.4671 +SD.log_k_JCZ38 1.5654 0.57311 2.5576 +SD.log_k_J9Z38 0.4645 -0.06533 0.9943 +SD.log_k_JSE76 0.9841 0.10738 1.8609 +SD.f_cyan_ilr_1 0.3285 0.10546 0.5515 +SD.f_cyan_ilr_2 0.2276 -0.38711 0.8424 +SD.f_JCZ38_qlogis 0.8340 -0.20970 1.8777 +SD.log_alpha 0.4250 0.16017 0.6898 Variance model: est. lower upper -a.1 3.406 3.17 3.642 +a.1 3.416 3.18 3.652 Backtransformed parameters: est. lower upper -cyan_0 1.010e+02 9.831e+01 1.037e+02 -k_JCZ38 3.409e-02 8.475e-03 1.372e-01 -k_J9Z38 5.194e-03 2.734e-03 9.867e-03 -k_JSE76 2.149e-03 6.633e-04 6.963e-03 -f_cyan_to_JCZ38 6.481e-01 NA NA -f_cyan_to_J9Z38 2.264e-01 NA NA -f_JCZ38_to_JSE76 8.858e-01 6.283e-01 9.727e-01 -alpha 7.971e-01 5.390e-01 1.179e+00 -beta 1.815e+01 1.489e+01 2.212e+01 +cyan_0 1.012e+02 9.851e+01 103.82023 +k_JCZ38 3.377e-02 8.375e-03 0.13614 +k_J9Z38 4.948e-03 2.697e-03 0.00908 +k_JSE76 2.174e-03 6.751e-04 0.00700 +f_cyan_to_JCZ38 6.389e-01 NA NA +f_cyan_to_J9Z38 2.226e-01 NA NA +f_JCZ38_to_JSE76 8.856e-01 6.483e-01 0.97016 +alpha 7.873e-01 5.336e-01 1.16166 +beta 1.771e+01 1.454e+01 21.56509 Resulting formation fractions: ff -cyan_JCZ38 0.6481 -cyan_J9Z38 0.2264 -cyan_sink 0.1255 -JCZ38_JSE76 0.8858 -JCZ38_sink 0.1142 +cyan_JCZ38 0.6389 +cyan_J9Z38 0.2226 +cyan_sink 0.1385 +JCZ38_JSE76 0.8856 +JCZ38_sink 0.1144 Estimated disappearance times: DT50 DT90 DT50back -cyan 25.15 308.01 92.72 -JCZ38 20.33 67.54 NA -J9Z38 133.46 443.35 NA -JSE76 322.53 1071.42 NA +cyan 25.00 312.06 93.94 +JCZ38 20.53 68.19 NA +J9Z38 140.07 465.32 NA +JSE76 318.86 1059.22 NA </code></pre> <p></p> @@ -2622,11 +2653,11 @@ JSE76 322.53 1071.42 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:42:53 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:42:50 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -2641,41 +2672,41 @@ Data: Model predictions using solution type deSolve -Fitted in 494.121 s +Fitted in 460.309 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.13827 -3.32493 -5.08921 -5.93478 0.71330 + 101.13294 -3.32499 -5.09097 -5.93566 0.71359 f_cyan_ilr_2 f_JCZ38_qlogis log_alpha log_beta - 10.05989 12.79248 -0.09621 3.10646 + 10.30315 14.62272 -0.09633 3.10634 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.643 0.000 0.000 0.00 0.0000 -log_k_JCZ38 0.000 2.319 0.000 0.00 0.0000 -log_k_J9Z38 0.000 0.000 1.731 0.00 0.0000 -log_k_JSE76 0.000 0.000 0.000 1.86 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.00 0.7186 -f_cyan_ilr_2 0.000 0.000 0.000 0.00 0.0000 -f_JCZ38_qlogis 0.000 0.000 0.000 0.00 0.0000 -log_alpha 0.000 0.000 0.000 0.00 0.0000 -log_beta 0.000 0.000 0.000 0.00 0.0000 +cyan_0 5.649 0.000 0.00 0.00 0.0000 +log_k_JCZ38 0.000 2.319 0.00 0.00 0.0000 +log_k_J9Z38 0.000 0.000 1.73 0.00 0.0000 +log_k_JSE76 0.000 0.000 0.00 1.86 0.0000 +f_cyan_ilr_1 0.000 0.000 0.00 0.00 0.7183 +f_cyan_ilr_2 0.000 0.000 0.00 0.00 0.0000 +f_JCZ38_qlogis 0.000 0.000 0.00 0.00 0.0000 +log_alpha 0.000 0.000 0.00 0.00 0.0000 +log_beta 0.000 0.000 0.00 0.00 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis log_alpha log_beta cyan_0 0.00 0.00 0.0000 0.0000 log_k_JCZ38 0.00 0.00 0.0000 0.0000 log_k_J9Z38 0.00 0.00 0.0000 0.0000 log_k_JSE76 0.00 0.00 0.0000 0.0000 f_cyan_ilr_1 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 12.49 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.00 20.19 0.0000 0.0000 +f_cyan_ilr_2 12.85 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 18.54 0.0000 0.0000 log_alpha 0.00 0.00 0.3142 0.0000 -log_beta 0.00 0.00 0.0000 0.7331 +log_beta 0.00 0.00 0.0000 0.7333 Starting values for error model parameters: a.1 b.1 @@ -2685,74 +2716,74 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2423 2416 -1193 + 2424 2416 -1193 Optimised parameters: est. lower upper -cyan_0 100.57649 NA NA -log_k_JCZ38 -3.46250 NA NA -log_k_J9Z38 -5.24442 NA NA -log_k_JSE76 -5.75229 NA NA -f_cyan_ilr_1 0.68480 NA NA -f_cyan_ilr_2 0.61670 NA NA -f_JCZ38_qlogis 87.97407 NA NA -log_alpha -0.15699 NA NA -log_beta 3.01540 NA NA -a.1 3.11518 NA NA -b.1 0.04445 NA NA -SD.log_k_JCZ38 1.40732 NA NA -SD.log_k_J9Z38 0.56510 NA NA -SD.log_k_JSE76 0.72067 NA NA -SD.f_cyan_ilr_1 0.31199 NA NA -SD.f_cyan_ilr_2 0.36894 NA NA -SD.f_JCZ38_qlogis 6.92892 NA NA -SD.log_alpha 0.25662 NA NA -SD.log_beta 0.35845 NA NA +cyan_0 100.65667 NA NA +log_k_JCZ38 -3.45782 NA NA +log_k_J9Z38 -5.23476 NA NA +log_k_JSE76 -5.71827 NA NA +f_cyan_ilr_1 0.68389 NA NA +f_cyan_ilr_2 0.61027 NA NA +f_JCZ38_qlogis 116.27482 NA NA +log_alpha -0.14484 NA NA +log_beta 3.03220 NA NA +a.1 3.11051 NA NA +b.1 0.04508 NA NA +SD.log_k_JCZ38 1.39961 NA NA +SD.log_k_J9Z38 0.57920 NA NA +SD.log_k_JSE76 0.68364 NA NA +SD.f_cyan_ilr_1 0.31477 NA NA +SD.f_cyan_ilr_2 0.37716 NA NA +SD.f_JCZ38_qlogis 5.52695 NA NA +SD.log_alpha 0.22823 NA NA +SD.log_beta 0.39161 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_JCZ38 1.4073 NA NA -SD.log_k_J9Z38 0.5651 NA NA -SD.log_k_JSE76 0.7207 NA NA -SD.f_cyan_ilr_1 0.3120 NA NA -SD.f_cyan_ilr_2 0.3689 NA NA -SD.f_JCZ38_qlogis 6.9289 NA NA -SD.log_alpha 0.2566 NA NA -SD.log_beta 0.3585 NA NA +SD.log_k_JCZ38 1.3996 NA NA +SD.log_k_J9Z38 0.5792 NA NA +SD.log_k_JSE76 0.6836 NA NA +SD.f_cyan_ilr_1 0.3148 NA NA +SD.f_cyan_ilr_2 0.3772 NA NA +SD.f_JCZ38_qlogis 5.5270 NA NA +SD.log_alpha 0.2282 NA NA +SD.log_beta 0.3916 NA NA Variance model: est. lower upper -a.1 3.11518 NA NA -b.1 0.04445 NA NA +a.1 3.11051 NA NA +b.1 0.04508 NA NA Backtransformed parameters: est. lower upper -cyan_0 1.006e+02 NA NA -k_JCZ38 3.135e-02 NA NA -k_J9Z38 5.277e-03 NA NA -k_JSE76 3.175e-03 NA NA -f_cyan_to_JCZ38 5.991e-01 NA NA -f_cyan_to_J9Z38 2.275e-01 NA NA +cyan_0 1.007e+02 NA NA +k_JCZ38 3.150e-02 NA NA +k_J9Z38 5.328e-03 NA NA +k_JSE76 3.285e-03 NA NA +f_cyan_to_JCZ38 5.980e-01 NA NA +f_cyan_to_J9Z38 2.273e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA -alpha 8.547e-01 NA NA -beta 2.040e+01 NA NA +alpha 8.652e-01 NA NA +beta 2.074e+01 NA NA Resulting formation fractions: ff -cyan_JCZ38 0.5991 -cyan_J9Z38 0.2275 -cyan_sink 0.1734 +cyan_JCZ38 0.5980 +cyan_J9Z38 0.2273 +cyan_sink 0.1746 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 Estimated disappearance times: - DT50 DT90 DT50back -cyan 25.50 281.29 84.68 -JCZ38 22.11 73.44 NA -J9Z38 131.36 436.35 NA -JSE76 218.28 725.11 NA + DT50 DT90 DT50back +cyan 25.48 276.2 83.15 +JCZ38 22.01 73.1 NA +J9Z38 130.09 432.2 NA +JSE76 210.98 700.9 NA </code></pre> <p></p> @@ -2760,11 +2791,11 @@ JSE76 218.28 725.11 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:43:22 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:43:33 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -2783,16 +2814,16 @@ Data: Model predictions using solution type deSolve -Fitted in 523.691 s +Fitted in 504.014 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 102.0644 -3.4008 -5.0024 -5.8613 0.6855 + 102.0643 -3.4008 -5.0024 -5.8612 0.6855 f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 g_qlogis - 1.2365 13.7245 -1.8641 -4.5063 -0.6468 + 1.2366 13.6901 -1.8641 -4.5063 -0.6468 Fixed degradation parameter values: None @@ -2816,7 +2847,7 @@ log_k_J9Z38 0.00 0.00 0.0000 0.0000 0.000 log_k_JSE76 0.00 0.00 0.0000 0.0000 0.000 f_cyan_ilr_1 0.00 0.00 0.0000 0.0000 0.000 f_cyan_ilr_2 1.28 0.00 0.0000 0.0000 0.000 -f_JCZ38_qlogis 0.00 16.11 0.0000 0.0000 0.000 +f_JCZ38_qlogis 0.00 16.08 0.0000 0.0000 0.000 log_k1 0.00 0.00 0.9866 0.0000 0.000 log_k2 0.00 0.00 0.0000 0.5953 0.000 g_qlogis 0.00 0.00 0.0000 0.0000 1.583 @@ -2833,72 +2864,72 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -cyan_0 102.6079 NA NA -log_k_JCZ38 -3.4855 NA NA -log_k_J9Z38 -5.1686 NA NA -log_k_JSE76 -5.6697 NA NA -f_cyan_ilr_1 0.6714 NA NA -f_cyan_ilr_2 0.4986 NA NA -f_JCZ38_qlogis 55.4760 NA NA -log_k1 -1.8409 NA NA -log_k2 -4.4915 NA NA -g_qlogis -0.6403 NA NA -a.1 3.2387 NA NA -SD.log_k_JCZ38 1.4524 NA NA -SD.log_k_J9Z38 0.5151 NA NA -SD.log_k_JSE76 0.6514 NA NA -SD.f_cyan_ilr_1 0.3023 NA NA -SD.f_cyan_ilr_2 0.2959 NA NA -SD.f_JCZ38_qlogis 1.9984 NA NA -SD.log_k1 0.5188 NA NA -SD.log_k2 0.3894 NA NA -SD.g_qlogis 0.8579 NA NA +cyan_0 102.5565 NA NA +log_k_JCZ38 -3.4729 NA NA +log_k_J9Z38 -5.1533 NA NA +log_k_JSE76 -5.6669 NA NA +f_cyan_ilr_1 0.6665 NA NA +f_cyan_ilr_2 0.5191 NA NA +f_JCZ38_qlogis 37.0113 NA NA +log_k1 -1.8497 NA NA +log_k2 -4.4931 NA NA +g_qlogis -0.6383 NA NA +a.1 3.2397 NA NA +SD.log_k_JCZ38 1.4286 NA NA +SD.log_k_J9Z38 0.5312 NA NA +SD.log_k_JSE76 0.6627 NA NA +SD.f_cyan_ilr_1 0.3013 NA NA +SD.f_cyan_ilr_2 0.2980 NA NA +SD.f_JCZ38_qlogis 0.1637 NA NA +SD.log_k1 0.5069 NA NA +SD.log_k2 0.3828 NA NA +SD.g_qlogis 0.8641 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_JCZ38 1.4524 NA NA -SD.log_k_J9Z38 0.5151 NA NA -SD.log_k_JSE76 0.6514 NA NA -SD.f_cyan_ilr_1 0.3023 NA NA -SD.f_cyan_ilr_2 0.2959 NA NA -SD.f_JCZ38_qlogis 1.9984 NA NA -SD.log_k1 0.5188 NA NA -SD.log_k2 0.3894 NA NA -SD.g_qlogis 0.8579 NA NA +SD.log_k_JCZ38 1.4286 NA NA +SD.log_k_J9Z38 0.5312 NA NA +SD.log_k_JSE76 0.6627 NA NA +SD.f_cyan_ilr_1 0.3013 NA NA +SD.f_cyan_ilr_2 0.2980 NA NA +SD.f_JCZ38_qlogis 0.1637 NA NA +SD.log_k1 0.5069 NA NA +SD.log_k2 0.3828 NA NA +SD.g_qlogis 0.8641 NA NA Variance model: - est. lower upper -a.1 3.239 NA NA + est. lower upper +a.1 3.24 NA NA Backtransformed parameters: est. lower upper cyan_0 1.026e+02 NA NA -k_JCZ38 3.064e-02 NA NA -k_J9Z38 5.692e-03 NA NA -k_JSE76 3.449e-03 NA NA -f_cyan_to_JCZ38 5.798e-01 NA NA -f_cyan_to_J9Z38 2.243e-01 NA NA +k_JCZ38 3.103e-02 NA NA +k_J9Z38 5.780e-03 NA NA +k_JSE76 3.459e-03 NA NA +f_cyan_to_JCZ38 5.813e-01 NA NA +f_cyan_to_J9Z38 2.265e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA -k1 1.587e-01 NA NA -k2 1.120e-02 NA NA -g 3.452e-01 NA NA +k1 1.573e-01 NA NA +k2 1.119e-02 NA NA +g 3.456e-01 NA NA Resulting formation fractions: ff -cyan_JCZ38 0.5798 -cyan_J9Z38 0.2243 -cyan_sink 0.1958 +cyan_JCZ38 0.5813 +cyan_J9Z38 0.2265 +cyan_sink 0.1922 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 25.21 167.73 50.49 4.368 61.87 -JCZ38 22.62 75.15 NA NA NA -J9Z38 121.77 404.50 NA NA NA -JSE76 200.98 667.64 NA NA NA +cyan 25.23 167.94 50.55 4.407 61.97 +JCZ38 22.34 74.22 NA NA NA +J9Z38 119.92 398.36 NA NA NA +JSE76 200.41 665.76 NA NA NA </code></pre> <p></p> @@ -2906,11 +2937,11 @@ JSE76 200.98 667.64 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:46:08 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:46:07 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -2929,7 +2960,7 @@ Data: Model predictions using solution type deSolve -Fitted in 689.217 s +Fitted in 658.043 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -2938,7 +2969,7 @@ Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 101.3964 -3.3626 -4.9792 -5.8727 0.6814 f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 g_qlogis - 6.7799 13.7245 -1.9222 -4.5035 -0.7172 + 6.8713 13.6901 -1.9222 -4.5035 -0.7172 Fixed degradation parameter values: None @@ -2949,7 +2980,7 @@ cyan_0 5.317 0.000 0.000 0.000 0.0000 log_k_JCZ38 0.000 2.272 0.000 0.000 0.0000 log_k_J9Z38 0.000 0.000 1.633 0.000 0.0000 log_k_JSE76 0.000 0.000 0.000 1.271 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6838 +f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6839 f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 log_k1 0.000 0.000 0.000 0.000 0.0000 @@ -2961,8 +2992,8 @@ log_k_JCZ38 0.00 0.00 0.0000 0.0000 0.000 log_k_J9Z38 0.00 0.00 0.0000 0.0000 0.000 log_k_JSE76 0.00 0.00 0.0000 0.0000 0.000 f_cyan_ilr_1 0.00 0.00 0.0000 0.0000 0.000 -f_cyan_ilr_2 11.77 0.00 0.0000 0.0000 0.000 -f_JCZ38_qlogis 0.00 16.11 0.0000 0.0000 0.000 +f_cyan_ilr_2 11.95 0.00 0.0000 0.0000 0.000 +f_JCZ38_qlogis 0.00 16.08 0.0000 0.0000 0.000 log_k1 0.00 0.00 0.9496 0.0000 0.000 log_k2 0.00 0.00 0.0000 0.5846 0.000 g_qlogis 0.00 0.00 0.0000 0.0000 1.719 @@ -2978,73 +3009,73 @@ Likelihood computed by importance sampling 2398 2390 -1179 Optimised parameters: - est. lower upper -cyan_0 100.8076 NA NA -log_k_JCZ38 -3.4684 NA NA -log_k_J9Z38 -5.0844 NA NA -log_k_JSE76 -5.5743 NA NA -f_cyan_ilr_1 0.6669 NA NA -f_cyan_ilr_2 0.7912 NA NA -f_JCZ38_qlogis 84.1825 NA NA -log_k1 -2.1671 NA NA -log_k2 -4.5447 NA NA -g_qlogis -0.5631 NA NA -a.1 2.9627 NA NA -b.1 0.0444 NA NA -SD.log_k_JCZ38 1.4044 NA NA -SD.log_k_J9Z38 0.6410 NA NA -SD.log_k_JSE76 0.5391 NA NA -SD.f_cyan_ilr_1 0.3203 NA NA -SD.f_cyan_ilr_2 0.5038 NA NA -SD.f_JCZ38_qlogis 3.5865 NA NA -SD.log_k2 0.3119 NA NA -SD.g_qlogis 0.8276 NA NA + est. lower upper +cyan_0 100.69709 NA NA +log_k_JCZ38 -3.46669 NA NA +log_k_J9Z38 -5.05076 NA NA +log_k_JSE76 -5.55558 NA NA +f_cyan_ilr_1 0.66045 NA NA +f_cyan_ilr_2 0.84275 NA NA +f_JCZ38_qlogis 64.22404 NA NA +log_k1 -2.17715 NA NA +log_k2 -4.55002 NA NA +g_qlogis -0.55920 NA NA +a.1 2.95785 NA NA +b.1 0.04456 NA NA +SD.log_k_JCZ38 1.39881 NA NA +SD.log_k_J9Z38 0.67788 NA NA +SD.log_k_JSE76 0.52603 NA NA +SD.f_cyan_ilr_1 0.32490 NA NA +SD.f_cyan_ilr_2 0.53923 NA NA +SD.f_JCZ38_qlogis 2.75576 NA NA +SD.log_k2 0.30694 NA NA +SD.g_qlogis 0.83619 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_JCZ38 1.4044 NA NA -SD.log_k_J9Z38 0.6410 NA NA -SD.log_k_JSE76 0.5391 NA NA -SD.f_cyan_ilr_1 0.3203 NA NA -SD.f_cyan_ilr_2 0.5038 NA NA -SD.f_JCZ38_qlogis 3.5865 NA NA -SD.log_k2 0.3119 NA NA -SD.g_qlogis 0.8276 NA NA +SD.log_k_JCZ38 1.3988 NA NA +SD.log_k_J9Z38 0.6779 NA NA +SD.log_k_JSE76 0.5260 NA NA +SD.f_cyan_ilr_1 0.3249 NA NA +SD.f_cyan_ilr_2 0.5392 NA NA +SD.f_JCZ38_qlogis 2.7558 NA NA +SD.log_k2 0.3069 NA NA +SD.g_qlogis 0.8362 NA NA Variance model: - est. lower upper -a.1 2.9627 NA NA -b.1 0.0444 NA NA + est. lower upper +a.1 2.95785 NA NA +b.1 0.04456 NA NA Backtransformed parameters: est. lower upper -cyan_0 1.008e+02 NA NA -k_JCZ38 3.117e-02 NA NA -k_J9Z38 6.193e-03 NA NA -k_JSE76 3.794e-03 NA NA -f_cyan_to_JCZ38 6.149e-01 NA NA -f_cyan_to_J9Z38 2.395e-01 NA NA +cyan_0 1.007e+02 NA NA +k_JCZ38 3.122e-02 NA NA +k_J9Z38 6.404e-03 NA NA +k_JSE76 3.866e-03 NA NA +f_cyan_to_JCZ38 6.187e-01 NA NA +f_cyan_to_J9Z38 2.431e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA -k1 1.145e-01 NA NA -k2 1.062e-02 NA NA -g 3.628e-01 NA NA +k1 1.134e-01 NA NA +k2 1.057e-02 NA NA +g 3.637e-01 NA NA Resulting formation fractions: ff -cyan_JCZ38 0.6149 -cyan_J9Z38 0.2395 -cyan_sink 0.1456 +cyan_JCZ38 0.6187 +cyan_J9Z38 0.2431 +cyan_sink 0.1382 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 26.26 174.32 52.47 6.053 65.25 -JCZ38 22.24 73.88 NA NA NA -J9Z38 111.93 371.82 NA NA NA -JSE76 182.69 606.88 NA NA NA +cyan 26.35 175.12 52.72 6.114 65.6 +JCZ38 22.20 73.75 NA NA NA +J9Z38 108.23 359.53 NA NA NA +JSE76 179.30 595.62 NA NA NA </code></pre> <p></p> @@ -3052,11 +3083,11 @@ JSE76 182.69 606.88 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:43:37 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:43:36 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -3074,7 +3105,7 @@ Data: Model predictions using solution type deSolve -Fitted in 538.025 s +Fitted in 507.042 s Using 300, 100 iterations and 10 chains Variance model: Constant variance @@ -3087,7 +3118,7 @@ log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 -5.8613 0.6855 1.2366 f_JCZ38_qlogis - 13.7418 + 13.7395 Fixed degradation parameter values: None @@ -3125,7 +3156,7 @@ log_k_J9Z38 0.0000 0.00 0.00 log_k_JSE76 0.0000 0.00 0.00 f_cyan_ilr_1 0.6852 0.00 0.00 f_cyan_ilr_2 0.0000 1.28 0.00 -f_JCZ38_qlogis 0.0000 0.00 16.14 +f_JCZ38_qlogis 0.0000 0.00 16.13 Starting values for error model parameters: a.1 @@ -3139,77 +3170,77 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -cyan_free_0 102.7803 NA NA -log_k_cyan_free -2.8068 NA NA -log_k_cyan_free_bound -2.5714 NA NA -log_k_cyan_bound_free -3.4426 NA NA -log_k_JCZ38 -3.4994 NA NA -log_k_J9Z38 -5.1148 NA NA -log_k_JSE76 -5.6335 NA NA -f_cyan_ilr_1 0.6597 NA NA -f_cyan_ilr_2 0.5132 NA NA -f_JCZ38_qlogis 37.2090 NA NA -a.1 3.2367 NA NA -SD.log_k_cyan_free 0.3161 NA NA -SD.log_k_cyan_free_bound 0.8103 NA NA -SD.log_k_cyan_bound_free 0.5554 NA NA -SD.log_k_JCZ38 1.4858 NA NA -SD.log_k_J9Z38 0.5859 NA NA -SD.log_k_JSE76 0.6195 NA NA -SD.f_cyan_ilr_1 0.3118 NA NA -SD.f_cyan_ilr_2 0.3344 NA NA -SD.f_JCZ38_qlogis 0.5518 NA NA +cyan_free_0 102.8136 NA NA +log_k_cyan_free -2.7935 NA NA +log_k_cyan_free_bound -2.5440 NA NA +log_k_cyan_bound_free -3.4303 NA NA +log_k_JCZ38 -3.5010 NA NA +log_k_J9Z38 -5.1226 NA NA +log_k_JSE76 -5.6314 NA NA +f_cyan_ilr_1 0.6609 NA NA +f_cyan_ilr_2 0.5085 NA NA +f_JCZ38_qlogis 44.0153 NA NA +a.1 3.2318 NA NA +SD.log_k_cyan_free 0.3211 NA NA +SD.log_k_cyan_free_bound 0.8408 NA NA +SD.log_k_cyan_bound_free 0.5724 NA NA +SD.log_k_JCZ38 1.4925 NA NA +SD.log_k_J9Z38 0.5816 NA NA +SD.log_k_JSE76 0.6037 NA NA +SD.f_cyan_ilr_1 0.3115 NA NA +SD.f_cyan_ilr_2 0.3436 NA NA +SD.f_JCZ38_qlogis 4.8937 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_cyan_free 0.3161 NA NA -SD.log_k_cyan_free_bound 0.8103 NA NA -SD.log_k_cyan_bound_free 0.5554 NA NA -SD.log_k_JCZ38 1.4858 NA NA -SD.log_k_J9Z38 0.5859 NA NA -SD.log_k_JSE76 0.6195 NA NA -SD.f_cyan_ilr_1 0.3118 NA NA -SD.f_cyan_ilr_2 0.3344 NA NA -SD.f_JCZ38_qlogis 0.5518 NA NA +SD.log_k_cyan_free 0.3211 NA NA +SD.log_k_cyan_free_bound 0.8408 NA NA +SD.log_k_cyan_bound_free 0.5724 NA NA +SD.log_k_JCZ38 1.4925 NA NA +SD.log_k_J9Z38 0.5816 NA NA +SD.log_k_JSE76 0.6037 NA NA +SD.f_cyan_ilr_1 0.3115 NA NA +SD.f_cyan_ilr_2 0.3436 NA NA +SD.f_JCZ38_qlogis 4.8937 NA NA Variance model: est. lower upper -a.1 3.237 NA NA +a.1 3.232 NA NA Backtransformed parameters: est. lower upper cyan_free_0 1.028e+02 NA NA -k_cyan_free 6.040e-02 NA NA -k_cyan_free_bound 7.643e-02 NA NA -k_cyan_bound_free 3.198e-02 NA NA -k_JCZ38 3.022e-02 NA NA -k_J9Z38 6.007e-03 NA NA -k_JSE76 3.576e-03 NA NA -f_cyan_free_to_JCZ38 5.787e-01 NA NA -f_cyan_free_to_J9Z38 2.277e-01 NA NA +k_cyan_free 6.120e-02 NA NA +k_cyan_free_bound 7.855e-02 NA NA +k_cyan_bound_free 3.238e-02 NA NA +k_JCZ38 3.017e-02 NA NA +k_J9Z38 5.961e-03 NA NA +k_JSE76 3.584e-03 NA NA +f_cyan_free_to_JCZ38 5.784e-01 NA NA +f_cyan_free_to_J9Z38 2.271e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g -0.15646 0.01235 0.33341 +0.15973 0.01241 0.33124 Resulting formation fractions: ff -cyan_free_JCZ38 0.5787 -cyan_free_J9Z38 0.2277 -cyan_free_sink 0.1936 +cyan_free_JCZ38 0.5784 +cyan_free_J9Z38 0.2271 +cyan_free_sink 0.1945 cyan_free 1.0000 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 Estimated disappearance times: - DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 24.48 153.7 46.26 4.43 56.15 -JCZ38 22.94 76.2 NA NA NA -J9Z38 115.39 383.3 NA NA NA -JSE76 193.84 643.9 NA NA NA + DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 +cyan 24.51 153.18 46.11 4.34 55.87 +JCZ38 22.98 76.33 NA NA NA +J9Z38 116.28 386.29 NA NA NA +JSE76 193.42 642.53 NA NA NA </code></pre> <p></p> @@ -3217,11 +3248,11 @@ JSE76 193.84 643.9 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:45:51 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:46:14 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -3239,7 +3270,7 @@ Data: Model predictions using solution type deSolve -Fitted in 672.309 s +Fitted in 664.11 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function @@ -3250,9 +3281,9 @@ Starting values for degradation parameters: log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 -3.4376 -3.3626 -4.9792 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 - -5.8727 0.6814 6.8139 + -5.8727 0.6814 6.7399 f_JCZ38_qlogis - 13.7419 + 13.7395 Fixed degradation parameter values: None @@ -3289,8 +3320,8 @@ log_k_JCZ38 0.0000 0.00 0.00 log_k_J9Z38 0.0000 0.00 0.00 log_k_JSE76 0.0000 0.00 0.00 f_cyan_ilr_1 0.6838 0.00 0.00 -f_cyan_ilr_2 0.0000 11.84 0.00 -f_JCZ38_qlogis 0.0000 0.00 16.14 +f_cyan_ilr_2 0.0000 11.69 0.00 +f_JCZ38_qlogis 0.0000 0.00 16.13 Starting values for error model parameters: a.1 b.1 @@ -3304,77 +3335,77 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -cyan_free_0 100.69983 NA NA -log_k_cyan_free -3.11584 NA NA -log_k_cyan_free_bound -3.15216 NA NA -log_k_cyan_bound_free -3.65986 NA NA -log_k_JCZ38 -3.47811 NA NA -log_k_J9Z38 -5.08835 NA NA -log_k_JSE76 -5.55514 NA NA -f_cyan_ilr_1 0.66764 NA NA -f_cyan_ilr_2 0.78329 NA NA -f_JCZ38_qlogis 25.35245 NA NA -a.1 2.99088 NA NA -b.1 0.04346 NA NA -SD.log_k_cyan_free 0.48797 NA NA -SD.log_k_cyan_bound_free 0.27243 NA NA -SD.log_k_JCZ38 1.42450 NA NA -SD.log_k_J9Z38 0.63496 NA NA -SD.log_k_JSE76 0.55951 NA NA -SD.f_cyan_ilr_1 0.32687 NA NA -SD.f_cyan_ilr_2 0.48056 NA NA -SD.f_JCZ38_qlogis 0.43818 NA NA +cyan_free_0 100.56004 NA NA +log_k_cyan_free -3.12657 NA NA +log_k_cyan_free_bound -3.16825 NA NA +log_k_cyan_bound_free -3.66003 NA NA +log_k_JCZ38 -3.47278 NA NA +log_k_J9Z38 -5.06823 NA NA +log_k_JSE76 -5.54327 NA NA +f_cyan_ilr_1 0.66631 NA NA +f_cyan_ilr_2 0.82898 NA NA +f_JCZ38_qlogis 38.31115 NA NA +a.1 2.98352 NA NA +b.1 0.04388 NA NA +SD.log_k_cyan_free 0.49145 NA NA +SD.log_k_cyan_bound_free 0.27347 NA NA +SD.log_k_JCZ38 1.41193 NA NA +SD.log_k_J9Z38 0.66073 NA NA +SD.log_k_JSE76 0.55885 NA NA +SD.f_cyan_ilr_1 0.33020 NA NA +SD.f_cyan_ilr_2 0.51367 NA NA +SD.f_JCZ38_qlogis 5.52122 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_cyan_free 0.4880 NA NA -SD.log_k_cyan_bound_free 0.2724 NA NA -SD.log_k_JCZ38 1.4245 NA NA -SD.log_k_J9Z38 0.6350 NA NA -SD.log_k_JSE76 0.5595 NA NA -SD.f_cyan_ilr_1 0.3269 NA NA -SD.f_cyan_ilr_2 0.4806 NA NA -SD.f_JCZ38_qlogis 0.4382 NA NA +SD.log_k_cyan_free 0.4914 NA NA +SD.log_k_cyan_bound_free 0.2735 NA NA +SD.log_k_JCZ38 1.4119 NA NA +SD.log_k_J9Z38 0.6607 NA NA +SD.log_k_JSE76 0.5589 NA NA +SD.f_cyan_ilr_1 0.3302 NA NA +SD.f_cyan_ilr_2 0.5137 NA NA +SD.f_JCZ38_qlogis 5.5212 NA NA Variance model: est. lower upper -a.1 2.99088 NA NA -b.1 0.04346 NA NA +a.1 2.98352 NA NA +b.1 0.04388 NA NA Backtransformed parameters: est. lower upper -cyan_free_0 1.007e+02 NA NA -k_cyan_free 4.434e-02 NA NA -k_cyan_free_bound 4.276e-02 NA NA -k_cyan_bound_free 2.574e-02 NA NA -k_JCZ38 3.087e-02 NA NA -k_J9Z38 6.168e-03 NA NA -k_JSE76 3.868e-03 NA NA -f_cyan_free_to_JCZ38 6.143e-01 NA NA -f_cyan_free_to_J9Z38 2.389e-01 NA NA +cyan_free_0 1.006e+02 NA NA +k_cyan_free 4.387e-02 NA NA +k_cyan_free_bound 4.208e-02 NA NA +k_cyan_bound_free 2.573e-02 NA NA +k_JCZ38 3.103e-02 NA NA +k_J9Z38 6.294e-03 NA NA +k_JSE76 3.914e-03 NA NA +f_cyan_free_to_JCZ38 6.188e-01 NA NA +f_cyan_free_to_J9Z38 2.412e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g -0.10161 0.01123 0.36636 +0.10044 0.01124 0.36580 Resulting formation fractions: - ff -cyan_free_JCZ38 6.143e-01 -cyan_free_J9Z38 2.389e-01 -cyan_free_sink 1.468e-01 -cyan_free 1.000e+00 -JCZ38_JSE76 1.000e+00 -JCZ38_sink 9.763e-12 + ff +cyan_free_JCZ38 0.6188 +cyan_free_J9Z38 0.2412 +cyan_free_sink 0.1400 +cyan_free 1.0000 +JCZ38_JSE76 1.0000 +JCZ38_sink 0.0000 Estimated disappearance times: DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 25.91 164.4 49.49 6.822 61.72 -JCZ38 22.46 74.6 NA NA NA -J9Z38 112.37 373.3 NA NA NA -JSE76 179.22 595.4 NA NA NA +cyan 26.05 164.4 49.48 6.901 61.67 +JCZ38 22.34 74.2 NA NA NA +J9Z38 110.14 365.9 NA NA NA +JSE76 177.11 588.3 NA NA NA </code></pre> <p></p> @@ -3382,11 +3413,11 @@ JSE76 179.22 595.4 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:43:26 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:43:42 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - ifelse(time <= tb, k1, k2) * cyan @@ -3401,27 +3432,27 @@ Data: Model predictions using solution type deSolve -Fitted in 526.974 s +Fitted in 512.818 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 102.8738 -3.4490 -4.9348 -5.5989 0.6469 + 102.8845 -3.4495 -4.9355 -5.6040 0.6468 f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 log_tb - 1.2854 9.7193 -2.9084 -4.1810 1.7813 + 1.2396 9.7220 -2.9079 -4.1810 1.7813 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.409 0.00 0.00 0.000 0.0000 +cyan_0 5.406 0.00 0.00 0.000 0.0000 log_k_JCZ38 0.000 2.33 0.00 0.000 0.0000 log_k_J9Z38 0.000 0.00 1.59 0.000 0.0000 -log_k_JSE76 0.000 0.00 0.00 1.006 0.0000 -f_cyan_ilr_1 0.000 0.00 0.00 0.000 0.6371 +log_k_JSE76 0.000 0.00 0.00 1.013 0.0000 +f_cyan_ilr_1 0.000 0.00 0.00 0.000 0.6367 f_cyan_ilr_2 0.000 0.00 0.00 0.000 0.0000 f_JCZ38_qlogis 0.000 0.00 0.00 0.000 0.0000 log_k1 0.000 0.00 0.00 0.000 0.0000 @@ -3433,11 +3464,11 @@ log_k_JCZ38 0.000 0.00 0.0000 0.0000 0.0000 log_k_J9Z38 0.000 0.00 0.0000 0.0000 0.0000 log_k_JSE76 0.000 0.00 0.0000 0.0000 0.0000 f_cyan_ilr_1 0.000 0.00 0.0000 0.0000 0.0000 -f_cyan_ilr_2 2.167 0.00 0.0000 0.0000 0.0000 -f_JCZ38_qlogis 0.000 10.22 0.0000 0.0000 0.0000 -log_k1 0.000 0.00 0.7003 0.0000 0.0000 +f_cyan_ilr_2 2.038 0.00 0.0000 0.0000 0.0000 +f_JCZ38_qlogis 0.000 10.33 0.0000 0.0000 0.0000 +log_k1 0.000 0.00 0.7006 0.0000 0.0000 log_k2 0.000 0.00 0.0000 0.8928 0.0000 -log_tb 0.000 0.00 0.0000 0.0000 0.6774 +log_tb 0.000 0.00 0.0000 0.0000 0.6773 Starting values for error model parameters: a.1 @@ -3447,220 +3478,76 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2427 2420 -1194 + 2427 2419 -1194 Optimised parameters: - est. lower upper -cyan_0 101.84849 NA NA -log_k_JCZ38 -3.47365 NA NA -log_k_J9Z38 -5.10562 NA NA -log_k_JSE76 -5.60318 NA NA -f_cyan_ilr_1 0.66127 NA NA -f_cyan_ilr_2 0.60283 NA NA -f_JCZ38_qlogis 45.06408 NA NA -log_k1 -3.10124 NA NA -log_k2 -4.39028 NA NA -log_tb 2.32256 NA NA -a.1 3.32683 NA NA -SD.log_k_JCZ38 1.41427 NA NA -SD.log_k_J9Z38 0.54767 NA NA -SD.log_k_JSE76 0.62147 NA NA -SD.f_cyan_ilr_1 0.30189 NA NA -SD.f_cyan_ilr_2 0.34960 NA NA -SD.f_JCZ38_qlogis 0.04644 NA NA -SD.log_k1 0.39534 NA NA -SD.log_k2 0.43468 NA NA -SD.log_tb 0.60781 NA NA - -Correlation is not available - -Random effects: - est. lower upper -SD.log_k_JCZ38 1.41427 NA NA -SD.log_k_J9Z38 0.54767 NA NA -SD.log_k_JSE76 0.62147 NA NA -SD.f_cyan_ilr_1 0.30189 NA NA -SD.f_cyan_ilr_2 0.34960 NA NA -SD.f_JCZ38_qlogis 0.04644 NA NA -SD.log_k1 0.39534 NA NA -SD.log_k2 0.43468 NA NA -SD.log_tb 0.60781 NA NA - -Variance model: - est. lower upper -a.1 3.327 NA NA - -Backtransformed parameters: - est. lower upper -cyan_0 1.018e+02 NA NA -k_JCZ38 3.100e-02 NA NA -k_J9Z38 6.063e-03 NA NA -k_JSE76 3.686e-03 NA NA -f_cyan_to_JCZ38 5.910e-01 NA NA -f_cyan_to_J9Z38 2.320e-01 NA NA -f_JCZ38_to_JSE76 1.000e+00 NA NA -k1 4.499e-02 NA NA -k2 1.240e-02 NA NA -tb 1.020e+01 NA NA - -Resulting formation fractions: - ff -cyan_JCZ38 0.591 -cyan_J9Z38 0.232 -cyan_sink 0.177 -JCZ38_JSE76 1.000 -JCZ38_sink 0.000 - -Estimated disappearance times: - DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 29.09 158.91 47.84 15.41 55.91 -JCZ38 22.36 74.27 NA NA NA -J9Z38 114.33 379.80 NA NA NA -JSE76 188.04 624.66 NA NA NA - -</code></pre> -<p></p> -<caption> -Hierarchical HS path 1 fit with two-component error -</caption> -<pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:43:29 2023 -Date of summary: Fri May 19 18:14:01 2023 - -Equations: -d_cyan/dt = - ifelse(time <= tb, k1, k2) * cyan -d_JCZ38/dt = + f_cyan_to_JCZ38 * ifelse(time <= tb, k1, k2) * cyan - - k_JCZ38 * JCZ38 -d_J9Z38/dt = + f_cyan_to_J9Z38 * ifelse(time <= tb, k1, k2) * cyan - - k_J9Z38 * J9Z38 -d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76 - -Data: -433 observations of 4 variable(s) grouped in 5 datasets - -Model predictions using solution type deSolve - -Fitted in 529.515 s -Using 300, 100 iterations and 10 chains - -Variance model: Two-component variance function - -Starting values for degradation parameters: - cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.168 -3.358 -4.941 -5.794 0.676 - f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 log_tb - 5.740 13.863 -3.147 -4.262 2.173 - -Fixed degradation parameter values: -None - -Starting values for random effects (square root of initial entries in omega): - cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.79 0.000 0.000 0.000 0.0000 -log_k_JCZ38 0.00 2.271 0.000 0.000 0.0000 -log_k_J9Z38 0.00 0.000 1.614 0.000 0.0000 -log_k_JSE76 0.00 0.000 0.000 1.264 0.0000 -f_cyan_ilr_1 0.00 0.000 0.000 0.000 0.6761 -f_cyan_ilr_2 0.00 0.000 0.000 0.000 0.0000 -f_JCZ38_qlogis 0.00 0.000 0.000 0.000 0.0000 -log_k1 0.00 0.000 0.000 0.000 0.0000 -log_k2 0.00 0.000 0.000 0.000 0.0000 -log_tb 0.00 0.000 0.000 0.000 0.0000 - f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 log_tb -cyan_0 0.000 0.00 0.0000 0.0000 0.000 -log_k_JCZ38 0.000 0.00 0.0000 0.0000 0.000 -log_k_J9Z38 0.000 0.00 0.0000 0.0000 0.000 -log_k_JSE76 0.000 0.00 0.0000 0.0000 0.000 -f_cyan_ilr_1 0.000 0.00 0.0000 0.0000 0.000 -f_cyan_ilr_2 9.572 0.00 0.0000 0.0000 0.000 -f_JCZ38_qlogis 0.000 19.19 0.0000 0.0000 0.000 -log_k1 0.000 0.00 0.8705 0.0000 0.000 -log_k2 0.000 0.00 0.0000 0.9288 0.000 -log_tb 0.000 0.00 0.0000 0.0000 1.065 - -Starting values for error model parameters: -a.1 b.1 - 1 1 - -Results: - -Likelihood computed by importance sampling - AIC BIC logLik - 2422 2414 -1190 - -Optimised parameters: - est. lower upper -cyan_0 100.9521 NA NA -log_k_JCZ38 -3.4629 NA NA -log_k_J9Z38 -5.0346 NA NA -log_k_JSE76 -5.5722 NA NA -f_cyan_ilr_1 0.6560 NA NA -f_cyan_ilr_2 0.7983 NA NA -f_JCZ38_qlogis 42.7949 NA NA -log_k1 -3.1721 NA NA -log_k2 -4.4039 NA NA -log_tb 2.3994 NA NA -a.1 3.0586 NA NA -b.1 0.0380 NA NA -SD.log_k_JCZ38 1.3754 NA NA -SD.log_k_J9Z38 0.6703 NA NA -SD.log_k_JSE76 0.5876 NA NA -SD.f_cyan_ilr_1 0.3272 NA NA -SD.f_cyan_ilr_2 0.5300 NA NA -SD.f_JCZ38_qlogis 6.4465 NA NA -SD.log_k1 0.4135 NA NA -SD.log_k2 0.4182 NA NA -SD.log_tb 0.6035 NA NA + est. lower upper +cyan_0 101.9660 1.005e+02 1.035e+02 +log_k_JCZ38 -3.4698 -4.716e+00 -2.224e+00 +log_k_J9Z38 -5.0947 -5.740e+00 -4.450e+00 +log_k_JSE76 -5.5977 -6.321e+00 -4.875e+00 +f_cyan_ilr_1 0.6595 3.734e-01 9.456e-01 +f_cyan_ilr_2 0.5905 1.664e-01 1.015e+00 +f_JCZ38_qlogis 25.8627 -4.224e+05 4.225e+05 +log_k1 -3.0884 -3.453e+00 -2.723e+00 +log_k2 -4.3877 -4.778e+00 -3.998e+00 +log_tb 2.3057 1.715e+00 2.896e+00 +a.1 3.3228 NA NA +SD.log_k_JCZ38 1.4071 NA NA +SD.log_k_J9Z38 0.5774 NA NA +SD.log_k_JSE76 0.6214 NA NA +SD.f_cyan_ilr_1 0.3058 NA NA +SD.f_cyan_ilr_2 0.3470 NA NA +SD.f_JCZ38_qlogis 0.0644 NA NA +SD.log_k1 0.3994 NA NA +SD.log_k2 0.4373 NA NA +SD.log_tb 0.6419 NA NA Correlation is not available Random effects: est. lower upper -SD.log_k_JCZ38 1.3754 NA NA -SD.log_k_J9Z38 0.6703 NA NA -SD.log_k_JSE76 0.5876 NA NA -SD.f_cyan_ilr_1 0.3272 NA NA -SD.f_cyan_ilr_2 0.5300 NA NA -SD.f_JCZ38_qlogis 6.4465 NA NA -SD.log_k1 0.4135 NA NA -SD.log_k2 0.4182 NA NA -SD.log_tb 0.6035 NA NA +SD.log_k_JCZ38 1.4071 NA NA +SD.log_k_J9Z38 0.5774 NA NA +SD.log_k_JSE76 0.6214 NA NA +SD.f_cyan_ilr_1 0.3058 NA NA +SD.f_cyan_ilr_2 0.3470 NA NA +SD.f_JCZ38_qlogis 0.0644 NA NA +SD.log_k1 0.3994 NA NA +SD.log_k2 0.4373 NA NA +SD.log_tb 0.6419 NA NA Variance model: est. lower upper -a.1 3.059 NA NA -b.1 0.038 NA NA +a.1 3.323 NA NA Backtransformed parameters: - est. lower upper -cyan_0 1.010e+02 NA NA -k_JCZ38 3.134e-02 NA NA -k_J9Z38 6.509e-03 NA NA -k_JSE76 3.802e-03 NA NA -f_cyan_to_JCZ38 6.127e-01 NA NA -f_cyan_to_J9Z38 2.423e-01 NA NA -f_JCZ38_to_JSE76 1.000e+00 NA NA -k1 4.191e-02 NA NA -k2 1.223e-02 NA NA -tb 1.102e+01 NA NA + est. lower upper +cyan_0 1.020e+02 1.005e+02 1.035e+02 +k_JCZ38 3.112e-02 8.951e-03 1.082e-01 +k_J9Z38 6.129e-03 3.216e-03 1.168e-02 +k_JSE76 3.706e-03 1.798e-03 7.639e-03 +f_cyan_to_JCZ38 5.890e-01 NA NA +f_cyan_to_J9Z38 2.318e-01 NA NA +f_JCZ38_to_JSE76 1.000e+00 0.000e+00 1.000e+00 +k1 4.558e-02 3.164e-02 6.565e-02 +k2 1.243e-02 8.417e-03 1.835e-02 +tb 1.003e+01 5.557e+00 1.811e+01 Resulting formation fractions: - ff -cyan_JCZ38 0.6127 -cyan_J9Z38 0.2423 -cyan_sink 0.1449 -JCZ38_JSE76 1.0000 -JCZ38_sink 0.0000 + ff +cyan_JCZ38 5.890e-01 +cyan_J9Z38 2.318e-01 +cyan_sink 1.793e-01 +JCZ38_JSE76 1.000e+00 +JCZ38_sink 5.861e-12 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 29.94 161.54 48.63 16.54 56.68 -JCZ38 22.12 73.47 NA NA NA -J9Z38 106.50 353.77 NA NA NA -JSE76 182.30 605.60 NA NA NA +cyan 29.02 158.51 47.72 15.21 55.77 +JCZ38 22.27 73.98 NA NA NA +J9Z38 113.09 375.69 NA NA NA +JSE76 187.01 621.23 NA NA NA </code></pre> <p></p> @@ -3669,14 +3556,14 @@ JSE76 182.30 605.60 NA NA NA <h4 id="pathway-2">Pathway 2<a class="anchor" aria-label="anchor" href="#pathway-2"></a> </h4> <caption> -Hierarchical FOMC path 2 fit with constant variance +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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:54:58 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:54:36 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -3691,88 +3578,89 @@ Data: Model predictions using solution type deSolve -Fitted in 519.639 s +Fitted in 491.928 s Using 300, 100 iterations and 10 chains -Variance model: Constant variance +Variance model: Two-component variance function Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.8173 -1.8998 -5.1449 -2.5415 0.6705 + 102.4477 -1.8631 -5.1087 -2.5114 0.6826 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta - 4.4669 16.1281 13.3327 -0.2314 2.8738 + 4.7944 15.9616 13.1566 -0.1564 2.9781 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.742 0.000 0.000 0.00 