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Kinetic evaluations shown for these datasets are intended -to illustrate and advance kinetic modelling. 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</ul><ul class="nav navbar-nav navbar-right"><li> - <a href="https://github.com/jranke/mkin/" class="external-link"> - <span class="fab fa-github fa-lg"></span> - - </a> -</li> - </ul></div><!--/.nav-collapse --> - </div><!--/.container --> -</div><!--/.navbar --> - - - - </header><div class="row"> - <div class="col-md-9 contents"> - <div class="page-header"> - <h1>Aerobic soil degradation data on dimethenamid and dimethenamid-P from the EU assessment in 2018</h1> - <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/dimethenamid_2018.R" class="external-link"><code>R/dimethenamid_2018.R</code></a></small> - <div class="hidden name"><code>dimethenamid_2018.Rd</code></div> - </div> - - <div class="ref-description"> - <p>The datasets were extracted from the active substance evaluation dossier -published by EFSA. Kinetic evaluations shown for these datasets are intended -to illustrate and advance kinetic modelling. The fact that these data and -some results are shown here does not imply a license to use them in the -context of pesticide registrations, as the use of the data may be -constrained by data protection regulations.</p> - </div> - - <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">dimethenamid_2018</span></span></code></pre></div> - </div> - - <div id="format"> - <h2>Format</h2> - <p>An <a href="mkindsg.html">mkindsg</a> object grouping seven datasets with some meta information</p> - </div> - <div id="source"> - <h2>Source</h2> - <p>Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria (2018) -Renewal Assessment Report Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour -Rev. 2 - November 2017 -<a href="https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716" class="external-link">https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716</a></p> - </div> - <div id="details"> - <h2>Details</h2> - <p>The R code used to create this data object is installed with this package -in the 'dataset_generation' directory. In the code, page numbers are given for -specific pieces of information in the comments.</p> - </div> - - <div id="ref-examples"> - <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><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">dimethenamid_2018</span><span class="op">)</span></span></span> -<span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 7 mkinds objects</span> -<span class="r-out co"><span class="r-pr">#></span> Title $title: Aerobic soil degradation data on dimethenamid-P from the EU assessment in 2018 </span> -<span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> -<span class="r-out co"><span class="r-pr">#></span> DMTAP M23 M27 M31 DMTA </span> -<span class="r-out co"><span class="r-pr">#></span> 3 7 7 7 4 </span> -<span class="r-out co"><span class="r-pr">#></span> Time normalisation factors $f_time_norm:</span> -<span class="r-out co"><span class="r-pr">#></span> [1] 1.0000000 0.9706477 1.2284784 1.2284784 0.6233856 0.7678922 0.6733938</span> -<span class="r-