0.0000 -log_k_JCZ38 0.000 1.402 0.000 0.00 0.0000 -log_k_J9Z38 0.000 0.000 1.718 0.00 0.0000 -log_k_JSE76 0.000 0.000 0.000 3.57 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.00 0.5926 -f_cyan_ilr_2 0.000 0.000 0.000 0.00 0.0000 -f_JCZ38_qlogis 0.000 0.000 0.000 0.00 0.0000 -f_JSE76_qlogis 0.000 0.000 0.000 0.00 0.0000 -log_alpha 0.000 0.000 0.000 0.00 0.0000 -log_beta 0.000 0.000 0.000 0.00 0.0000 +cyan_0 7.701 0.000 0.000 0.000 0.0000 +log_k_JCZ38 0.000 1.448 0.000 0.000 0.0000 +log_k_J9Z38 0.000 0.000 1.724 0.000 0.0000 +log_k_JSE76 0.000 0.000 0.000 3.659 0.0000 +f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6356 +f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 +f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 +f_JSE76_qlogis 0.000 0.000 0.000 0.000 0.0000 +log_alpha 0.000 0.000 0.000 0.000 0.0000 +log_beta 0.000 0.000 0.000 0.000 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta cyan_0 0.00 0.00 0.00 0.0000 0.0000 log_k_JCZ38 0.00 0.00 0.00 0.0000 0.0000 log_k_J9Z38 0.00 0.00 0.00 0.0000 0.0000 log_k_JSE76 0.00 0.00 0.00 0.0000 0.0000 f_cyan_ilr_1 0.00 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 10.56 0.00 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.00 12.04 0.00 0.0000 0.0000 -f_JSE76_qlogis 0.00 0.00 15.26 0.0000 0.0000 -log_alpha 0.00 0.00 0.00 0.4708 0.0000 -log_beta 0.00 0.00 0.00 0.0000 0.4432 +f_cyan_ilr_2 10.32 0.00 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 12.23 0.00 0.0000 0.0000 +f_JSE76_qlogis 0.00 0.00 14.99 0.0000 0.0000 +log_alpha 0.00 0.00 0.00 0.3924 0.0000 +log_beta 0.00 0.00 0.00 0.0000 0.5639 Starting values for error model parameters: -a.1 - 1 +a.1 b.1 + 1 1 Results: Likelihood computed by importance sampling AIC BIC logLik - 2308 2301 -1134 + 2249 2241 -1104 Optimised parameters: - est. lower upper -cyan_0 101.9586 99.22024 104.69700 -log_k_JCZ38 -2.4861 -3.17661 -1.79560 -log_k_J9Z38 -5.3926 -6.08842 -4.69684 -log_k_JSE76 -3.1193 -4.12904 -2.10962 -f_cyan_ilr_1 0.7368 0.42085 1.05276 -f_cyan_ilr_2 0.6196 0.06052 1.17861 -f_JCZ38_qlogis 4.8970 -4.68003 14.47398 -f_JSE76_qlogis 4.4066 -1.02087 9.83398 -log_alpha -0.3021 -0.68264 0.07838 -log_beta 2.7438 2.57970 2.90786 -a.1 2.9008 2.69920 3.10245 -SD.cyan_0 2.7081 0.64216 4.77401 -SD.log_k_JCZ38 0.7043 0.19951 1.20907 -SD.log_k_J9Z38 0.6248 0.05790 1.19180 -SD.log_k_JSE76 1.0750 0.33157 1.81839 -SD.f_cyan_ilr_1 0.3429 0.11688 0.56892 -SD.f_cyan_ilr_2 0.4774 0.09381 0.86097 -SD.f_JCZ38_qlogis 1.5565 -7.83970 10.95279 -SD.f_JSE76_qlogis 1.6871 -1.25577 4.63000 -SD.log_alpha 0.4216 0.15913 0.68405 + 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 -log_k_JCZ38 -0.0167 -log_k_J9Z38 -0.0307 0.0057 -log_k_JSE76 -0.0032 0.1358 0.0009 -f_cyan_ilr_1 -0.0087 0.0206 -0.1158 -0.0009 -f_cyan_ilr_2 -0.1598 0.0690 0.1770 0.0002 -0.0007 -f_JCZ38_qlogis 0.0966 -0.1132 -0.0440 0.0182 -0.1385 -0.4583 -f_JSE76_qlogis -0.0647 0.1157 0.0333 -0.0026 0.1110 0.3620 -0.8586 -log_alpha -0.0389 0.0113 0.0209 0.0021 0.0041 0.0451 -0.0605 0.0412 -log_beta -0.2508 0.0533 0.0977 0.0098 0.0220 0.2741 -0.2934 0.1999 +log_k_JCZ38 -0.0235 +log_k_J9Z38 -0.0442 0.0047 +log_k_JSE76 -0.0023 0.0966 0.0006 +f_cyan_ilr_1 -0.0032 0.0070 -0.0536 -0.0001 +f_cyan_ilr_2 -0.5189 0.0452 0.1152 0.0013 -0.0304 +f_JCZ38_qlogis 0.1088 -0.0848 -0.0240 0.0040 -0.0384 -0.2303 +f_JSE76_qlogis -0.0545 0.1315 0.0195 0.0020 0.0252 0.1737 -0.5939 +log_alpha -0.0445 0.0056 0.0261 0.0019 -0.0055 0.0586 -0.0239 -0.0284 +log_beta -0.2388 0.0163 0.0566 0.0040 -0.0078 0.2183 -0.0714 -0.0332 log_lph log_k_JCZ38 log_k_J9Z38 @@ -3782,199 +3670,54 @@ f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha -log_beta 0.2281 - -Random effects: - est. lower upper -SD.cyan_0 2.7081 0.64216 4.7740 -SD.log_k_JCZ38 0.7043 0.19951 1.2091 -SD.log_k_J9Z38 0.6248 0.05790 1.1918 -SD.log_k_JSE76 1.0750 0.33157 1.8184 -SD.f_cyan_ilr_1 0.3429 0.11688 0.5689 -SD.f_cyan_ilr_2 0.4774 0.09381 0.8610 -SD.f_JCZ38_qlogis 1.5565 -7.83970 10.9528 -SD.f_JSE76_qlogis 1.6871 -1.25577 4.6300 -SD.log_alpha 0.4216 0.15913 0.6840 - -Variance model: - est. lower upper -a.1 2.901 2.699 3.102 - -Backtransformed parameters: - est. lower upper -cyan_0 101.95862 99.220240 1.047e+02 -k_JCZ38 0.08323 0.041727 1.660e-01 -k_J9Z38 0.00455 0.002269 9.124e-03 -k_JSE76 0.04419 0.016098 1.213e-01 -f_cyan_to_JCZ38 0.61318 NA NA -f_cyan_to_J9Z38 0.21630 NA NA -f_JCZ38_to_JSE76 0.99259 0.009193 1.000e+00 -f_JSE76_to_JCZ38 0.98795 0.264857 9.999e-01 -alpha 0.73924 0.505281 1.082e+00 -beta 15.54568 13.193194 1.832e+01 - -Resulting formation fractions: - ff -cyan_JCZ38 0.613182 -cyan_J9Z38 0.216298 -cyan_sink 0.170519 -JCZ38_JSE76 0.992586 -JCZ38_sink 0.007414 -JSE76_JCZ38 0.987950 -JSE76_sink 0.012050 - -Estimated disappearance times: - DT50 DT90 DT50back -cyan 24.157 334.68 100.7 -JCZ38 8.328 27.66 NA -J9Z38 152.341 506.06 NA -JSE76 15.687 52.11 NA - -</code></pre> -<p></p> -<caption> -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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:54:41 2023 -Date of summary: Fri May 19 18:14:01 2023 - -Equations: -d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan -d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) * - cyan - k_JCZ38 * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76 -d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) * - cyan - k_J9Z38 * J9Z38 -d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76 - -Data: -433 observations of 4 variable(s) grouped in 5 datasets - -Model predictions using solution type deSolve - -Fitted in 503.222 s -Using 300, 100 iterations and 10 chains - -Variance model: Two-component variance function - -Starting values for degradation parameters: - cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.9028 -1.9055 -5.0249 -2.5646 0.6807 - f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta - 4.8883 16.0676 9.3923 -0.1346 3.0364 - -Fixed degradation parameter values: -None - -Starting values for random effects (square root of initial entries in omega): - cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 6.321 0.000 0.000 0.000 0.0000 -log_k_JCZ38 0.000 1.392 0.000 0.000 0.0000 -log_k_J9Z38 0.000 0.000 1.561 0.000 0.0000 -log_k_JSE76 0.000 0.000 0.000 3.614 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6339 -f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 -f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 -f_JSE76_qlogis 0.000 0.000 0.000 0.000 0.0000 -log_alpha 0.000 0.000 0.000 0.000 0.0000 -log_beta 0.000 0.000 0.000 0.000 0.0000 - f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta -cyan_0 0.00 0.00 0.00 0.0000 0.0000 -log_k_JCZ38 0.00 0.00 0.00 0.0000 0.0000 -log_k_J9Z38 0.00 0.00 0.00 0.0000 0.0000 -log_k_JSE76 0.00 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_1 0.00 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 10.41 0.00 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.00 12.24 0.00 0.0000 0.0000 -f_JSE76_qlogis 0.00 0.00 15.13 0.0000 0.0000 -log_alpha 0.00 0.00 0.00 0.3701 0.0000 -log_beta 0.00 0.00 0.00 0.0000 0.5662 - -Starting values for error model parameters: -a.1 b.1 - 1 1 - -Results: - -Likelihood computed by importance sampling - AIC BIC logLik - 2248 2240 -1103 - -Optimised parameters: - est. lower upper -cyan_0 101.55545 9.920e+01 1.039e+02 -log_k_JCZ38 -2.37354 -2.928e+00 -1.819e+00 -log_k_J9Z38 -5.14736 -5.960e+00 -4.335e+00 -log_k_JSE76 -3.07802 -4.243e+00 -1.913e+00 -f_cyan_ilr_1 0.71263 3.655e-01 1.060e+00 -f_cyan_ilr_2 0.95202 2.701e-01 1.634e+00 -f_JCZ38_qlogis 3.58473 1.251e+00 5.919e+00 -f_JSE76_qlogis 19.03623 -1.037e+07 1.037e+07 -log_alpha -0.15297 -4.490e-01 1.431e-01 -log_beta 2.99230 2.706e+00 3.278e+00 -a.1 2.04816 NA NA -b.1 0.06886 NA NA -SD.log_k_JCZ38 0.56174 NA NA -SD.log_k_J9Z38 0.86509 NA NA -SD.log_k_JSE76 1.28450 NA NA -SD.f_cyan_ilr_1 0.38705 NA NA -SD.f_cyan_ilr_2 0.54153 NA NA -SD.f_JCZ38_qlogis 1.65311 NA NA -SD.f_JSE76_qlogis 7.51468 NA NA -SD.log_alpha 0.31586 NA NA -SD.log_beta 0.24696 NA NA - -Correlation is not available +log_beta 0.2135 Random effects: - est. lower upper -SD.log_k_JCZ38 0.5617 NA NA -SD.log_k_J9Z38 0.8651 NA NA -SD.log_k_JSE76 1.2845 NA NA -SD.f_cyan_ilr_1 0.3870 NA NA -SD.f_cyan_ilr_2 0.5415 NA NA -SD.f_JCZ38_qlogis 1.6531 NA NA -SD.f_JSE76_qlogis 7.5147 NA NA -SD.log_alpha 0.3159 NA NA -SD.log_beta 0.2470 NA NA + est. lower upper +SD.log_k_JCZ38 0.5082 1.390e-01 0.8774 +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 1.711e-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 2.04816 NA NA -b.1 0.06886 NA NA + est. lower upper +a.1 2.04034 1.84252 2.238 +b.1 0.06924 0.05749 0.081 Backtransformed parameters: - est. lower upper -cyan_0 1.016e+02 99.20301 103.9079 -k_JCZ38 9.315e-02 0.05349 0.1622 -k_J9Z38 5.815e-03 0.00258 0.0131 -k_JSE76 4.605e-02 0.01436 0.1477 -f_cyan_to_JCZ38 6.438e-01 NA NA -f_cyan_to_J9Z38 2.350e-01 NA NA -f_JCZ38_to_JSE76 9.730e-01 0.77745 0.9973 -f_JSE76_to_JCZ38 1.000e+00 0.00000 1.0000 -alpha 8.582e-01 0.63824 1.1538 -beta 1.993e+01 14.97621 26.5262 + est. lower upper +cyan_0 1.016e+02 9.920e+01 103.9059 +k_JCZ38 9.798e-02 5.890e-02 0.1630 +k_J9Z38 5.912e-03 2.627e-03 0.0133 +k_JSE76 4.892e-02 1.410e-02 0.1697 +f_cyan_to_JCZ38 6.432e-01 NA NA +f_cyan_to_J9Z38 2.362e-01 NA NA +f_JCZ38_to_JSE76 9.794e-01 7.160e-01 0.9989 +f_JSE76_to_JCZ38 9.995e-01 2.268e-49 1.0000 +alpha 8.581e-01 6.371e-01 1.1556 +beta 1.992e+01 1.505e+01 26.3646 Resulting formation fractions: ff -cyan_JCZ38 6.438e-01 -cyan_J9Z38 2.350e-01 -cyan_sink 1.212e-01 -JCZ38_JSE76 9.730e-01 -JCZ38_sink 2.700e-02 -JSE76_JCZ38 1.000e+00 -JSE76_sink 5.403e-09 +cyan_JCZ38 0.6432301 +cyan_J9Z38 0.2361657 +cyan_sink 0.1206042 +JCZ38_JSE76 0.9793879 +JCZ38_sink 0.0206121 +JSE76_JCZ38 0.9994559 +JSE76_sink 0.0005441 Estimated disappearance times: DT50 DT90 DT50back -cyan 24.771 271.70 81.79 -JCZ38 7.441 24.72 NA -J9Z38 119.205 395.99 NA -JSE76 15.052 50.00 NA +cyan 24.759 271.61 81.76 +JCZ38 7.075 23.50 NA +J9Z38 117.249 389.49 NA +JSE76 14.169 47.07 NA </code></pre> <p></p> @@ -3982,11 +3725,11 @@ JSE76 15.052 50.00 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:55:53 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:55:32 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -4006,25 +3749,25 @@ Data: Model predictions using solution type deSolve -Fitted in 574.8 s +Fitted in 548.554 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 102.4358 -2.3107 -5.3123 -3.7120 0.6753 + 102.4380 -2.3107 -5.3123 -3.7120 0.6757 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 - 1.1462 12.4095 12.3630 -1.9317 -4.4557 + 1.1439 13.1194 12.3492 -1.9317 -4.4557 g_qlogis - -0.5648 + -0.5644 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 4.594 0.0000 0.000 0.0 0.0000 +cyan_0 4.591 0.0000 0.000 0.0 0.0000 log_k_JCZ38 0.000 0.7966 0.000 0.0 0.0000 log_k_J9Z38 0.000 0.0000 1.561 0.0 0.0000 log_k_JSE76 0.000 0.0000 0.000 0.8 0.0000 @@ -4036,17 +3779,17 @@ log_k1 0.000 0.0000 0.000 0.0 0.0000 log_k2 0.000 0.0000 0.000 0.0 0.0000 g_qlogis 0.000 0.0000 0.000 0.0 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 -cyan_0 0.000 0.00 0.0 0.000 0.0000 -log_k_JCZ38 0.000 0.00 0.0 0.000 0.0000 -log_k_J9Z38 0.000 0.00 0.0 0.000 0.0000 -log_k_JSE76 0.000 0.00 0.0 0.000 0.0000 -f_cyan_ilr_1 0.000 0.00 0.0 0.000 0.0000 -f_cyan_ilr_2 1.797 0.00 0.0 0.000 0.0000 -f_JCZ38_qlogis 0.000 13.85 0.0 0.000 0.0000 -f_JSE76_qlogis 0.000 0.00 14.1 0.000 0.0000 -log_k1 0.000 0.00 0.0 1.106 0.0000 -log_k2 0.000 0.00 0.0 0.000 0.6141 -g_qlogis 0.000 0.00 0.0 0.000 0.0000 +cyan_0 0.000 0.00 0.00 0.000 0.0000 +log_k_JCZ38 0.000 0.00 0.00 0.000 0.0000 +log_k_J9Z38 0.000 0.00 0.00 0.000 0.0000 +log_k_JSE76 0.000 0.00 0.00 0.000 0.0000 +f_cyan_ilr_1 0.000 0.00 0.00 0.000 0.0000 +f_cyan_ilr_2 1.797 0.00 0.00 0.000 0.0000 +f_JCZ38_qlogis 0.000 13.86 0.00 0.000 0.0000 +f_JSE76_qlogis 0.000 0.00 13.91 0.000 0.0000 +log_k1 0.000 0.00 0.00 1.106 0.0000 +log_k2 0.000 0.00 0.00 0.000 0.6141 +g_qlogis 0.000 0.00 0.00 0.000 0.0000 g_qlogis cyan_0 0.000 log_k_JCZ38 0.000 @@ -4068,45 +3811,45 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2290 2281 -1123 + 2288 2280 -1122 Optimised parameters: - est. lower upper -cyan_0 102.6903 101.44420 103.9365 -log_k_JCZ38 -2.4018 -2.98058 -1.8230 -log_k_J9Z38 -5.1865 -5.92931 -4.4437 -log_k_JSE76 -3.0784 -4.25226 -1.9045 -f_cyan_ilr_1 0.7157 0.37625 1.0551 -f_cyan_ilr_2 0.7073 0.20136 1.2132 -f_JCZ38_qlogis 4.6797 0.43240 8.9269 -f_JSE76_qlogis 5.0080 -1.01380 11.0299 -log_k1 -1.9620 -2.62909 -1.2949 -log_k2 -4.4894 -4.94958 -4.0292 -g_qlogis -0.4658 -1.34443 0.4129 -a.1 2.7158 2.52576 2.9059 -SD.log_k_JCZ38 0.5818 0.15679 1.0067 -SD.log_k_J9Z38 0.7421 0.16751 1.3167 -SD.log_k_JSE76 1.2841 0.43247 2.1356 -SD.f_cyan_ilr_1 0.3748 0.13040 0.6192 -SD.f_cyan_ilr_2 0.4550 0.08396 0.8261 -SD.f_JCZ38_qlogis 2.0862 -0.73390 4.9062 -SD.f_JSE76_qlogis 1.9585 -3.14773 7.0647 -SD.log_k1 0.7389 0.25761 1.2201 -SD.log_k2 0.5132 0.18143 0.8450 -SD.g_qlogis 0.9870 0.35773 1.6164 + est. lower upper +cyan_0 102.7204 1.014e+02 1.040e+02 +log_k_JCZ38 -2.8925 -4.044e+00 -1.741e+00 +log_k_J9Z38 -5.1430 -5.828e+00 -4.457e+00 +log_k_JSE76 -3.5577 -4.174e+00 -2.941e+00 +f_cyan_ilr_1 0.6929 3.788e-01 1.007e+00 +f_cyan_ilr_2 0.6066 5.342e-02 1.160e+00 +f_JCZ38_qlogis 9.8071 -2.819e+03 2.838e+03 +f_JSE76_qlogis 2.2229 5.684e-01 3.877e+00 +log_k1 -1.9339 -2.609e+00 -1.258e+00 +log_k2 -4.4709 -4.935e+00 -4.007e+00 +g_qlogis -0.4987 -1.373e+00 3.757e-01 +a.1 2.7368 2.545e+00 2.928e+00 +SD.log_k_JCZ38 1.2747 4.577e-01 2.092e+00 +SD.log_k_J9Z38 0.6758 1.418e-01 1.210e+00 +SD.log_k_JSE76 0.5869 1.169e-01 1.057e+00 +SD.f_cyan_ilr_1 0.3392 1.161e-01 5.622e-01 +SD.f_cyan_ilr_2 0.4200 8.501e-02 7.550e-01 +SD.f_JCZ38_qlogis 0.8511 -1.137e+06 1.137e+06 +SD.f_JSE76_qlogis 0.3767 -5.238e-01 1.277e+00 +SD.log_k1 0.7475 2.601e-01 1.235e+00 +SD.log_k2 0.5179 1.837e-01 8.521e-01 +SD.g_qlogis 0.9817 3.553e-01 1.608e+00 Correlation: cyan_0 l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76 -log_k_JCZ38 -0.0170 -log_k_J9Z38 -0.0457 0.0016 -log_k_JSE76 -0.0046 0.1183 0.0005 -f_cyan_ilr_1 0.0079 0.0072 -0.0909 0.0003 -f_cyan_ilr_2 -0.3114 0.0343 0.1542 0.0023 -0.0519 -f_JCZ38_qlogis 0.0777 -0.0601 -0.0152 0.0080 -0.0520 -0.2524 -f_JSE76_qlogis -0.0356 0.0817 0.0073 0.0051 0.0388 0.1959 -0.6236 -log_k1 0.0848 -0.0028 0.0010 -0.0010 -0.0014 -0.0245 0.0121 -0.0177 -log_k2 0.0274 -0.0001 0.0075 0.0000 -0.0023 -0.0060 0.0000 -0.0130 -g_qlogis 0.0159 0.0002 -0.0095 0.0002 0.0029 -0.0140 -0.0001 0.0149 +log_k_JCZ38 -0.0351 +log_k_J9Z38 -0.0541 0.0043 +log_k_JSE76 -0.0078 0.0900 -0.0014 +f_cyan_ilr_1 -0.0249 0.0268 -0.0962 0.0000 +f_cyan_ilr_2 -0.3560 0.0848 0.1545 -0.0022 0.0463 +f_JCZ38_qlogis 0.2005 -0.1226 -0.0347 0.0514 -0.1840 -0.5906 +f_JSE76_qlogis -0.1638 0.1307 0.0266 0.0001 0.1645 0.5181 -0.9297 +log_k1 0.0881 -0.0071 0.0005 -0.0070 -0.0064 -0.0346 0.0316 -0.0341 +log_k2 0.0238 -0.0003 0.0082 -0.0022 -0.0017 -0.0017 -0.0002 -0.0076 +g_qlogis 0.0198 -0.0002 -0.0109 0.0034 0.0017 -0.0176 0.0044 0.0051 log_k1 log_k2 log_k_JCZ38 log_k_J9Z38 @@ -4116,56 +3859,56 @@ f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 -log_k2 0.0280 -g_qlogis -0.0278 -0.0310 +log_k2 0.0276 +g_qlogis -0.0283 -0.0309 Random effects: - est. lower upper -SD.log_k_JCZ38 0.5818 0.15679 1.0067 -SD.log_k_J9Z38 0.7421 0.16751 1.3167 -SD.log_k_JSE76 1.2841 0.43247 2.1356 -SD.f_cyan_ilr_1 0.3748 0.13040 0.6192 -SD.f_cyan_ilr_2 0.4550 0.08396 0.8261 -SD.f_JCZ38_qlogis 2.0862 -0.73390 4.9062 -SD.f_JSE76_qlogis 1.9585 -3.14773 7.0647 -SD.log_k1 0.7389 0.25761 1.2201 -SD.log_k2 0.5132 0.18143 0.8450 -SD.g_qlogis 0.9870 0.35773 1.6164 + est. lower upper +SD.log_k_JCZ38 1.2747 4.577e-01 2.092e+00 +SD.log_k_J9Z38 0.6758 1.418e-01 1.210e+00 +SD.log_k_JSE76 0.5869 1.169e-01 1.057e+00 +SD.f_cyan_ilr_1 0.3392 1.161e-01 5.622e-01 +SD.f_cyan_ilr_2 0.4200 8.501e-02 7.550e-01 +SD.f_JCZ38_qlogis 0.8511 -1.137e+06 1.137e+06 +SD.f_JSE76_qlogis 0.3767 -5.238e-01 1.277e+00 +SD.log_k1 0.7475 2.601e-01 1.235e+00 +SD.log_k2 0.5179 1.837e-01 8.521e-01 +SD.g_qlogis 0.9817 3.553e-01 1.608e+00 Variance model: est. lower upper -a.1 2.716 2.526 2.906 +a.1 2.737 2.545 2.928 Backtransformed parameters: est. lower upper -cyan_0 1.027e+02 1.014e+02 103.93649 -k_JCZ38 9.056e-02 5.076e-02 0.16154 -k_J9Z38 5.591e-03 2.660e-03 0.01175 -k_JSE76 4.603e-02 1.423e-02 0.14890 -f_cyan_to_JCZ38 6.184e-01 NA NA -f_cyan_to_J9Z38 2.248e-01 NA NA -f_JCZ38_to_JSE76 9.908e-01 6.064e-01 0.99987 -f_JSE76_to_JCZ38 9.934e-01 2.662e-01 0.99998 -k1 1.406e-01 7.214e-02 0.27393 -k2 1.123e-02 7.086e-03 0.01779 -g 3.856e-01 2.068e-01 0.60177 +cyan_0 102.72037 1.014e+02 104.00464 +k_JCZ38 0.05544 1.752e-02 0.17539 +k_J9Z38 0.00584 2.942e-03 0.01159 +k_JSE76 0.02850 1.539e-02 0.05279 +f_cyan_to_JCZ38 0.59995 NA NA +f_cyan_to_J9Z38 0.22519 NA NA +f_JCZ38_to_JSE76 0.99994 0.000e+00 1.00000 +f_JSE76_to_JCZ38 0.90229 6.384e-01 0.97971 +k1 0.14459 7.357e-02 0.28414 +k2 0.01144 7.192e-03 0.01819 +g 0.37784 2.021e-01 0.59284 Resulting formation fractions: - ff -cyan_JCZ38 0.618443 -cyan_J9Z38 0.224770 -cyan_sink 0.156787 -JCZ38_JSE76 0.990803 -JCZ38_sink 0.009197 -JSE76_JCZ38 0.993360 -JSE76_sink 0.006640 + ff +cyan_JCZ38 5.999e-01 +cyan_J9Z38 2.252e-01 +cyan_sink 1.749e-01 +JCZ38_JSE76 9.999e-01 +JCZ38_sink 5.506e-05 +JSE76_JCZ38 9.023e-01 +JSE76_sink 9.771e-02 Estimated disappearance times: - DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 21.674 161.70 48.68 4.931 61.74 -JCZ38 7.654 25.43 NA NA NA -J9Z38 123.966 411.81 NA NA NA -JSE76 15.057 50.02 NA NA NA + DT50 DT90 DT50back DT50_k1 DT50_k2 +cyan 21.93 159.83 48.11 4.794 60.6 +JCZ38 12.50 41.53 NA NA NA +J9Z38 118.69 394.27 NA NA NA +JSE76 24.32 80.78 NA NA NA </code></pre> <p></p> @@ -4173,11 +3916,11 @@ JSE76 15.057 50.02 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:58:32 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:57:56 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -4197,59 +3940,59 @@ Data: Model predictions using solution type deSolve -Fitted in 733.398 s +Fitted in 691.67 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.7523 -1.5948 -5.0119 -2.2723 0.6719 + 101.7393 -1.4493 -5.0118 -2.1269 0.6720 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 - 5.1681 12.8238 12.4130 -2.0057 -4.5526 + 7.3362 13.4423 13.2659 -2.0061 -4.5527 g_qlogis - -0.5805 + -0.5806 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.627 0.000 0.000 0.000 0.0000 -log_k_JCZ38 0.000 2.327 0.000 0.000 0.0000 -log_k_J9Z38 0.000 0.000 1.664 0.000 0.0000 -log_k_JSE76 0.000 0.000 0.000 4.566 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6519 -f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 -f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 -f_JSE76_qlogis 0.000 0.000 0.000 0.000 0.0000 -log_k1 0.000 0.000 0.000 0.000 0.0000 -log_k2 0.000 0.000 0.000 0.000 0.0000 -g_qlogis 0.000 0.000 0.000 0.000 0.0000 +cyan_0 5.604 0.00 0.000 0.000 0.0000 +log_k_JCZ38 0.000 2.77 0.000 0.000 0.0000 +log_k_J9Z38 0.000 0.00 1.662 0.000 0.0000 +log_k_JSE76 0.000 0.00 0.000 5.021 0.0000 +f_cyan_ilr_1 0.000 0.00 0.000 0.000 0.6519 +f_cyan_ilr_2 0.000 0.00 0.000 0.000 0.0000 +f_JCZ38_qlogis 0.000 0.00 0.000 0.000 0.0000 +f_JSE76_qlogis 0.000 0.00 0.000 0.000 0.0000 +log_k1 0.000 0.00 0.000 0.000 0.0000 +log_k2 0.000 0.00 0.000 0.000 0.0000 +g_qlogis 0.000 0.00 0.000 0.000 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 -cyan_0 0.0 0.00 0.00 0.0000 0.0000 -log_k_JCZ38 0.0 0.00 0.00 0.0000 0.0000 -log_k_J9Z38 0.0 0.00 0.00 0.0000 0.0000 -log_k_JSE76 0.0 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_1 0.0 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 10.1 0.00 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.0 13.99 0.00 0.0000 0.0000 -f_JSE76_qlogis 0.0 0.00 14.15 0.0000 0.0000 -log_k1 0.0 0.00 0.00 0.8452 0.0000 -log_k2 0.0 0.00 0.00 0.0000 0.5968 -g_qlogis 0.0 0.00 0.00 0.0000 0.0000 +cyan_0 0.00 0.00 0.00 0.0000 0.0000 +log_k_JCZ38 0.00 0.00 0.00 0.0000 0.0000 +log_k_J9Z38 0.00 0.00 0.00 0.0000 0.0000 +log_k_JSE76 0.00 0.00 0.00 0.0000 0.0000 +f_cyan_ilr_1 0.00 0.00 0.00 0.0000 0.0000 +f_cyan_ilr_2 13.37 0.00 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 14.21 0.00 0.0000 0.0000 +f_JSE76_qlogis 0.00 0.00 14.58 0.0000 0.0000 +log_k1 0.00 0.00 0.00 0.8453 0.0000 +log_k2 0.00 0.00 0.00 0.0000 0.5969 +g_qlogis 0.00 0.00 0.00 0.0000 0.0000 g_qlogis -cyan_0 0.000 -log_k_JCZ38 0.000 -log_k_J9Z38 0.000 -log_k_JSE76 0.000 -f_cyan_ilr_1 0.000 -f_cyan_ilr_2 0.000 -f_JCZ38_qlogis 0.000 -f_JSE76_qlogis 0.000 -log_k1 0.000 -log_k2 0.000 -g_qlogis 1.691 +cyan_0 0.00 +log_k_JCZ38 0.00 +log_k_J9Z38 0.00 +log_k_JSE76 0.00 +f_cyan_ilr_1 0.00 +f_cyan_ilr_2 0.00 +f_JCZ38_qlogis 0.00 +f_JSE76_qlogis 0.00 +log_k1 0.00 +log_k2 0.00 +g_qlogis 1.69 Starting values for error model parameters: a.1 b.1 @@ -4262,42 +4005,42 @@ Likelihood computed by importance sampling 2234 2226 -1095 Optimised parameters: - est. lower upper -cyan_0 101.10667 9.903e+01 103.18265 -log_k_JCZ38 -2.49437 -3.297e+00 -1.69221 -log_k_J9Z38 -5.08171 -5.875e+00 -4.28846 -log_k_JSE76 -3.20072 -4.180e+00 -2.22163 -f_cyan_ilr_1 0.71059 3.639e-01 1.05727 -f_cyan_ilr_2 1.15398 2.981e-01 2.00984 -f_JCZ38_qlogis 3.18027 1.056e+00 5.30452 -f_JSE76_qlogis 5.61578 -2.505e+01 36.28077 -log_k1 -2.38875 -2.517e+00 -2.26045 -log_k2 -4.67246 -4.928e+00 -4.41715 -g_qlogis -0.28231 -1.135e+00 0.57058 -a.1 2.08190 1.856e+00 2.30785 -b.1 0.06114 5.015e-02 0.07214 -SD.log_k_JCZ38 0.84622 2.637e-01 1.42873 -SD.log_k_J9Z38 0.84564 2.566e-01 1.43464 -SD.log_k_JSE76 1.04385 3.242e-01 1.76351 -SD.f_cyan_ilr_1 0.38568 1.362e-01 0.63514 -SD.f_cyan_ilr_2 0.68046 7.166e-02 1.28925 -SD.f_JCZ38_qlogis 1.25244 -4.213e-02 2.54700 -SD.f_JSE76_qlogis 0.28202 -1.515e+03 1515.87968 -SD.log_k2 0.25749 7.655e-02 0.43843 -SD.g_qlogis 0.94535 3.490e-01 1.54174 + est. lower upper +cyan_0 101.25496 99.14662 103.36331 +log_k_JCZ38 -2.55593 -3.32972 -1.78215 +log_k_J9Z38 -5.07103 -5.85423 -4.28783 +log_k_JSE76 -3.25468 -4.17577 -2.33360 +f_cyan_ilr_1 0.70139 0.35924 1.04355 +f_cyan_ilr_2 1.07712 0.17789 1.97636 +f_JCZ38_qlogis 3.57483 0.05990 7.08976 +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 1.86481 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 0.25395 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 -0.42359 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 Correlation: cyan_0 l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76 -log_k_JCZ38 -0.0086 -log_k_J9Z38 -0.0363 -0.0007 -log_k_JSE76 0.0015 0.1210 -0.0017 -f_cyan_ilr_1 -0.0048 0.0095 -0.0572 0.0030 -f_cyan_ilr_2 -0.4788 0.0328 0.1143 0.0027 -0.0316 -f_JCZ38_qlogis 0.0736 -0.0664 -0.0137 0.0145 -0.0444 -0.2175 -f_JSE76_qlogis -0.0137 0.0971 0.0035 0.0009 0.0293 0.1333 -0.6767 -log_k1 0.2345 -0.0350 -0.0099 -0.0113 -0.0126 -0.1652 0.1756 -0.2161 -log_k2 0.0440 -0.0133 0.0199 -0.0040 -0.0097 -0.0119 0.0604 -0.1306 -g_qlogis 0.0438 0.0078 -0.0123 0.0029 0.0046 -0.0363 -0.0318 0.0736 +log_k_JCZ38 -0.0265 +log_k_J9Z38 -0.0392 0.0024 +log_k_JSE76 0.0011 0.1220 -0.0016 +f_cyan_ilr_1 -0.0161 0.0217 -0.0552 0.0034 +f_cyan_ilr_2 -0.4718 0.0829 0.1102 0.0042 0.0095 +f_JCZ38_qlogis 0.1609 -0.1318 -0.0277 0.0081 -0.1040 -0.4559 +f_JSE76_qlogis -0.1289 0.1494 0.0219 0.0012 0.1004 0.4309 -0.8543 +log_k1 0.2618 -0.0739 -0.0167 -0.0148 -0.0444 -0.2768 0.3518 -0.3818 +log_k2 0.0603 -0.0217 0.0174 -0.0058 -0.0197 -0.0533 0.0923 -0.1281 +g_qlogis 0.0362 0.0115 -0.0111 0.0040 0.0095 -0.0116 -0.0439 0.0651 log_k1 log_k2 log_k_JCZ38 log_k_J9Z38 @@ -4307,56 +4050,56 @@ f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 -log_k2 0.3198 -g_qlogis -0.1666 -0.0954 +log_k2 0.3269 +g_qlogis -0.1656 -0.0928 Random effects: - est. lower upper -SD.log_k_JCZ38 0.8462 2.637e-01 1.4287 -SD.log_k_J9Z38 0.8456 2.566e-01 1.4346 -SD.log_k_JSE76 1.0439 3.242e-01 1.7635 -SD.f_cyan_ilr_1 0.3857 1.362e-01 0.6351 -SD.f_cyan_ilr_2 0.6805 7.166e-02 1.2893 -SD.f_JCZ38_qlogis 1.2524 -4.213e-02 2.5470 -SD.f_JSE76_qlogis 0.2820 -1.515e+03 1515.8797 -SD.log_k2 0.2575 7.655e-02 0.4384 -SD.g_qlogis 0.9453 3.490e-01 1.5417 + est. lower upper +SD.log_k_JCZ38 0.8114 0.25296 1.3698 +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 -0.42359 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 2.08190 1.85595 2.30785 -b.1 0.06114 0.05015 0.07214 +a.1 2.05925 1.86481 2.25369 +b.1 0.06172 0.05062 0.07282 Backtransformed parameters: est. lower upper -cyan_0 1.011e+02 9.903e+01 103.18265 -k_JCZ38 8.255e-02 3.701e-02 0.18411 -k_J9Z38 6.209e-03 2.809e-03 0.01373 -k_JSE76 4.073e-02 1.530e-02 0.10843 -f_cyan_to_JCZ38 6.608e-01 NA NA -f_cyan_to_J9Z38 2.419e-01 NA NA -f_JCZ38_to_JSE76 9.601e-01 7.419e-01 0.99506 -f_JSE76_to_JCZ38 9.964e-01 1.322e-11 1.00000 -k1 9.174e-02 8.070e-02 0.10430 -k2 9.349e-03 7.243e-03 0.01207 -g 4.299e-01 2.432e-01 0.63890 +cyan_0 1.013e+02 9.915e+01 103.36331 +k_JCZ38 7.762e-02 3.580e-02 0.16828 +k_J9Z38 6.276e-03 2.868e-03 0.01373 +k_JSE76 3.859e-02 1.536e-02 0.09695 +f_cyan_to_JCZ38 6.520e-01 NA NA +f_cyan_to_J9Z38 2.418e-01 NA NA +f_JCZ38_to_JSE76 9.727e-01 5.150e-01 0.99917 +f_JSE76_to_JCZ38 9.895e-01 7.052e-04 1.00000 +k1 9.236e-02 8.075e-02 0.10565 +k2 9.397e-03 7.309e-03 0.01208 +g 4.294e-01 2.420e-01 0.63945 Resulting formation fractions: - ff -cyan_JCZ38 0.660808 -cyan_J9Z38 0.241904 -cyan_sink 0.097288 -JCZ38_JSE76 0.960085 -JCZ38_sink 0.039915 -JSE76_JCZ38 0.996373 -JSE76_sink 0.003627 + ff +cyan_JCZ38 0.65203 +cyan_J9Z38 0.24181 +cyan_sink 0.10616 +JCZ38_JSE76 0.97274 +JCZ38_sink 0.02726 +JSE76_JCZ38 0.98953 +JSE76_sink 0.01047 Estimated disappearance times: - DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 24.359 186.18 56.05 7.555 74.14 -JCZ38 8.397 27.89 NA NA NA -J9Z38 111.631 370.83 NA NA NA -JSE76 17.017 56.53 NA NA NA + DT50 DT90 DT50back DT50_k1 DT50_k2 +cyan 24.26 185.34 55.79 7.504 73.77 +JCZ38 8.93 29.66 NA NA NA +J9Z38 110.45 366.89 NA NA NA +JSE76 17.96 59.66 NA NA NA </code></pre> <p></p> @@ -4364,11 +4107,11 @@ JSE76 17.017 56.53 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:55:51 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:55:26 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -4386,20 +4129,20 @@ Data: Model predictions using solution type deSolve -Fitted in 572.747 s +Fitted in 542.162 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_free_0 log_k_cyan_free log_k_cyan_free_bound - 102.4394 -2.7673 -2.8942 + 102.4395 -2.7673 -2.8942 log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 -3.6201 -2.3107 -5.3123 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 -3.7120 0.6754 1.1448 f_JCZ38_qlogis f_JSE76_qlogis - 13.2672 13.3538 + 14.8408 15.4734 Fixed degradation parameter values: None @@ -4430,17 +4173,17 @@ f_cyan_ilr_2 0.000 0.0000 0.000 0.0 f_JCZ38_qlogis 0.000 0.0000 0.000 0.0 f_JSE76_qlogis 0.000 0.0000 0.000 0.0 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis -cyan_free_0 0.0000 0.000 0.00 0.00 -log_k_cyan_free 0.0000 0.000 0.00 0.00 -log_k_cyan_free_bound 0.0000 0.000 0.00 0.00 -log_k_cyan_bound_free 0.0000 0.000 0.00 0.00 -log_k_JCZ38 0.0000 0.000 0.00 0.00 -log_k_J9Z38 0.0000 0.000 0.00 0.00 -log_k_JSE76 0.0000 0.000 0.00 0.00 -f_cyan_ilr_1 0.6349 0.000 0.00 0.00 -f_cyan_ilr_2 0.0000 1.797 0.00 0.00 -f_JCZ38_qlogis 0.0000 0.000 13.84 0.00 -f_JSE76_qlogis 0.0000 0.000 0.00 14.66 +cyan_free_0 0.0000 0.000 0.0 0.00 +log_k_cyan_free 0.0000 0.000 0.0 0.00 +log_k_cyan_free_bound 0.0000 0.000 0.0 0.00 +log_k_cyan_bound_free 0.0000 0.000 0.0 0.00 +log_k_JCZ38 0.0000 0.000 0.0 0.00 +log_k_J9Z38 0.0000 0.000 0.0 0.00 +log_k_JSE76 0.0000 0.000 0.0 0.00 +f_cyan_ilr_1 0.6349 0.000 0.0 0.00 +f_cyan_ilr_2 0.0000 1.797 0.0 0.00 +f_JCZ38_qlogis 0.0000 0.000 15.6 0.00 +f_JSE76_qlogis 0.0000 0.000 0.0 17.52 Starting values for error model parameters: a.1 @@ -4450,45 +4193,45 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2284 2275 -1120 + 2283 2275 -1120 Optimised parameters: - est. lower upper -cyan_free_0 102.7730 1.015e+02 1.041e+02 -log_k_cyan_free -2.8530 -3.167e+00 -2.539e+00 -log_k_cyan_free_bound -2.7326 -3.543e+00 -1.922e+00 -log_k_cyan_bound_free -3.5582 -4.126e+00 -2.990e+00 -log_k_JCZ38 -2.3810 -2.921e+00 -1.841e+00 -log_k_J9Z38 -5.2301 -5.963e+00 -4.497e+00 -log_k_JSE76 -3.0286 -4.286e+00 -1.771e+00 -f_cyan_ilr_1 0.7081 3.733e-01 1.043e+00 -f_cyan_ilr_2 0.5847 7.846e-03 1.162e+00 -f_JCZ38_qlogis 9.5676 -1.323e+03 1.342e+03 -f_JSE76_qlogis 3.7042 7.254e-02 7.336e+00 -a.1 2.7222 2.532e+00 2.913e+00 -SD.log_k_cyan_free 0.3338 1.086e-01 5.589e-01 -SD.log_k_cyan_free_bound 0.8888 3.023e-01 1.475e+00 -SD.log_k_cyan_bound_free 0.6220 2.063e-01 1.038e+00 -SD.log_k_JCZ38 0.5221 1.334e-01 9.108e-01 -SD.log_k_J9Z38 0.7104 1.371e-01 1.284e+00 -SD.log_k_JSE76 1.3837 4.753e-01 2.292e+00 -SD.f_cyan_ilr_1 0.3620 1.248e-01 5.992e-01 -SD.f_cyan_ilr_2 0.4259 8.145e-02 7.704e-01 -SD.f_JCZ38_qlogis 3.5332 -1.037e+05 1.037e+05 -SD.f_JSE76_qlogis 1.6990 -2.771e-01 3.675e+00 + est. lower upper +cyan_free_0 102.6517 101.40815 103.8952 +log_k_cyan_free -2.8729 -3.18649 -2.5593 +log_k_cyan_free_bound -2.7803 -3.60525 -1.9552 +log_k_cyan_bound_free -3.5845 -4.16644 -3.0026 +log_k_JCZ38 -2.3411 -2.89698 -1.7852 +log_k_J9Z38 -5.2487 -6.01271 -4.4847 +log_k_JSE76 -3.0259 -4.28274 -1.7690 +f_cyan_ilr_1 0.7289 0.38214 1.0756 +f_cyan_ilr_2 0.6891 0.18277 1.1954 +f_JCZ38_qlogis 4.2162 0.47015 7.9622 +f_JSE76_qlogis 5.8911 -20.19088 31.9730 +a.1 2.7159 2.52587 2.9060 +SD.log_k_cyan_free 0.3354 0.10979 0.5610 +SD.log_k_cyan_free_bound 0.9061 0.30969 1.5025 +SD.log_k_cyan_bound_free 0.6376 0.21229 1.0628 +SD.log_k_JCZ38 0.5499 0.14533 0.9545 +SD.log_k_J9Z38 0.7457 0.15106 1.3404 +SD.log_k_JSE76 1.3822 0.47329 2.2912 +SD.f_cyan_ilr_1 0.3820 0.13280 0.6313 +SD.f_cyan_ilr_2 0.4317 0.06803 0.7953 +SD.f_JCZ38_qlogis 1.8258 -0.25423 3.9059 +SD.f_JSE76_qlogis 2.2348 -83.33679 87.8065 Correlation: cyn_f_0 lg_k_c_ lg_k_cyn_f_ lg_k_cyn_b_ l__JCZ3 l__J9Z3 -log_k_cyan_free 0.2126 -log_k_cyan_free_bound 0.0894 0.0871 -log_k_cyan_bound_free 0.0033 0.0410 0.0583 -log_k_JCZ38 -0.0708 -0.0280 -0.0147 0.0019 -log_k_J9Z38 -0.0535 -0.0138 0.0012 0.0148 0.0085 -log_k_JSE76 -0.0066 -0.0030 -0.0021 -0.0005 0.1090 0.0010 -f_cyan_ilr_1 -0.0364 -0.0157 -0.0095 -0.0015 0.0458 -0.0960 -f_cyan_ilr_2 -0.3814 -0.1104 -0.0423 0.0146 0.1540 0.1526 -f_JCZ38_qlogis 0.2507 0.0969 0.0482 -0.0097 -0.2282 -0.0363 -f_JSE76_qlogis -0.1648 -0.0710 -0.0443 -0.0087 0.2002 0.0226 +log_k_cyan_free 0.1944 +log_k_cyan_free_bound 0.0815 0.0814 +log_k_cyan_bound_free 0.0106 0.0426 0.0585 +log_k_JCZ38 -0.0231 -0.0106 -0.0089 -0.0051 +log_k_J9Z38 -0.0457 -0.0108 0.0019 0.0129 0.0032 +log_k_JSE76 -0.0054 -0.0024 -0.0017 -0.0005 0.1108 0.0009 +f_cyan_ilr_1 0.0051 -0.0005 -0.0035 -0.0056 0.0131 -0.0967 +f_cyan_ilr_2 -0.3182 -0.0771 -0.0309 -0.0038 0.0680 0.1643 +f_JCZ38_qlogis 0.0834 0.0369 0.0302 0.0172 -0.1145 -0.0204 +f_JSE76_qlogis -0.0553 -0.0365 -0.0441 -0.0414 0.1579 0.0175 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 log_k_cyan_free log_k_cyan_free_bound @@ -4496,63 +4239,63 @@ log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76 -f_cyan_ilr_1 0.0001 -f_cyan_ilr_2 0.0031 0.0586 -f_JCZ38_qlogis 0.0023 -0.1867 -0.6255 -f_JSE76_qlogis 0.0082 0.1356 0.4519 -0.7951 +f_cyan_ilr_1 -0.0002 +f_cyan_ilr_2 0.0020 -0.0415 +f_JCZ38_qlogis 0.0052 -0.0665 -0.3437 +f_JSE76_qlogis 0.0066 0.0635 0.3491 -0.7487 Random effects: - est. lower upper -SD.log_k_cyan_free 0.3338 1.086e-01 5.589e-01 -SD.log_k_cyan_free_bound 0.8888 3.023e-01 1.475e+00 -SD.log_k_cyan_bound_free 0.6220 2.063e-01 1.038e+00 -SD.log_k_JCZ38 0.5221 1.334e-01 9.108e-01 -SD.log_k_J9Z38 0.7104 1.371e-01 1.284e+00 -SD.log_k_JSE76 1.3837 4.753e-01 2.292e+00 -SD.f_cyan_ilr_1 0.3620 1.248e-01 5.992e-01 -SD.f_cyan_ilr_2 0.4259 8.145e-02 7.704e-01 -SD.f_JCZ38_qlogis 3.5332 -1.037e+05 1.037e+05 -SD.f_JSE76_qlogis 1.6990 -2.771e-01 3.675e+00 + est. lower upper +SD.log_k_cyan_free 0.3354 0.10979 0.5610 +SD.log_k_cyan_free_bound 0.9061 0.30969 1.5025 +SD.log_k_cyan_bound_free 0.6376 0.21229 1.0628 +SD.log_k_JCZ38 0.5499 0.14533 0.9545 +SD.log_k_J9Z38 0.7457 0.15106 1.3404 +SD.log_k_JSE76 1.3822 0.47329 2.2912 +SD.f_cyan_ilr_1 0.3820 0.13280 0.6313 +SD.f_cyan_ilr_2 0.4317 0.06803 0.7953 +SD.f_JCZ38_qlogis 1.8258 -0.25423 3.9059 +SD.f_JSE76_qlogis 2.2348 -83.33679 87.8065 Variance model: est. lower upper -a.1 2.722 2.532 2.913 +a.1 2.716 2.526 2.906 Backtransformed parameters: est. lower upper -cyan_free_0 1.028e+02 1.015e+02 104.06475 -k_cyan_free 5.767e-02 4.213e-02 0.07894 -k_cyan_free_bound 6.505e-02 2.892e-02 0.14633 -k_cyan_bound_free 2.849e-02 1.614e-02 0.05028 -k_JCZ38 9.246e-02 5.390e-02 0.15859 -k_J9Z38 5.353e-03 2.572e-03 0.01114 -k_JSE76 4.838e-02 1.376e-02 0.17009 -f_cyan_free_to_JCZ38 6.011e-01 5.028e-01 0.83792 -f_cyan_free_to_J9Z38 2.208e-01 5.028e-01 0.83792 -f_JCZ38_to_JSE76 9.999e-01 0.000e+00 1.00000 -f_JSE76_to_JCZ38 9.760e-01 5.181e-01 0.99935 +cyan_free_0 1.027e+02 1.014e+02 103.89517 +k_cyan_free 5.654e-02 4.132e-02 0.07736 +k_cyan_free_bound 6.202e-02 2.718e-02 0.14153 +k_cyan_bound_free 2.775e-02 1.551e-02 0.04966 +k_JCZ38 9.622e-02 5.519e-02 0.16777 +k_J9Z38 5.254e-03 2.447e-03 0.01128 +k_JSE76 4.852e-02 1.380e-02 0.17051 +f_cyan_free_to_JCZ38 6.197e-01 5.643e-01 0.84429 +f_cyan_free_to_J9Z38 2.211e-01 5.643e-01 0.84429 +f_JCZ38_to_JSE76 9.855e-01 6.154e-01 0.99965 +f_JSE76_to_JCZ38 9.972e-01 1.703e-09 1.00000 Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g -0.13942 0.01178 0.35948 +0.13466 0.01165 0.36490 Resulting formation fractions: - ff -cyan_free_JCZ38 6.011e-01 -cyan_free_J9Z38 2.208e-01 -cyan_free_sink 1.780e-01 -cyan_free 1.000e+00 -JCZ38_JSE76 9.999e-01 -JCZ38_sink 6.996e-05 -JSE76_JCZ38 9.760e-01 -JSE76_sink 2.403e-02 + ff +cyan_free_JCZ38 0.619745 +cyan_free_J9Z38 0.221083 +cyan_free_sink 0.159172 +cyan_free 1.000000 +JCZ38_JSE76 0.985460 +JCZ38_sink 0.014540 +JSE76_JCZ38 0.997244 +JSE76_sink 0.002756 Estimated disappearance times: DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 23.390 157.60 47.44 4.971 58.82 -JCZ38 7.497 24.90 NA NA NA -J9Z38 129.482 430.13 NA NA NA -JSE76 14.326 47.59 NA NA NA +cyan 23.293 158.67 47.77 5.147 59.5 +JCZ38 7.203 23.93 NA NA NA +J9Z38 131.918 438.22 NA NA NA +JSE76 14.287 47.46 NA NA NA </code></pre> <p></p> @@ -4560,11 +4303,11 @@ JSE76 14.326 47.59 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 17:58:21 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 07:58:06 2025 +Date of summary: Sun Feb 16 17:03:40 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -4582,20 +4325,20 @@ Data: Model predictions using solution type deSolve -Fitted in 722.847 s +Fitted in 701.582 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_free_0 log_k_cyan_free log_k_cyan_free_bound - 101.751 -2.837 -3.016 + 101.7511 -2.8370 -3.0162 log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 - -3.660 -2.299 -5.313 + -3.6600 -2.2988 -5.3129 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 - -3.699 0.672 5.873 + -3.6991 0.6722 4.8596 f_JCZ38_qlogis f_JSE76_qlogis - 13.216 13.338 + 13.4678 14.2149 Fixed degradation parameter values: None @@ -4626,17 +4369,17 @@ f_cyan_ilr_2 0.000 0.0000 0.000 0.0000 f_JCZ38_qlogis 0.000 0.0000 0.000 0.0000 f_JSE76_qlogis 0.000 0.0000 0.000 0.0000 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis -cyan_free_0 0.0000 0.00 0.00 0.00 -log_k_cyan_free 0.0000 0.00 0.00 0.00 -log_k_cyan_free_bound 0.0000 0.00 0.00 0.00 -log_k_cyan_bound_free 0.0000 0.00 0.00 0.00 -log_k_JCZ38 0.0000 0.00 0.00 0.00 -log_k_J9Z38 0.0000 0.00 0.00 0.00 -log_k_JSE76 0.0000 0.00 0.00 0.00 -f_cyan_ilr_1 0.6519 0.00 0.00 0.00 -f_cyan_ilr_2 0.0000 10.78 0.00 0.00 -f_JCZ38_qlogis 0.0000 0.00 13.96 0.00 -f_JSE76_qlogis 0.0000 0.00 0.00 14.69 +cyan_free_0 0.0000 0.000 0.00 0.00 +log_k_cyan_free 0.0000 0.000 0.00 0.00 +log_k_cyan_free_bound 0.0000 0.000 0.00 0.00 +log_k_cyan_bound_free 0.0000 0.000 0.00 0.00 +log_k_JCZ38 0.0000 0.000 0.00 0.00 +log_k_J9Z38 0.0000 0.000 0.00 0.00 +log_k_JSE76 0.0000 0.000 0.00 0.00 +f_cyan_ilr_1 0.6518 0.000 0.00 0.00 +f_cyan_ilr_2 0.0000 9.981 0.00 0.00 +f_JCZ38_qlogis 0.0000 0.000 14.26 0.00 +f_JSE76_qlogis 0.0000 0.000 0.00 16.17 Starting values for error model parameters: a.1 b.1 @@ -4646,45 +4389,45 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2240 2232 -1098 + 2240 2231 -1098 Optimised parameters: - est. lower upper -cyan_free_0 101.10205 98.99221 103.2119 -log_k_cyan_free -3.16929 -3.61395 -2.7246 -log_k_cyan_free_bound -3.38259 -3.63022 -3.1350 -log_k_cyan_bound_free -3.81075 -4.13888 -3.4826 -log_k_JCZ38 -2.42057 -3.00756 -1.8336 -log_k_J9Z38 -5.07501 -5.85138 -4.2986 -log_k_JSE76 -3.12442 -4.21277 -2.0361 -f_cyan_ilr_1 0.70577 0.35788 1.0537 -f_cyan_ilr_2 1.14824 0.15810 2.1384 -f_JCZ38_qlogis 3.52245 0.43257 6.6123 -f_JSE76_qlogis 5.65140 -21.22295 32.5257 -a.1 2.07062 1.84329 2.2980 -b.1 0.06227 0.05124 0.0733 -SD.log_k_cyan_free 0.49468 0.18566 0.8037 -SD.log_k_cyan_bound_free 0.28972 0.07188 0.5076 -SD.log_k_JCZ38 0.58852 0.16800 1.0090 -SD.log_k_J9Z38 0.82500 0.24730 1.4027 -SD.log_k_JSE76 1.19201 0.40313 1.9809 -SD.f_cyan_ilr_1 0.38534 0.13640 0.6343 -SD.f_cyan_ilr_2 0.72463 0.10076 1.3485 -SD.f_JCZ38_qlogis 1.38223 -0.20997 2.9744 -SD.f_JSE76_qlogis 2.07989 -72.53027 76.6901 + est. lower upper +cyan_free_0 100.73014 9.873e+01 1.027e+02 +log_k_cyan_free -3.19634 -3.641e+00 -2.752e+00 +log_k_cyan_free_bound -3.43533 -3.674e+00 -3.197e+00 +log_k_cyan_bound_free -3.83282 -4.163e+00 -3.503e+00 +log_k_JCZ38 -2.51065 -3.225e+00 -1.796e+00 +log_k_J9Z38 -5.02539 -5.825e+00 -4.226e+00 +log_k_JSE76 -3.24777 -4.163e+00 -2.333e+00 +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 1.877e+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 6.809e-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 -2.808e-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 -log_k_cyan_free 0.1117 -log_k_cyan_free_bound 0.1763 0.1828 -log_k_cyan_bound_free 0.0120 0.0593 0.5030 -log_k_JCZ38 -0.0459 -0.0230 -0.0931 -0.0337 -log_k_J9Z38 -0.0381 -0.0123 -0.0139 0.0237 0.0063 -log_k_JSE76 -0.0044 -0.0038 -0.0175 -0.0072 0.1120 0.0003 -f_cyan_ilr_1 -0.0199 -0.0087 -0.0407 -0.0233 0.0268 -0.0552 -f_cyan_ilr_2 -0.4806 -0.1015 -0.2291 -0.0269 0.1156 0.1113 -f_JCZ38_qlogis 0.1805 0.0825 0.3085 0.0963 -0.1674 -0.0314 -f_JSE76_qlogis -0.1586 -0.0810 -0.3560 -0.1563 0.2025 0.0278 +log_k_cyan_free 0.0936 +log_k_cyan_free_bound 0.1302 0.1627 +log_k_cyan_bound_free 0.0029 0.0525 0.5181 +log_k_JCZ38 -0.0116 -0.0077 -0.0430 -0.0236 +log_k_J9Z38 -0.0192 -0.0077 -0.0048 0.0229 -0.0005 +log_k_JSE76 0.0007 -0.0020 -0.0134 -0.0072 0.1225 -0.0016 +f_cyan_ilr_1 -0.0118 -0.0027 -0.0132 -0.0118 0.0127 -0.0505 +f_cyan_ilr_2 -0.4643 -0.0762 -0.1245 0.0137 0.0497 0.1003 +f_JCZ38_qlogis 0.0710 0.0371 0.1826 0.0925 -0.0869 -0.0130 +f_JSE76_qlogis -0.0367 -0.0270 -0.2274 -0.1865 0.1244 0.0098 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 log_k_cyan_free log_k_cyan_free_bound @@ -4692,63 +4435,63 @@ log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76 -f_cyan_ilr_1 0.0024 -f_cyan_ilr_2 0.0087 0.0172 -f_JCZ38_qlogis -0.0016 -0.1047 -0.4656 -f_JSE76_qlogis 0.0119 0.1034 0.4584 -0.8137 +f_cyan_ilr_1 0.0036 +f_cyan_ilr_2 0.0050 -0.0201 +f_JCZ38_qlogis 0.0142 -0.0529 -0.2698 +f_JSE76_qlogis 0.0064 0.0345 0.2015 -0.7058 Random effects: - est. lower upper -SD.log_k_cyan_free 0.4947 0.18566 0.8037 -SD.log_k_cyan_bound_free 0.2897 0.07188 0.5076 -SD.log_k_JCZ38 0.5885 0.16800 1.0090 -SD.log_k_J9Z38 0.8250 0.24730 1.4027 -SD.log_k_JSE76 1.1920 0.40313 1.9809 -SD.f_cyan_ilr_1 0.3853 0.13640 0.6343 -SD.f_cyan_ilr_2 0.7246 0.10076 1.3485 -SD.f_JCZ38_qlogis 1.3822 -0.20997 2.9744 -SD.f_JSE76_qlogis 2.0799 -72.53027 76.6901 + est. lower upper +SD.log_k_cyan_free 0.4967 1.865e-01 8.069e-01 +SD.log_k_cyan_bound_free 0.2854 6.809e-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 -2.808e-02 2.128e+00 +SD.f_JSE76_qlogis 0.4468 -3.985e+05 3.985e+05 Variance model: - est. lower upper -a.1 2.07062 1.84329 2.2980 -b.1 0.06227 0.05124 0.0733 + est. lower upper +a.1 2.07082 1.87680 2.26483 +b.1 0.06227 0.05098 0.07355 Backtransformed parameters: - est. lower upper -cyan_free_0 1.011e+02 9.899e+01 103.21190 -k_cyan_free 4.203e-02 2.695e-02 0.06557 -k_cyan_free_bound 3.396e-02 2.651e-02 0.04350 -k_cyan_bound_free 2.213e-02 1.594e-02 0.03073 -k_JCZ38 8.887e-02 4.941e-02 0.15984 -k_J9Z38 6.251e-03 2.876e-03 0.01359 -k_JSE76 4.396e-02 1.481e-02 0.13054 -f_cyan_free_to_JCZ38 6.590e-01 5.557e-01 0.95365 -f_cyan_free_to_J9Z38 2.429e-01 5.557e-01 0.95365 -f_JCZ38_to_JSE76 9.713e-01 6.065e-01 0.99866 -f_JSE76_to_JCZ38 9.965e-01 6.067e-10 1.00000 + est. lower upper +cyan_free_0 1.007e+02 9.873e+01 102.72898 +k_cyan_free 4.091e-02 2.623e-02 0.06382 +k_cyan_free_bound 3.221e-02 2.537e-02 0.04090 +k_cyan_bound_free 2.165e-02 1.557e-02 0.03011 +k_JCZ38 8.122e-02 3.975e-02 0.16594 +k_J9Z38 6.569e-03 2.954e-03 0.01461 +k_JSE76 3.886e-02 1.556e-02 0.09703 +f_cyan_free_to_JCZ38 6.785e-01 6.102e-01 0.97309 +f_cyan_free_to_J9Z38 2.498e-01 6.102e-01 0.97309 +f_JCZ38_to_JSE76 9.452e-01 7.392e-01 0.99056 +f_JSE76_to_JCZ38 9.998e-01 5.580e-279 1.00000 Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g -0.08749 0.01063 0.40855 +0.08426 0.01051 0.41220 Resulting formation fractions: - ff -cyan_free_JCZ38 0.65905 -cyan_free_J9Z38 0.24291 -cyan_free_sink 0.09805 -cyan_free 1.00000 -JCZ38_JSE76 0.97132 -JCZ38_sink 0.02868 -JSE76_JCZ38 0.99650 -JSE76_sink 0.00350 + ff +cyan_free_JCZ38 0.6784541 +cyan_free_J9Z38 0.2498405 +cyan_free_sink 0.0717054 +cyan_free 1.0000000 +JCZ38_JSE76 0.9452043 +JCZ38_sink 0.0547957 +JSE76_JCZ38 0.9998226 +JSE76_sink 0.0001774 Estimated disappearance times: - DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 24.91 167.16 50.32 7.922 65.19 -JCZ38 7.80 25.91 NA NA NA -J9Z38 110.89 368.36 NA NA NA -JSE76 15.77 52.38 NA NA NA + DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 +cyan 25.237 168.51 50.73 8.226 65.95 +JCZ38 8.535 28.35 NA NA NA +J9Z38 105.517 350.52 NA NA NA +JSE76 17.837 59.25 NA NA NA </code></pre> <p></p> @@ -4761,11 +4504,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:12:10 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:11:01 2025 +Date of summary: Sun Feb 16 17:03:41 2025 Equations: d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan @@ -4780,27 +4523,27 @@ Data: Model predictions using solution type deSolve -Fitted in 816.454 s +Fitted in 773.693 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.9028 -1.9055 -5.0249 -2.5646 0.6807 + 102.4477 -1.8631 -5.1087 -2.5114 0.6826 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta - 4.8883 16.0676 9.3923 -0.1346 3.0364 + 4.7944 15.9616 13.1566 -0.1564 2.9781 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 6.321 0.000 0.000 0.000 0.0000 -log_k_JCZ38 0.000 1.392 0.000 0.000 0.0000 -log_k_J9Z38 0.000 0.000 1.561 0.000 0.0000 -log_k_JSE76 0.000 0.000 0.000 3.614 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6339 +cyan_0 7.701 0.000 0.000 0.000 0.0000 +log_k_JCZ38 0.000 1.448 0.000 0.000 0.0000 +log_k_J9Z38 0.000 0.000 1.724 0.000 0.0000 +log_k_JSE76 0.000 0.000 0.000 3.659 0.0000 +f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6356 f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 f_JSE76_qlogis 0.000 0.000 0.000 0.000 0.0000 @@ -4812,11 +4555,11 @@ log_k_JCZ38 0.00 0.00 0.00 0.0000 0.0000 log_k_J9Z38 0.00 0.00 0.00 0.0000 0.0000 log_k_JSE76 0.00 0.00 0.00 0.0000 0.0000 f_cyan_ilr_1 0.00 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 10.41 0.00 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.00 12.24 0.00 0.0000 0.0000 -f_JSE76_qlogis 0.00 0.00 15.13 0.0000 0.0000 -log_alpha 0.00 0.00 0.00 0.3701 0.0000 -log_beta 0.00 0.00 0.00 0.0000 0.5662 +f_cyan_ilr_2 10.32 0.00 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 12.23 0.00 0.0000 0.0000 +f_JSE76_qlogis 0.00 0.00 14.99 0.0000 0.0000 +log_alpha 0.00 0.00 0.00 0.3924 0.0000 +log_beta 0.00 0.00 0.00 0.0000 0.5639 Starting values for error model parameters: a.1 b.1 @@ -4826,76 +4569,76 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2251 2244 -1106 + 2249 2242 -1106 Optimised parameters: - est. lower upper -cyan_0 101.05768 NA NA -log_k_JCZ38 -2.73252 NA NA -log_k_J9Z38 -5.07399 NA NA -log_k_JSE76 -3.52863 NA NA -f_cyan_ilr_1 0.72176 NA NA -f_cyan_ilr_2 1.34610 NA NA -f_JCZ38_qlogis 2.08337 NA NA -f_JSE76_qlogis 1590.31880 NA NA -log_alpha -0.09336 NA NA -log_beta 3.10191 NA NA -a.1 2.08557 1.85439 2.31675 -b.1 0.06998 0.05800 0.08197 -SD.log_k_JCZ38 1.20053 0.43329 1.96777 -SD.log_k_J9Z38 0.85854 0.26708 1.45000 -SD.log_k_JSE76 0.62528 0.16061 1.08995 -SD.f_cyan_ilr_1 0.35190 0.12340 0.58039 -SD.f_cyan_ilr_2 0.85385 0.15391 1.55378 -SD.log_alpha 0.28971 0.08718 0.49225 -SD.log_beta 0.31614 0.05938 0.57290 + 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 Random effects: est. lower upper -SD.log_k_JCZ38 1.2005 0.43329 1.9678 -SD.log_k_J9Z38 0.8585 0.26708 1.4500 -SD.log_k_JSE76 0.6253 0.16061 1.0900 -SD.f_cyan_ilr_1 0.3519 0.12340 0.5804 -SD.f_cyan_ilr_2 0.8538 0.15391 1.5538 -SD.log_alpha 0.2897 0.08718 0.4923 -SD.log_beta 0.3161 0.05938 0.5729 +SD.log_k_JCZ38 1.2171 0.44160 1.9927 +SD.log_k_J9Z38 0.8827 0.27541 1.4900 +SD.log_k_JSE76 0.5945 0.15005 1.0390 +SD.f_cyan_ilr_1 0.3537 0.12409 0.5833 +SD.f_cyan_ilr_2 0.7819 0.18547 1.3782 +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 2.08557 1.854 2.31675 -b.1 0.06998 0.058 0.08197 + est. lower upper +a.1 2.05279 1.85495 2.2506 +b.1 0.07116 0.05912 0.0832 Backtransformed parameters: est. lower upper -cyan_0 1.011e+02 NA NA -k_JCZ38 6.506e-02 NA NA -k_J9Z38 6.257e-03 NA NA -k_JSE76 2.935e-02 NA NA -f_cyan_to_JCZ38 6.776e-01 NA NA -f_cyan_to_J9Z38 2.442e-01 NA NA -f_JCZ38_to_JSE76 8.893e-01 NA NA -f_JSE76_to_JCZ38 1.000e+00 NA NA -alpha 9.109e-01 NA NA -beta 2.224e+01 NA NA +cyan_0 1.012e+02 NA NA +k_JCZ38 5.763e-02 NA NA +k_J9Z38 6.237e-03 NA NA +k_JSE76 2.916e-02 NA NA +f_cyan_to_JCZ38 6.354e-01 NA NA +f_cyan_to_J9Z38 2.447e-01 NA NA +f_JCZ38_to_JSE76 1.000e+00 NA NA +f_JSE76_to_JCZ38 8.829e-01 NA NA +alpha 8.955e-01 NA NA +beta 2.145e+01 NA NA Resulting formation fractions: - ff -cyan_JCZ38 0.67761 -cyan_J9Z38 0.24417 -cyan_sink 0.07822 -JCZ38_JSE76 0.88928 -JCZ38_sink 0.11072 -JSE76_JCZ38 1.00000 -JSE76_sink 0.00000 + ff +cyan_JCZ38 0.6354 +cyan_J9Z38 0.2447 +cyan_sink 0.1200 +JCZ38_JSE76 1.0000 +JCZ38_sink 0.0000 +JSE76_JCZ38 0.8829 +JSE76_sink 0.1171 Estimated disappearance times: DT50 DT90 DT50back -cyan 25.36 256.37 77.18 -JCZ38 10.65 35.39 NA -J9Z38 110.77 367.98 NA -JSE76 23.62 78.47 NA +cyan 25.07 259.21 78.03 +JCZ38 12.03 39.96 NA +J9Z38 111.14 369.19 NA +JSE76 23.77 78.98 NA </code></pre> <p></p> @@ -4904,11 +4647,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:13:38 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:12:27 2025 +Date of summary: Sun Feb 16 17:03:41 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -4928,25 +4671,25 @@ Data: Model predictions using solution type deSolve -Fitted in 904.25 s +Fitted in 859.906 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 102.4358 -2.3107 -5.3123 -3.7120 0.6753 + 102.4380 -2.3107 -5.3123 -3.7120 0.6757 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 - 1.1462 12.4095 12.3630 -1.9317 -4.4557 + 1.1439 13.1194 12.3492 -1.9317 -4.4557 g_qlogis - -0.5648 + -0.5644 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 4.594 0.0000 0.000 0.0 0.0000 +cyan_0 4.591 0.0000 0.000 0.0 0.0000 log_k_JCZ38 0.000 0.7966 0.000 0.0 0.0000 log_k_J9Z38 0.000 0.0000 1.561 0.0 0.0000 log_k_JSE76 0.000 0.0000 0.000 0.8 0.0000 @@ -4958,17 +4701,17 @@ log_k1 0.000 0.0000 0.000 0.0 0.0000 log_k2 0.000 0.0000 0.000 0.0 0.0000 g_qlogis 0.000 0.0000 0.000 0.0 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 -cyan_0 0.000 0.00 0.0 0.000 0.0000 -log_k_JCZ38 0.000 0.00 0.0 0.000 0.0000 -log_k_J9Z38 0.000 0.00 0.0 0.000 0.0000 -log_k_JSE76 0.000 0.00 0.0 0.000 0.0000 -f_cyan_ilr_1 0.000 0.00 0.0 0.000 0.0000 -f_cyan_ilr_2 1.797 0.00 0.0 0.000 0.0000 -f_JCZ38_qlogis 0.000 13.85 0.0 0.000 0.0000 -f_JSE76_qlogis 0.000 0.00 14.1 0.000 0.0000 -log_k1 0.000 0.00 0.0 1.106 0.0000 -log_k2 0.000 0.00 0.0 0.000 0.6141 -g_qlogis 0.000 0.00 0.0 0.000 0.0000 +cyan_0 0.000 0.00 0.00 0.000 0.0000 +log_k_JCZ38 0.000 0.00 0.00 0.000 0.0000 +log_k_J9Z38 0.000 0.00 0.00 0.000 0.0000 +log_k_JSE76 0.000 0.00 0.00 0.000 0.0000 +f_cyan_ilr_1 0.000 0.00 0.00 0.000 0.0000 +f_cyan_ilr_2 1.797 0.00 0.00 0.000 0.0000 +f_JCZ38_qlogis 0.000 13.86 0.00 0.000 0.0000 +f_JSE76_qlogis 0.000 0.00 13.91 0.000 0.0000 +log_k1 0.000 0.00 0.00 1.106 0.0000 +log_k2 0.000 0.00 0.00 0.000 0.6141 +g_qlogis 0.000 0.00 0.00 0.000 0.0000 g_qlogis cyan_0 0.000 log_k_JCZ38 0.000 @@ -4994,74 +4737,74 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -cyan_0 102.5254 NA NA -log_k_JCZ38 -2.9358 NA NA -log_k_J9Z38 -5.1424 NA NA -log_k_JSE76 -3.6458 NA NA -f_cyan_ilr_1 0.6957 NA NA -f_cyan_ilr_2 0.6635 NA NA -f_JCZ38_qlogis 4984.8163 NA NA -f_JSE76_qlogis 1.9415 NA NA -log_k1 -1.9456 NA NA -log_k2 -4.4705 NA NA -g_qlogis -0.5117 NA NA -a.1 2.7455 2.55392 2.9370 -SD.log_k_JCZ38 1.3163 0.47635 2.1563 -SD.log_k_J9Z38 0.7162 0.16133 1.2711 -SD.log_k_JSE76 0.6457 0.15249 1.1390 -SD.f_cyan_ilr_1 0.3424 0.11714 0.5677 -SD.f_cyan_ilr_2 0.4524 0.09709 0.8077 -SD.log_k1 0.7353 0.25445 1.2161 -SD.log_k2 0.5137 0.18206 0.8453 -SD.g_qlogis 0.9857 0.35651 1.6148 +cyan_0 102.6036 NA NA +log_k_JCZ38 -2.9348 NA NA +log_k_J9Z38 -5.1617 NA NA +log_k_JSE76 -3.6396 NA NA +f_cyan_ilr_1 0.6991 NA NA +f_cyan_ilr_2 0.6341 NA NA +f_JCZ38_qlogis 4232.3011 NA NA +f_JSE76_qlogis 1.9658 NA NA +log_k1 -1.9503 NA NA +log_k2 -4.4745 NA NA +g_qlogis -0.4967 NA NA +a.1 2.7461 2.59274 2.8994 +SD.log_k_JCZ38 1.3178 0.47602 2.1596 +SD.log_k_J9Z38 0.7022 0.15061 1.2538 +SD.log_k_JSE76 0.6566 0.15613 1.1570 +SD.f_cyan_ilr_1 0.3409 0.11666 0.5652 +SD.f_cyan_ilr_2 0.4385 0.09482 0.7821 +SD.log_k1 0.7381 0.25599 1.2202 +SD.log_k2 0.5133 0.18152 0.8450 +SD.g_qlogis 0.9866 0.35681 1.6164 Correlation is not available Random effects: est. lower upper -SD.log_k_JCZ38 1.3163 0.47635 2.1563 -SD.log_k_J9Z38 0.7162 0.16133 1.2711 -SD.log_k_JSE76 0.6457 0.15249 1.1390 -SD.f_cyan_ilr_1 0.3424 0.11714 0.5677 -SD.f_cyan_ilr_2 0.4524 0.09709 0.8077 -SD.log_k1 0.7353 0.25445 1.2161 -SD.log_k2 0.5137 0.18206 0.8453 -SD.g_qlogis 0.9857 0.35651 1.6148 +SD.log_k_JCZ38 1.3178 0.47602 2.1596 +SD.log_k_J9Z38 0.7022 0.15061 1.2538 +SD.log_k_JSE76 0.6566 0.15613 1.1570 +SD.f_cyan_ilr_1 0.3409 0.11666 0.5652 +SD.f_cyan_ilr_2 0.4385 0.09482 0.7821 +SD.log_k1 0.7381 0.25599 1.2202 +SD.log_k2 0.5133 0.18152 0.8450 +SD.g_qlogis 0.9866 0.35681 1.6164 Variance model: est. lower upper -a.1 2.745 2.554 2.937 +a.1 2.746 2.593 2.899 Backtransformed parameters: est. lower upper -cyan_0 1.025e+02 NA NA -k_JCZ38 5.309e-02 NA NA -k_J9Z38 5.844e-03 NA NA -k_JSE76 2.610e-02 NA NA -f_cyan_to_JCZ38 6.079e-01 NA NA -f_cyan_to_J9Z38 2.272e-01 NA NA +cyan_0 1.026e+02 NA NA +k_JCZ38 5.314e-02 NA NA +k_J9Z38 5.732e-03 NA NA +k_JSE76 2.626e-02 NA NA +f_cyan_to_JCZ38 6.051e-01 NA NA +f_cyan_to_J9Z38 2.251e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA -f_JSE76_to_JCZ38 8.745e-01 NA NA -k1 1.429e-01 NA NA -k2 1.144e-02 NA NA -g 3.748e-01 NA NA +f_JSE76_to_JCZ38 8.772e-01 NA NA +k1 1.422e-01 NA NA +k2 1.140e-02 NA NA +g 3.783e-01 NA NA Resulting formation fractions: ff -cyan_JCZ38 0.6079 -cyan_J9Z38 0.2272 -cyan_sink 0.1649 +cyan_JCZ38 0.6051 +cyan_J9Z38 0.2251 +cyan_sink 0.1698 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 -JSE76_JCZ38 0.8745 -JSE76_sink 0.1255 +JSE76_JCZ38 0.8772 +JSE76_sink 0.1228 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 22.29 160.20 48.22 4.85 60.58 -JCZ38 13.06 43.37 NA NA NA -J9Z38 118.61 394.02 NA NA NA -JSE76 26.56 88.22 NA NA NA +cyan 22.05 160.35 48.27 4.873 60.83 +JCZ38 13.04 43.33 NA NA NA +J9Z38 120.93 401.73 NA NA NA +JSE76 26.39 87.68 NA NA NA </code></pre> <p></p> @@ -5070,11 +4813,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:00 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:12:54 2025 +Date of summary: Sun Feb 16 17:03:41 2025 Equations: d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -5094,59 +4837,59 @@ Data: Model predictions using solution type deSolve -Fitted in 926.094 s +Fitted in 886.298 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 - 101.7523 -1.5948 -5.0119 -2.2723 0.6719 + 101.7393 -1.4493 -5.0118 -2.1269 0.6720 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 - 5.1681 12.8238 12.4130 -2.0057 -4.5526 + 7.3362 13.4423 13.2659 -2.0061 -4.5527 g_qlogis - -0.5805 + -0.5806 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1 -cyan_0 5.627 0.000 0.000 0.000 0.0000 -log_k_JCZ38 0.000 2.327 0.000 0.000 0.0000 -log_k_J9Z38 0.000 0.000 1.664 0.000 0.0000 -log_k_JSE76 0.000 0.000 0.000 4.566 0.0000 -f_cyan_ilr_1 0.000 0.000 0.000 0.000 0.6519 -f_cyan_ilr_2 0.000 0.000 0.000 0.000 0.0000 -f_JCZ38_qlogis 0.000 0.000 0.000 0.000 0.0000 -f_JSE76_qlogis 0.000 0.000 0.000 0.000 0.0000 -log_k1 0.000 0.000 0.000 0.000 0.0000 -log_k2 0.000 0.000 0.000 0.000 0.0000 -g_qlogis 0.000 0.000 0.000 0.000 0.0000 +cyan_0 5.604 0.00 0.000 0.000 0.0000 +log_k_JCZ38 0.000 2.77 0.000 0.000 0.0000 +log_k_J9Z38 0.000 0.00 1.662 0.000 0.0000 +log_k_JSE76 0.000 0.00 0.000 5.021 0.0000 +f_cyan_ilr_1 0.000 0.00 0.000 0.000 0.6519 +f_cyan_ilr_2 0.000 0.00 0.000 0.000 0.0000 +f_JCZ38_qlogis 0.000 0.00 0.000 0.000 0.0000 +f_JSE76_qlogis 0.000 0.00 0.000 0.000 0.0000 +log_k1 0.000 0.00 0.000 0.000 0.0000 +log_k2 0.000 0.00 0.000 0.000 0.0000 +g_qlogis 0.000 0.00 0.000 0.000 0.0000 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2 -cyan_0 0.0 0.00 0.00 0.0000 0.0000 -log_k_JCZ38 0.0 0.00 0.00 0.0000 0.0000 -log_k_J9Z38 0.0 0.00 0.00 0.0000 0.0000 -log_k_JSE76 0.0 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_1 0.0 0.00 0.00 0.0000 0.0000 -f_cyan_ilr_2 10.1 0.00 0.00 0.0000 0.0000 -f_JCZ38_qlogis 0.0 13.99 0.00 0.0000 0.0000 -f_JSE76_qlogis 0.0 0.00 14.15 0.0000 0.0000 -log_k1 0.0 0.00 0.00 0.8452 0.0000 -log_k2 0.0 0.00 0.00 0.0000 0.5968 -g_qlogis 0.0 0.00 0.00 0.0000 0.0000 +cyan_0 0.00 0.00 0.00 0.0000 0.0000 +log_k_JCZ38 0.00 0.00 0.00 0.0000 0.0000 +log_k_J9Z38 0.00 0.00 0.00 0.0000 0.0000 +log_k_JSE76 0.00 0.00 0.00 0.0000 0.0000 +f_cyan_ilr_1 0.00 0.00 0.00 0.0000 0.0000 +f_cyan_ilr_2 13.37 0.00 0.00 0.0000 0.0000 +f_JCZ38_qlogis 0.00 14.21 0.00 0.0000 0.0000 +f_JSE76_qlogis 0.00 0.00 14.58 0.0000 0.0000 +log_k1 0.00 0.00 0.00 0.8453 0.0000 +log_k2 0.00 0.00 0.00 0.0000 0.5969 +g_qlogis 0.00 0.00 0.00 0.0000 0.0000 g_qlogis -cyan_0 0.000 -log_k_JCZ38 0.000 -log_k_J9Z38 0.000 -log_k_JSE76 0.000 -f_cyan_ilr_1 0.000 -f_cyan_ilr_2 0.000 -f_JCZ38_qlogis 0.000 -f_JSE76_qlogis 0.000 -log_k1 0.000 -log_k2 0.000 -g_qlogis 1.691 +cyan_0 0.00 +log_k_JCZ38 0.00 +log_k_J9Z38 0.00 +log_k_JSE76 0.00 +f_cyan_ilr_1 0.00 +f_cyan_ilr_2 0.00 +f_JCZ38_qlogis 0.00 +f_JSE76_qlogis 0.00 +log_k1 0.00 +log_k2 0.00 +g_qlogis 1.69 Starting values for error model parameters: a.1 b.1 @@ -5156,78 +4899,78 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2232 2224 -1096 + 2237 2229 -1099 Optimised parameters: est. lower upper -cyan_0 101.20051 NA NA -log_k_JCZ38 -2.93542 NA NA -log_k_J9Z38 -5.03151 NA NA -log_k_JSE76 -3.67679 NA NA -f_cyan_ilr_1 0.67290 NA NA -f_cyan_ilr_2 0.99787 NA NA -f_JCZ38_qlogis 348.32484 NA NA -f_JSE76_qlogis 1.87846 NA NA -log_k1 -2.32738 NA NA -log_k2 -4.61295 NA NA -g_qlogis -0.38342 NA NA -a.1 2.06184 1.83746 2.28622 -b.1 0.06329 0.05211 0.07447 -SD.log_k_JCZ38 1.29042 0.47468 2.10617 -SD.log_k_J9Z38 0.84235 0.25903 1.42566 -SD.log_k_JSE76 0.56930 0.13934 0.99926 -SD.f_cyan_ilr_1 0.35183 0.12298 0.58068 -SD.f_cyan_ilr_2 0.77269 0.17908 1.36631 -SD.log_k2 0.28549 0.09210 0.47888 -SD.g_qlogis 0.93830 0.34568 1.53093 +cyan_0 101.00243 NA NA +log_k_JCZ38 -2.80828 NA NA +log_k_J9Z38 -5.04449 NA NA +log_k_JSE76 -3.66981 NA NA +f_cyan_ilr_1 0.72564 NA NA +f_cyan_ilr_2 1.37978 NA NA +f_JCZ38_qlogis 1.98726 NA NA +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 1.91261 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 1.46739 +SD.log_k2 0.27476 0.08557 0.46394 +SD.g_qlogis 0.96170 0.35463 1.56878 Correlation is not available Random effects: - est. lower upper -SD.log_k_JCZ38 1.2904 0.4747 2.1062 -SD.log_k_J9Z38 0.8423 0.2590 1.4257 -SD.log_k_JSE76 0.5693 0.1393 0.9993 -SD.f_cyan_ilr_1 0.3518 0.1230 0.5807 -SD.f_cyan_ilr_2 0.7727 0.1791 1.3663 -SD.log_k2 0.2855 0.0921 0.4789 -SD.g_qlogis 0.9383 0.3457 1.5309 + est. lower upper +SD.log_k_JCZ38 1.3090 0.48128 2.1367 +SD.log_k_J9Z38 0.8388 0.25790 1.4197 +SD.log_k_JSE76 0.5810 0.14201 1.0201 +SD.f_cyan_ilr_1 0.3542 0.12398 0.5844 +SD.f_cyan_ilr_2 0.7937 0.12007 1.4674 +SD.log_k2 0.2748 0.08557 0.4639 +SD.g_qlogis 0.9617 0.35463 1.5688 Variance model: est. lower upper -a.1 2.06184 1.83746 2.28622 -b.1 0.06329 0.05211 0.07447 +a.1 2.10837 1.91261 2.30413 +b.1 0.06223 0.05085 0.07361 Backtransformed parameters: est. lower upper -cyan_0 1.012e+02 NA NA -k_JCZ38 5.311e-02 NA NA -k_J9Z38 6.529e-03 NA NA -k_JSE76 2.530e-02 NA NA -f_cyan_to_JCZ38 6.373e-01 NA NA -f_cyan_to_J9Z38 2.461e-01 NA NA -f_JCZ38_to_JSE76 1.000e+00 NA NA -f_JSE76_to_JCZ38 8.674e-01 NA NA -k1 9.755e-02 NA NA -k2 9.922e-03 NA NA -g 4.053e-01 NA NA +cyan_0 1.010e+02 NA NA +k_JCZ38 6.031e-02 NA NA +k_J9Z38 6.445e-03 NA NA +k_JSE76 2.548e-02 NA NA +f_cyan_to_JCZ38 6.808e-01 NA NA +f_cyan_to_J9Z38 2.440e-01 NA NA +f_JCZ38_to_JSE76 8.795e-01 NA NA +f_JSE76_to_JCZ38 1.000e+00 NA NA +k1 9.200e-02 NA NA +k2 9.693e-03 NA NA +g 4.160e-01 NA NA Resulting formation fractions: - ff -cyan_JCZ38 0.6373 -cyan_J9Z38 0.2461 -cyan_sink 0.1167 -JCZ38_JSE76 1.0000 -JCZ38_sink 0.0000 -JSE76_JCZ38 0.8674 -JSE76_sink 0.1326 + ff +cyan_JCZ38 0.68081 +cyan_J9Z38 0.24398 +cyan_sink 0.07521 +JCZ38_JSE76 0.87945 +JCZ38_sink 0.12055 +JSE76_JCZ38 1.00000 +JSE76_sink 0.00000 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -cyan 24.93 179.68 54.09 7.105 69.86 -JCZ38 13.05 43.36 NA NA NA -J9Z38 106.16 352.67 NA NA NA -JSE76 27.39 91.00 NA NA NA +cyan 25.00 182.05 54.8 7.535 71.51 +JCZ38 11.49 38.18 NA NA NA +J9Z38 107.55 357.28 NA NA NA +JSE76 27.20 90.36 NA NA NA </code></pre> <p></p> @@ -5236,11 +4979,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:13:34 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:12:32 2025 +Date of summary: Sun Feb 16 17:03:41 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -5258,20 +5001,20 @@ Data: Model predictions using solution type deSolve -Fitted in 900.859 s +Fitted in 865.121 s Using 300, 100 iterations and 10 chains Variance model: Constant variance Starting values for degradation parameters: cyan_free_0 log_k_cyan_free log_k_cyan_free_bound - 102.4394 -2.7673 -2.8942 + 102.4395 -2.7673 -2.8942 log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 -3.6201 -2.3107 -5.3123 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 -3.7120 0.6754 1.1448 f_JCZ38_qlogis f_JSE76_qlogis - 13.2672 13.3538 + 14.8408 15.4734 Fixed degradation parameter values: None @@ -5302,17 +5045,17 @@ f_cyan_ilr_2 0.000 0.0000 0.000 0.0 f_JCZ38_qlogis 0.000 0.0000 0.000 0.0 f_JSE76_qlogis 0.000 0.0000 0.000 0.0 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis -cyan_free_0 0.0000 0.000 0.00 0.00 -log_k_cyan_free 0.0000 0.000 0.00 0.00 -log_k_cyan_free_bound 0.0000 0.000 0.00 0.00 -log_k_cyan_bound_free 0.0000 0.000 0.00 0.00 -log_k_JCZ38 0.0000 0.000 0.00 0.00 -log_k_J9Z38 0.0000 0.000 0.00 0.00 -log_k_JSE76 0.0000 0.000 0.00 0.00 -f_cyan_ilr_1 0.6349 0.000 0.00 0.00 -f_cyan_ilr_2 0.0000 1.797 0.00 0.00 -f_JCZ38_qlogis 0.0000 0.000 13.84 0.00 -f_JSE76_qlogis 0.0000 0.000 0.00 14.66 +cyan_free_0 0.0000 0.000 0.0 0.00 +log_k_cyan_free 0.0000 0.000 0.0 0.00 +log_k_cyan_free_bound 0.0000 0.000 0.0 0.00 +log_k_cyan_bound_free 0.0000 0.000 0.0 0.00 +log_k_JCZ38 0.0000 0.000 0.0 0.00 +log_k_J9Z38 0.0000 0.000 0.0 0.00 +log_k_JSE76 0.0000 0.000 0.0 0.00 +f_cyan_ilr_1 0.6349 0.000 0.0 0.00 +f_cyan_ilr_2 0.0000 1.797 0.0 0.00 +f_JCZ38_qlogis 0.0000 0.000 15.6 0.00 +f_JSE76_qlogis 0.0000 0.000 0.0 17.52 Starting values for error model parameters: a.1 @@ -5322,83 +5065,83 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2279 2272 -1120 + 2280 2272 -1120 Optimised parameters: est. lower upper -cyan_free_0 102.5621 NA NA -log_k_cyan_free -2.8531 NA NA -log_k_cyan_free_bound -2.6916 NA NA -log_k_cyan_bound_free -3.5032 NA NA -log_k_JCZ38 -2.9436 NA NA -log_k_J9Z38 -5.1140 NA NA -log_k_JSE76 -3.6472 NA NA -f_cyan_ilr_1 0.6887 NA NA -f_cyan_ilr_2 0.6874 NA NA -f_JCZ38_qlogis 4063.6389 NA NA -f_JSE76_qlogis 1.9556 NA NA -a.1 2.7460 2.55451 2.9376 -SD.log_k_cyan_free 0.3131 0.09841 0.5277 -SD.log_k_cyan_free_bound 0.8850 0.29909 1.4710 -SD.log_k_cyan_bound_free 0.6167 0.20391 1.0295 -SD.log_k_JCZ38 1.3555 0.49101 2.2200 -SD.log_k_J9Z38 0.7200 0.16166 1.2783 -SD.log_k_JSE76 0.6252 0.14619 1.1042 -SD.f_cyan_ilr_1 0.3386 0.11447 0.5627 -SD.f_cyan_ilr_2 0.4699 0.09810 0.8417 +cyan_free_0 102.6532 NA NA +log_k_cyan_free -2.8547 NA NA +log_k_cyan_free_bound -2.7004 NA NA +log_k_cyan_bound_free -3.5078 NA NA +log_k_JCZ38 -2.9255 NA NA +log_k_J9Z38 -5.1089 NA NA +log_k_JSE76 -3.6263 NA NA +f_cyan_ilr_1 0.6873 NA NA +f_cyan_ilr_2 0.6498 NA NA +f_JCZ38_qlogis 3624.2149 NA NA +f_JSE76_qlogis 1.9991 NA NA +a.1 2.7472 2.55559 2.9388 +SD.log_k_cyan_free 0.3227 0.10296 0.5423 +SD.log_k_cyan_free_bound 0.8757 0.29525 1.4562 +SD.log_k_cyan_bound_free 0.6128 0.20220 1.0233 +SD.log_k_JCZ38 1.3431 0.48474 2.2014 +SD.log_k_J9Z38 0.6881 0.14714 1.2291 +SD.log_k_JSE76 0.6461 0.15321 1.1390 +SD.f_cyan_ilr_1 0.3361 0.11376 0.5585 +SD.f_cyan_ilr_2 0.4286 0.08419 0.7730 Correlation is not available Random effects: est. lower upper -SD.log_k_cyan_free 0.3131 0.09841 0.5277 -SD.log_k_cyan_free_bound 0.8850 0.29909 1.4710 -SD.log_k_cyan_bound_free 0.6167 0.20391 1.0295 -SD.log_k_JCZ38 1.3555 0.49101 2.2200 -SD.log_k_J9Z38 0.7200 0.16166 1.2783 -SD.log_k_JSE76 0.6252 0.14619 1.1042 -SD.f_cyan_ilr_1 0.3386 0.11447 0.5627 -SD.f_cyan_ilr_2 0.4699 0.09810 0.8417 +SD.log_k_cyan_free 0.3227 0.10296 0.5423 +SD.log_k_cyan_free_bound 0.8757 0.29525 1.4562 +SD.log_k_cyan_bound_free 0.6128 0.20220 1.0233 +SD.log_k_JCZ38 1.3431 0.48474 2.2014 +SD.log_k_J9Z38 0.6881 0.14714 1.2291 +SD.log_k_JSE76 0.6461 0.15321 1.1390 +SD.f_cyan_ilr_1 0.3361 0.11376 0.5585 +SD.f_cyan_ilr_2 0.4286 0.08419 0.7730 Variance model: est. lower upper -a.1 2.746 2.555 2.938 +a.1 2.747 2.556 2.939 Backtransformed parameters: est. lower upper -cyan_free_0 1.026e+02 NA NA -k_cyan_free 5.767e-02 NA NA -k_cyan_free_bound 6.777e-02 NA NA -k_cyan_bound_free 3.010e-02 NA NA -k_JCZ38 5.267e-02 NA NA -k_J9Z38 6.012e-03 NA NA -k_JSE76 2.606e-02 NA NA -f_cyan_free_to_JCZ38 6.089e-01 NA NA -f_cyan_free_to_J9Z38 2.299e-01 NA NA +cyan_free_0 1.027e+02 NA NA +k_cyan_free 5.758e-02 NA NA +k_cyan_free_bound 6.718e-02 NA NA +k_cyan_bound_free 2.996e-02 NA NA +k_JCZ38 5.364e-02 NA NA +k_J9Z38 6.042e-03 NA NA +k_JSE76 2.662e-02 NA NA +f_cyan_free_to_JCZ38 6.039e-01 NA NA +f_cyan_free_to_J9Z38 2.285e-01 NA NA f_JCZ38_to_JSE76 1.000e+00 NA NA -f_JSE76_to_JCZ38 8.761e-01 NA NA +f_JSE76_to_JCZ38 8.807e-01 NA NA Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g - 0.1434 0.0121 0.3469 + 0.1426 0.0121 0.3484 Resulting formation fractions: ff -cyan_free_JCZ38 0.6089 -cyan_free_J9Z38 0.2299 -cyan_free_sink 0.1612 +cyan_free_JCZ38 0.6039 +cyan_free_J9Z38 0.2285 +cyan_free_sink 0.1676 cyan_free 1.0000 JCZ38_JSE76 1.0000 JCZ38_sink 0.0000 -JSE76_JCZ38 0.8761 -JSE76_sink 0.1239 +JSE76_JCZ38 0.8807 +JSE76_sink 0.1193 Estimated disappearance times: DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 23.94 155.06 46.68 4.832 57.28 -JCZ38 13.16 43.71 NA NA NA -J9Z38 115.30 383.02 NA NA NA -JSE76 26.59 88.35 NA NA NA +cyan 23.84 154.95 46.65 4.86 57.31 +JCZ38 12.92 42.93 NA NA NA +J9Z38 114.71 381.07 NA NA NA +JSE76 26.04 86.51 NA NA NA </code></pre> <p></p> @@ -5407,11 +5150,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:13:37 2023 -Date of summary: Fri May 19 18:14:01 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:12:36 2025 +Date of summary: Sun Feb 16 17:03:41 2025 Equations: d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound * @@ -5429,20 +5172,20 @@ Data: Model predictions using solution type deSolve -Fitted in 903.326 s +Fitted in 868.952 s Using 300, 100 iterations and 10 chains Variance model: Two-component variance function Starting values for degradation parameters: cyan_free_0 log_k_cyan_free log_k_cyan_free_bound - 101.751 -2.837 -3.016 + 101.7511 -2.8370 -3.0162 log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 - -3.660 -2.299 -5.313 + -3.6600 -2.2988 -5.3129 log_k_JSE76 f_cyan_ilr_1 f_cyan_ilr_2 - -3.699 0.672 5.873 + -3.6991 0.6722 4.8596 f_JCZ38_qlogis f_JSE76_qlogis - 13.216 13.338 + 13.4678 14.2149 Fixed degradation parameter values: None @@ -5473,17 +5216,17 @@ f_cyan_ilr_2 0.000 0.0000 0.000 0.0000 f_JCZ38_qlogis 0.000 0.0000 0.000 0.0000 f_JSE76_qlogis 0.000 0.0000 0.000 0.0000 f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis -cyan_free_0 0.0000 0.00 0.00 0.00 -log_k_cyan_free 0.0000 0.00 0.00 0.00 -log_k_cyan_free_bound 0.0000 0.00 0.00 0.00 -log_k_cyan_bound_free 0.0000 0.00 0.00 0.00 -log_k_JCZ38 0.0000 0.00 0.00 0.00 -log_k_J9Z38 0.0000 0.00 0.00 0.00 -log_k_JSE76 0.0000 0.00 0.00 0.00 -f_cyan_ilr_1 0.6519 0.00 0.00 0.00 -f_cyan_ilr_2 0.0000 10.78 0.00 0.00 -f_JCZ38_qlogis 0.0000 0.00 13.96 0.00 -f_JSE76_qlogis 0.0000 0.00 0.00 14.69 +cyan_free_0 0.0000 0.000 0.00 0.00 +log_k_cyan_free 0.0000 0.000 0.00 0.00 +log_k_cyan_free_bound 0.0000 0.000 0.00 0.00 +log_k_cyan_bound_free 0.0000 0.000 0.00 0.00 +log_k_JCZ38 0.0000 0.000 0.00 0.00 +log_k_J9Z38 0.0000 0.000 0.00 0.00 +log_k_JSE76 0.0000 0.000 0.00 0.00 +f_cyan_ilr_1 0.6518 0.000 0.00 0.00 +f_cyan_ilr_2 0.0000 9.981 0.00 0.00 +f_JCZ38_qlogis 0.0000 0.000 14.26 0.00 +f_JSE76_qlogis 0.0000 0.000 0.00 16.17 Starting values for error model parameters: a.1 b.1 @@ -5493,83 +5236,83 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 2236 2228 -1098 + 2241 2233 -1101 Optimised parameters: est. lower upper -cyan_free_0 100.72760 NA NA -log_k_cyan_free -3.18281 NA NA -log_k_cyan_free_bound -3.37924 NA NA -log_k_cyan_bound_free -3.77107 NA NA -log_k_JCZ38 -2.92811 NA NA -log_k_J9Z38 -5.02759 NA NA -log_k_JSE76 -3.65835 NA NA -f_cyan_ilr_1 0.67390 NA NA -f_cyan_ilr_2 1.15106 NA NA -f_JCZ38_qlogis 827.82299 NA NA -f_JSE76_qlogis 1.83064 NA NA -a.1 2.06921 1.84443 2.29399 -b.1 0.06391 0.05267 0.07515 -SD.log_k_cyan_free 0.50518 0.18962 0.82075 -SD.log_k_cyan_bound_free 0.30991 0.08170 0.53813 -SD.log_k_JCZ38 1.26661 0.46578 2.06744 -SD.log_k_J9Z38 0.88272 0.27813 1.48730 -SD.log_k_JSE76 0.53050 0.12561 0.93538 -SD.f_cyan_ilr_1 0.35547 0.12461 0.58633 -SD.f_cyan_ilr_2 0.91446 0.20131 1.62761 +cyan_free_0 100.95469 NA NA +log_k_cyan_free -3.18706 NA NA +log_k_cyan_free_bound -3.38455 NA NA +log_k_cyan_bound_free -3.75788 NA NA +log_k_JCZ38 -2.77024 NA NA +log_k_J9Z38 -5.03665 NA NA +log_k_JSE76 -3.60289 NA NA +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 1.91479 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 +SD.log_k_J9Z38 0.86833 0.27222 1.46444 +SD.log_k_JSE76 0.59325 0.14711 1.03940 +SD.f_cyan_ilr_1 0.35705 0.12521 0.58890 +SD.f_cyan_ilr_2 0.88541 0.13797 1.63286 Correlation is not available Random effects: - est. lower upper -SD.log_k_cyan_free 0.5052 0.1896 0.8207 -SD.log_k_cyan_bound_free 0.3099 0.0817 0.5381 -SD.log_k_JCZ38 1.2666 0.4658 2.0674 -SD.log_k_J9Z38 0.8827 0.2781 1.4873 -SD.log_k_JSE76 0.5305 0.1256 0.9354 -SD.f_cyan_ilr_1 0.3555 0.1246 0.5863 -SD.f_cyan_ilr_2 0.9145 0.2013 1.6276 + est. lower upper +SD.log_k_cyan_free 0.5010 0.18805 0.8139 +SD.log_k_cyan_bound_free 0.3167 0.08467 0.5487 +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 +SD.f_cyan_ilr_1 0.3571 0.12521 0.5889 +SD.f_cyan_ilr_2 0.8854 0.13797 1.6329 Variance model: est. lower upper -a.1 2.06921 1.84443 2.29399 -b.1 0.06391 0.05267 0.07515 +a.1 2.11130 1.91479 2.30780 +b.1 0.06299 0.05152 0.07445 Backtransformed parameters: est. lower upper -cyan_free_0 1.007e+02 NA NA -k_cyan_free 4.147e-02 NA NA -k_cyan_free_bound 3.407e-02 NA NA -k_cyan_bound_free 2.303e-02 NA NA -k_JCZ38 5.350e-02 NA NA -k_J9Z38 6.555e-03 NA NA -k_JSE76 2.578e-02 NA NA -f_cyan_free_to_JCZ38 6.505e-01 NA NA -f_cyan_free_to_J9Z38 2.508e-01 NA NA -f_JCZ38_to_JSE76 1.000e+00 NA NA -f_JSE76_to_JCZ38 8.618e-01 NA NA +cyan_free_0 1.010e+02 NA NA +k_cyan_free 4.129e-02 NA NA +k_cyan_free_bound 3.389e-02 NA NA +k_cyan_bound_free 2.333e-02 NA NA +k_JCZ38 6.265e-02 NA NA +k_J9Z38 6.495e-03 NA NA +k_JSE76 2.724e-02 NA NA +f_cyan_free_to_JCZ38 6.844e-01 NA NA +f_cyan_free_to_J9Z38 2.463e-01 NA NA +f_JCZ38_to_JSE76 8.816e-01 NA NA +f_JSE76_to_JCZ38 1.000e+00 NA NA Estimated Eigenvalues of SFORB model(s): cyan_b1 cyan_b2 cyan_g -0.08768 0.01089 0.39821 +0.08751 0.01101 0.39586 Resulting formation fractions: ff -cyan_free_JCZ38 0.65053 -cyan_free_J9Z38 0.25082 -cyan_free_sink 0.09864 +cyan_free_JCZ38 0.68444 +cyan_free_J9Z38 0.24633 +cyan_free_sink 0.06923 cyan_free 1.00000 -JCZ38_JSE76 1.00000 -JCZ38_sink 0.00000 -JSE76_JCZ38 0.86184 -JSE76_sink 0.13816 +JCZ38_JSE76 0.88161 +JCZ38_sink 0.11839 +JSE76_JCZ38 1.00000 +JSE76_sink 0.00000 Estimated disappearance times: DT50 DT90 DT50back DT50_cyan_b1 DT50_cyan_b2 -cyan 25.32 164.79 49.61 7.906 63.64 -JCZ38 12.96 43.04 NA NA NA -J9Z38 105.75 351.29 NA NA NA -JSE76 26.89 89.33 NA NA NA +cyan 25.36 163.36 49.18 7.921 62.95 +JCZ38 11.06 36.75 NA NA NA +J9Z38 106.71 354.49 NA NA NA +JSE76 25.44 84.51 NA NA NA </code></pre> <p></p> @@ -5578,13 +5321,13 @@ JSE76 26.89 89.33 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 4.3.0 (2023-04-21) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.4.2 (2024-10-31) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default -BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 -LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so; LAPACK version 3.11.0 +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 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -5602,63 +5345,50 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.5 +[1] saemix_3.3 npde_3.5 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_4.3.0 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_4.3.0 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] 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_3.1-162 rmarkdown_2.21 compiler_4.3.0 prettyunits_1.1.1 -[65] readxl_1.4.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.8.9 dplyr_1.1.4 compiler_4.4.2 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.1.0 + [9] scales_1.3.0 textshaping_0.4.1 yaml_2.3.10 fastmap_1.2.0 +[13] lattice_0.22-6 ggplot2_3.5.1 R6_2.5.1 generics_0.1.3 +[17] lmtest_0.9-40 MASS_7.3-61 htmlwidgets_1.6.4 tibble_3.2.1 +[21] desc_1.4.3 munsell_0.5.1 bslib_0.8.0 pillar_1.9.0 +[25] rlang_1.1.4 utf8_1.2.4 inline_0.3.20 cachem_1.1.0 +[29] xfun_0.49 fs_1.6.5 sass_0.4.9 cli_3.6.3 +[33] pkgdown_2.1.1 magrittr_2.0.3 digest_0.6.37 grid_4.4.2 +[37] mclust_6.1.1 lifecycle_1.0.4 nlme_3.1-166 vctrs_0.6.5 +[41] evaluate_1.0.1 glue_1.8.0 ragg_1.3.3 zoo_1.8-12 +[45] fansi_1.0.6 colorspace_2.1-1 rmarkdown_2.29 pkgconfig_2.0.3 +[49] tools_4.4.2 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: 64925476 kB</code></pre> +<pre><code>MemTotal: 64927788 kB</code></pre> </div> </div> - </div> - - <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - - <nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2> - </nav> -</div> - + </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="copyright"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <footer><div class="pkgdown-footer-left"> + <p>Developed by Johannes Ranke.</p> </div> -<div class="pkgdown"> - <p></p> -<p>Site built with <a 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- <div class="col-md-9 contents"> - <div class="page-header toc-ignore"> - <h1 data-toc-skip>Testing hierarchical parent degradation kinetics -with residue data on dimethenamid and dimethenamid-P</h1> +<div class="row"> + <main id="main" class="col-md-9"><div class="page-header"> + + <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 19 Mai 2023</h4> +2023, last compiled on 16 Februar 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="hidden name"><code>2022_dmta_parent.rmd</code></div> - + <div class="d-none name"><code>2022_dmta_parent.rmd</code></div> </div> @@ -155,7 +103,7 @@ 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 1.2.5. 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> @@ -1006,7 +954,7 @@ updated assuming two-component error.</p> <td align="left">DFOP</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> @@ -1014,7 +962,7 @@ updated assuming two-component error.</p> <tr class="even"> <td align="left">HS</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> @@ -1112,9 +1060,9 @@ the best fits.</p> <tr class="even"> <td align="left">FOMC tc</td> <td align="right">8</td> -<td align="right">720.4</td> -<td align="right">718.8</td> -<td align="right">-352.2</td> +<td align="right">720.7</td> +<td align="right">719.1</td> +<td align="right">-352.4</td> </tr> <tr class="odd"> <td align="left">DFOP const</td> @@ -1133,9 +1081,9 @@ the best fits.</p> <tr class="odd"> <td align="left">DFOP tc</td> <td align="right">10</td> -<td align="right">665.5</td> -<td align="right">663.4</td> -<td align="right">-322.8</td> +<td align="right">665.7</td> +<td align="right">663.6</td> +<td align="right">-322.9</td> </tr> <tr class="even"> <td align="left">HS tc</td> @@ -1216,12 +1164,12 @@ achieved with the argument <code>test = TRUE</code> to the <span> <span class="fu"><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">kable</a></span><span class="op">(</span>format.args <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>digits <span class="op">=</span> <span class="fl">4</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> <table class="table"> <colgroup> -<col width="37%"> -<col width="6%"> +<col width="38%"> +<col width="7%"> <col width="8%"> <col width="8%"> <col width="9%"> -<col width="9%"> +<col width="8%"> <col width="4%"> <col width="15%"> </colgroup> @@ -1239,8 +1187,8 @@ achieved with the argument <code>test = TRUE</code> to the <tr class="odd"> <td align="left">f_saem_dfop_tc_no_ranef_k2</td> <td align="right">9</td> -<td align="right">663.8</td> -<td align="right">661.9</td> +<td align="right">663.7</td> +<td align="right">661.8</td> <td align="right">-322.9</td> <td align="right">NA</td> <td align="right">NA</td> @@ -1249,12 +1197,12 @@ achieved with the argument <code>test = TRUE</code> to the <tr class="even"> <td align="left">f_saem[[“DFOP”, “tc”]]</td> <td align="right">10</td> -<td align="right">665.5</td> -<td align="right">663.4</td> -<td align="right">-322.8</td> -<td align="right">0.2809</td> +<td align="right">665.7</td> +<td align="right">663.6</td> +<td align="right">-322.9</td> +<td align="right">0</td> +<td align="right">1</td> <td align="right">1</td> -<td align="right">0.5961</td> </tr> </tbody> </table> @@ -1286,11 +1234,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:27 2023 -Date of summary: Fri May 19 18:14:28 2023 +<pre><code>saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:19 2025 +Date of summary: Fri Feb 14 08:13:19 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1302,21 +1250,21 @@ Data: Model predictions using solution type analytical -Fitted in 4.477 s +Fitted in 4.154 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function Starting values for degradation parameters: - DMTA_0 k1 k2 g -98.759266 0.087034 0.009933 0.930827 + DMTA_0 k1 k2 g +98.71186 0.08675 0.01374 0.93491 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): DMTA_0 k1 k2 g -DMTA_0 98.76 0 0 0 +DMTA_0 98.71 0 0 0 k1 0.00 1 0 0 k2 0.00 0 1 0 g 0.00 0 0 1 @@ -1329,40 +1277,40 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 663.8 661.9 -322.9 + 663.7 661.8 -322.9 Optimised parameters: est. lower upper -DMTA_0 98.228939 96.285869 100.17201 -k1 0.064063 0.033477 0.09465 -k2 0.008297 0.005824 0.01077 -g 0.953821 0.914328 0.99331 -a.1 1.068479 0.869538 1.26742 -b.1 0.029424 0.022406 0.03644 -SD.DMTA_0 2.030437 0.404824 3.65605 -SD.k1 0.594692 0.256660 0.93272 -SD.g 1.006754 0.361327 1.65218 +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 0.878608 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 0.360061 1.67332 Correlation: DMTA_0 k1 k2 -k1 0.0218 -k2 0.0556 0.0355 -g -0.0516 -0.0284 -0.2800 +k1 0.0213 +k2 0.0541 0.0344 +g -0.0521 -0.0286 -0.2744 Random effects: est. lower upper -SD.DMTA_0 2.0304 0.4048 3.6560 -SD.k1 0.5947 0.2567 0.9327 -SD.g 1.0068 0.3613 1.6522 +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 1.06848 0.86954 1.26742 -b.1 0.02942 0.02241 0.03644 +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 -DMTA 11.45 41.4 12.46 10.82 83.54</code></pre> + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.45 41.32 12.44 10.82 81.85</code></pre> </div> <div class="section level3"> <h3 id="alternative-check-of-parameter-identifiability">Alternative check of parameter identifiability<a class="anchor" aria-label="anchor" href="#alternative-check-of-parameter-identifiability"></a> @@ -1462,11 +1410,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:19 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:11 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1476,7 +1424,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.091 s +Fitted in 0.869 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1534,11 +1482,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:21 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:13 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1548,7 +1496,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.517 s +Fitted in 2.423 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1576,13 +1524,13 @@ 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 @@ -1590,13 +1538,13 @@ 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 @@ -1608,11 +1556,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:20 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:11 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1622,7 +1570,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.25 s +Fitted in 1.228 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1654,7 +1602,7 @@ Optimised parameters: est. lower upper DMTA_0 98.3435 96.9033 99.784 alpha 7.2007 2.5889 11.812 -beta 112.8746 34.8816 190.868 +beta 112.8745 34.8816 190.867 a.1 2.0459 1.8054 2.286 SD.DMTA_0 1.4795 0.2717 2.687 SD.alpha 0.6396 0.1509 1.128 @@ -1685,11 +1633,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:21 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:13 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1699,7 +1647,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.666 s +Fitted in 2.87 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1725,38 +1673,38 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 720.4 718.8 -352.2 + 720.7 719.1 -352.4 Optimised parameters: est. lower upper -DMTA_0 98.99136 97.26011 100.72261 -alpha 5.86312 2.57485 9.15138 -beta 88.55571 29.20889 147.90254 -a.1 1.51063 1.24384 1.77741 -b.1 0.02824 0.02040 0.03609 -SD.DMTA_0 1.57436 -0.04867 3.19739 -SD.alpha 0.59871 0.17132 1.02611 -SD.beta 0.72994 0.22849 1.23139 +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 1.25801 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 1.15302 Correlation: DMTA_0 alpha -alpha -0.1363 -beta -0.1414 0.2542 +alpha -0.1321 +beta -0.1430 0.2467 Random effects: - est. lower upper -SD.DMTA_0 1.5744 -0.04867 3.197 -SD.alpha 0.5987 0.17132 1.026 -SD.beta 0.7299 0.22849 1.231 + est. lower upper +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 1.51063 1.2438 1.77741 -b.1 0.02824 0.0204 0.03609 + est. lower upper +a.1 1.50219 1.25801 1.74636 +b.1 0.02893 0.02048 0.03739 Estimated disappearance times: - DT50 DT90 DT50back -DMTA 11.11 42.6 12.82 + DT50 DT90 DT50back +DMTA 11.05 42.81 12.89 </code></pre> <p></p> @@ -1764,11 +1712,11 @@ DMTA 11.11 42.6 12.82 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:20 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:12 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1780,7 +1728,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.639 s +Fitted in 1.843 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1811,10 +1759,10 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -DMTA_0 98.092481 96.573898 99.61106 +DMTA_0 98.092481 96.573899 99.61106 k1 0.062499 0.030336 0.09466 k2 0.009065 -0.005133 0.02326 -g 0.948967 0.862079 1.03586 +g 0.948967 0.862080 1.03586 a.1 1.821671 1.604774 2.03857 SD.DMTA_0 1.677785 0.472066 2.88350 SD.k1 0.634962 0.270788 0.99914 @@ -1848,11 +1796,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:22 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:14 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1864,21 +1812,21 @@ Data: Model predictions using solution type analytical -Fitted in 3.435 s +Fitted in 3.469 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function Starting values for degradation parameters: - DMTA_0 k1 k2 g -98.759266 0.087034 0.009933 0.930827 + DMTA_0 k1 k2 g +98.71186 0.08675 0.01374 0.93491 Fixed degradation parameter values: None Starting values for random effects (square root of initial entries in omega): DMTA_0 k1 k2 g -DMTA_0 98.76 0 0 0 +DMTA_0 98.71 0 0 0 k1 0.00 1 0 0 k2 0.00 0 1 0 g 0.00 0 0 1 @@ -1891,42 +1839,42 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 665.5 663.4 -322.8 + 665.7 663.6 -322.9 Optimised parameters: est. lower upper -DMTA_0 98.377019 96.447952 100.30609 -k1 0.064843 0.034607 0.09508 -k2 0.008895 0.006368 0.01142 -g 0.949696 0.903815 0.99558 -a.1 1.065241 0.865754 1.26473 -b.1 0.029340 0.022336 0.03634 -SD.DMTA_0 2.007754 0.387982 3.62753 -SD.k1 0.580473 0.250286 0.91066 -SD.k2 0.006105 -4.920337 4.93255 -SD.g 1.097149 0.412779 1.78152 +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 0.883665 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 -7.831228 7.83956 +SD.g 1.064450 0.397479 1.73142 Correlation: DMTA_0 k1 k2 -k1 0.0235 -k2 0.0595 0.0424 -g -0.0470 -0.0278 -0.2731 +k1 0.0223 +k2 0.0568 0.0394 +g -0.0464 -0.0269 -0.2713 Random effects: est. lower upper -SD.DMTA_0 2.007754 0.3880 3.6275 -SD.k1 0.580473 0.2503 0.9107 -SD.k2 0.006105 -4.9203 4.9325 -SD.g 1.097149 0.4128 1.7815 +SD.DMTA_0 2.065796 0.4280 3.7036 +SD.k1 0.583703 0.2518 0.9156 +SD.k2 0.004167 -7.8312 7.8396 +SD.g 1.064450 0.3975 1.7314 Variance model: est. lower upper -a.1 1.06524 0.86575 1.26473 -b.1 0.02934 0.02234 0.03634 +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 -DMTA 11.36 41.32 12.44 10.69 77.92 +DMTA 11.39 41.36 12.45 10.74 83.48 </code></pre> <p></p> @@ -1934,11 +1882,11 @@ DMTA 11.36 41.32 12.44 10.69 77.92 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:20 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:12 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -1948,7 +1896,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.946 s +Fitted in 1.698 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -2016,11 +1964,11 @@ 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: 1.2.5 -R version used for fitting: 4.3.0 -Date of fit: Fri May 19 18:14:22 2023 -Date of summary: Fri May 19 18:15:34 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.4.2 +Date of fit: Fri Feb 14 08:13:13 2025 +Date of summary: Fri Feb 14 08:14:22 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -2030,7 +1978,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.626 s +Fitted in 3.307 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -2061,16 +2009,16 @@ Likelihood computed by importance sampling Optimised parameters: est. lower upper -DMTA_0 97.76570 95.81350 99.71791 +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 @@ -2080,15 +2028,15 @@ 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 @@ -2144,13 +2092,13 @@ 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 4.3.0 (2023-04-21) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.4.2 (2024-10-31) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default -BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 -LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so; LAPACK version 3.11.0 +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 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -2168,60 +2116,51 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.5 +[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_4.3.0 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_4.3.0 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 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 highr_0.10 xfun_0.39 -[49] tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 htmltools_0.5.5 -[53] nlme_3.1-162 rmarkdown_2.21 compiler_4.3.0 </code></pre> + [1] gtable_0.3.6 jsonlite_1.8.9 dplyr_1.1.4 compiler_4.4.2 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.1.0 + [9] scales_1.3.0 textshaping_0.4.1 yaml_2.3.10 fastmap_1.2.0 +[13] lattice_0.22-6 ggplot2_3.5.1 R6_2.5.1 generics_0.1.3 +[17] lmtest_0.9-40 MASS_7.3-61 htmlwidgets_1.6.4 tibble_3.2.1 +[21] desc_1.4.3 munsell_0.5.1 bslib_0.8.0 pillar_1.9.0 +[25] rlang_1.1.4 utf8_1.2.4 cachem_1.1.0 xfun_0.49 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.3 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.4.2 mclust_6.1.1 +[37] lifecycle_1.0.4 nlme_3.1-166 vctrs_0.6.5 evaluate_1.0.1 +[41] glue_1.8.0 codetools_0.2-20 ragg_1.3.3 zoo_1.8-12 +[45] fansi_1.0.6 colorspace_2.1-1 pkgconfig_2.0.3 tools_4.4.2 +[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: 64925476 kB</code></pre> +<pre><code>MemTotal: 64927788 kB</code></pre> </div> </div> - </div> - - <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - - <nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2> - </nav> -</div> - + </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="copyright"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <footer><div class="pkgdown-footer-left"> + <p>Developed by Johannes Ranke.</p> </div> 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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="hidden name"><code>2022_dmta_pathway.rmd</code></div> - + <div class="d-none name"><code>2022_dmta_pathway.rmd</code></div> </div> @@ -156,7 +104,7 @@ 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 1.2.5, 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 @@ -1497,7 +1445,7 @@ of parent models tested here.</p> <td align="left">dfop_path_1</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> @@ -1515,7 +1463,7 @@ of parent models tested here.</p> <td align="left">hs_path_1</td> <td align="left">C</td> <td align="left">C</td> -<td align="left">C</td> +<td align="left">OK</td> <td align="left">C</td> <td align="left">C</td> <td align="left">C</td> @@ -1553,24 +1501,24 @@ not converge with default settings.</p> <td align="left">fomc_path_1</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> </tr> <tr class="odd"> <td align="left">dfop_path_1</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> </tr> <tr class="even"> <td align="left">sforb_path_1</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> @@ -1583,7 +1531,7 @@ not converge with default settings.</p> <td align="left">C</td> <td align="left">C</td> <td align="left">C</td> -<td align="left">OK</td> +<td align="left">C</td> </tr> </tbody> </table> @@ -1644,8 +1592,6 @@ than twenty minutes.</p> successfully.</p> <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">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> -<pre><code>Warning in FUN(X[[i]], ...): Could not obtain log likelihood with 'is' method -for sforb_path_1 const</code></pre> <table class="table"> <thead><tr class="header"> <th align="left"></th> @@ -1665,58 +1611,65 @@ for sforb_path_1 const</code></pre> <tr class="even"> <td align="left">sfo_path_1 tc</td> <td align="right">18</td> -<td align="right">2276.3</td> -<td align="right">2272.5</td> -<td align="right">-1120.1</td> +<td align="right">2276.4</td> +<td align="right">2272.7</td> +<td align="right">-1120.2</td> </tr> <tr class="odd"> <td align="left">fomc_path_1 const</td> <td align="right">19</td> -<td align="right">2099.0</td> -<td align="right">2095.0</td> -<td align="right">-1030.5</td> +<td align="right">2095.9</td> +<td align="right">2091.9</td> +<td align="right">-1028.9</td> </tr> <tr class="even"> <td align="left">fomc_path_1 tc</td> <td align="right">20</td> -<td align="right">1939.6</td> -<td align="right">1935.5</td> -<td align="right">-949.8</td> +<td align="right">1939.0</td> +<td align="right">1934.8</td> +<td align="right">-949.5</td> </tr> <tr class="odd"> <td align="left">dfop_path_1 const</td> <td align="right">21</td> -<td align="right">2038.8</td> -<td align="right">2034.4</td> -<td align="right">-998.4</td> +<td align="right">2039.7</td> +<td align="right">2035.3</td> +<td align="right">-998.8</td> </tr> <tr class="even"> -<td align="left">hs_path_1 const</td> +<td align="left">sforb_path_1 const</td> <td align="right">21</td> -<td align="right">2024.2</td> -<td align="right">2019.8</td> -<td align="right">-991.1</td> +<td align="right">2017.7</td> +<td align="right">2013.4</td> +<td align="right">-987.9</td> </tr> <tr class="odd"> +<td align="left">hs_path_1 const</td> +<td align="right">21</td> +<td align="right">2023.7</td> +<td align="right">2019.3</td> +<td align="right">-990.9</td> +</tr> +<tr class="even"> <td align="left">dfop_path_1 tc</td> <td align="right">22</td> -<td align="right">1879.8</td> -<td align="right">1875.2</td> -<td align="right">-917.9</td> +<td align="right">1881.7</td> +<td align="right">1877.1</td> +<td align="right">-918.9</td> </tr> -<tr class="even"> +<tr class="odd"> <td align="left">sforb_path_1 tc</td> <td align="right">22</td> -<td align="right">1832.9</td> -<td align="right">1828.3</td> -<td align="right">-894.4</td> +<td align="right">1832.7</td> +<td align="right">1828.1</td> +<td align="right">-894.3</td> </tr> -<tr class="odd"> +<tr class="even"> <td align="left">hs_path_1 tc</td> <td align="right">22</td> -<td align="right">1831.4</td> -<td align="right">1826.8</td> -<td align="right">-893.7</td> +<td align="right">1831.6</td> +<td align="right">1827.0</td> +<td align="right">-893.8</td> </tr> </tbody> </table> @@ -1741,7 +1694,7 @@ Matrix<a class="anchor" aria-label="anchor" href="#parameter-identifiability-bas model parameters such as standard deviations of the degradation parameters in the population and error model parameters can be found.</p> -<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb9"><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">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"> @@ -1767,7 +1720,7 @@ found.</p> </tr> <tr class="even"> <td align="left">sforb_path_1</td> -<td align="left"></td> +<td align="left">sd(log_k_DMTA_bound_free)</td> <td align="left">sd(log_k_DMTA_bound_free)</td> </tr> <tr class="odd"> @@ -1787,13 +1740,13 @@ two-component error, the random effect for the rate constant from reversibly bound DMTA to the free DMTA (<code>k_DMTA_bound_free</code>) is not well-defined. Therefore, the fit is updated without assuming a random effect for this parameter.</p> -<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">saem_sforb_path_1_tc_reduced</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">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> <span> no_random_effect <span class="op">=</span> <span class="st">"log_k_DMTA_bound_free"</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">saem_sforb_path_1_tc_reduced</span><span class="op">)</span></span></code></pre></div> <p>As expected, no ill-defined parameters remain. The model comparison below shows that the reduced model is preferable.</p> -<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb11"><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">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="va">saem_sforb_path_1_tc_reduced</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"> @@ -1807,21 +1760,21 @@ below shows that the reduced model is preferable.</p> <tr class="odd"> <td align="left">saem_sforb_path_1_tc_reduced</td> <td align="right">21</td> -<td align="right">1830.3</td> -<td align="right">1825.9</td> +<td align="right">1830.4</td> +<td align="right">1826.0</td> <td align="right">-894.2</td> </tr> <tr class="even"> <td align="left">saem_1[[“sforb_path_1”, “tc”]]</td> <td align="right">22</td> -<td align="right">1832.9</td> -<td align="right">1828.3</td> -<td align="right">-894.4</td> +<td align="right">1832.7</td> +<td align="right">1828.1</td> +<td align="right">-894.3</td> </tr> </tbody> </table> <p>The convergence plot of the refined fit is shown below.</p> -<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb12"><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 class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></code></pre></div> <p><img src="2022_dmta_pathway_files/figure-html/saem-sforb-path-1-tc-reduced-convergence-1.png" width="700" style="display: block; margin: auto;"></p> <p>For some parameters, for example for <code>f_DMTA_ilr_1</code> and @@ -1840,14 +1793,16 @@ saemix.</p> </h3> <p>As an alternative check of parameter identifiability <span class="citation">(Duchesne et al. 2021)</span>, multistart runs were performed on the basis of the refined fit shown above.</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">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> +<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 -15 17 + 7 25 OK: Fit terminated successfully E: Error</code></pre> <p>Out of the 32 fits that were initiated, only 17 terminated without an @@ -1972,13 +1927,13 @@ 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 4.3.0 (2023-04-21) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.4.2 (2024-10-31) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default -BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 -LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so; LAPACK version 3.11.0 +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 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -1996,62 +1951,52 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.5 +[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_4.3.0 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_4.3.0 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 ragg_1.2.5 -[45] callr_3.7.3 pkgconfig_2.0.3 desc_1.4.2 pkgdown_2.0.7 -[49] bslib_0.4.2 pillar_1.9.0 gtable_0.3.3 glue_1.6.2 -[53] systemfonts_1.0.4 highr_0.10 xfun_0.39 tibble_3.2.1 -[57] lmtest_0.9-40 tidyselect_1.2.0 htmltools_0.5.5 nlme_3.1-162 -[61] rmarkdown_2.21 compiler_4.3.0 prettyunits_1.1.1</code></pre> + [1] sass_0.4.9 utf8_1.2.4 generics_0.1.3 lattice_0.22-6 + [5] digest_0.6.37 magrittr_2.0.3 evaluate_1.0.1 grid_4.4.2 + [9] fastmap_1.2.0 jsonlite_1.8.9 processx_3.8.4 pkgbuild_1.4.5 +[13] deSolve_1.40 mclust_6.1.1 ps_1.8.1 gridExtra_2.3 +[17] fansi_1.0.6 scales_1.3.0 codetools_0.2-20 textshaping_0.4.1 +[21] jquerylib_0.1.4 cli_3.6.3 rlang_1.1.4 munsell_0.5.1 +[25] cachem_1.1.0 yaml_2.3.10 inline_0.3.20 tools_4.4.2 +[29] dplyr_1.1.4 colorspace_2.1-1 ggplot2_3.5.1 vctrs_0.6.5 +[33] R6_2.5.1 zoo_1.8-12 lifecycle_1.0.4 fs_1.6.5 +[37] htmlwidgets_1.6.4 MASS_7.3-61 ragg_1.3.3 pkgconfig_2.0.3 +[41] desc_1.4.3 callr_3.7.6 pkgdown_2.1.1 pillar_1.9.0 +[45] bslib_0.8.0 gtable_0.3.6 glue_1.8.0 systemfonts_1.1.0 +[49] xfun_0.49 tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.1 +[53] htmltools_0.5.8.1 nlme_3.1-166 compiler_4.4.2 </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: 64925476 kB</code></pre> +<pre><code>MemTotal: 64927788 kB</code></pre> </div> </div> - </div> - - <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - - <nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2> - </nav> -</div> - + </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="copyright"> - <p></p> -<p>Developed by Johannes Ranke.</p> + <footer><div class="pkgdown-footer-left"> + <p>Developed by Johannes Ranke.</p> </div> -<div class="pkgdown"> - <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p> +<div class="pkgdown-footer-right"> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> </div> - </footer> + </footer> </div> - - + </body> </html> diff --git 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-parent degradation kinetics with residue data on mesotrione</h1> + + +<div class="row"> + <main id="main" class="col-md-9"><div class="page-header"> + + <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 10 August 2023</h4> +last compiled on 16 Februar 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="hidden name"><code>2023_mesotrione_parent.rmd</code></div> - + <div class="d-none name"><code>2023_mesotrione_parent.rmd</code></div> </div> @@ -159,7 +104,7 @@ 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> @@ -1521,7 +1466,7 @@ 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> @@ -2481,8 +2426,8 @@ 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 4.3.1 (2023-06-16) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.4.2 (2024-10-31) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default @@ -2505,60 +2450,50 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.43 mkin_1.2.6 +[1] saemix_3.3 npde_3.5 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_0.20-45 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.1 fastmap_1.1.1 cellranger_1.1.0 rprojroot_2.0.3 -[13] jsonlite_1.8.5 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_4.3.1 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 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 highr_0.10 xfun_0.39 -[49] tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 htmltools_0.5.5 -[53] nlme_3.1-162 rmarkdown_2.22 compiler_4.3.1 readxl_1.4.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.8.9 dplyr_1.1.4 compiler_4.4.2 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.1.0 + [9] scales_1.3.0 textshaping_0.4.1 yaml_2.3.10 fastmap_1.2.0 +[13] lattice_0.22-6 ggplot2_3.5.1 R6_2.5.1 generics_0.1.3 +[17] lmtest_0.9-40 MASS_7.3-61 htmlwidgets_1.6.4 tibble_3.2.1 +[21] desc_1.4.3 munsell_0.5.1 bslib_0.8.0 pillar_1.9.0 +[25] rlang_1.1.4 utf8_1.2.4 cachem_1.1.0 xfun_0.49 +[29] fs_1.6.5 sass_0.4.9 cli_3.6.3 pkgdown_2.1.1 +[33] magrittr_2.0.3 digest_0.6.37 grid_4.4.2 mclust_6.1.1 +[37] lifecycle_1.0.4 nlme_3.1-166 vctrs_0.6.5 evaluate_1.0.1 +[41] glue_1.8.0 ragg_1.3.3 zoo_1.8-12 fansi_1.0.6 +[45] colorspace_2.1-1 rmarkdown_2.29 pkgconfig_2.0.3 tools_4.4.2 +[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: Intel(R) Core(TM) i7-4710MQ CPU @ 2.50GHz</code></pre> -<pre><code>MemTotal: 12165632 kB</code></pre> +<pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> +<pre><code>MemTotal: 64927788 kB</code></pre> </div> </div> - 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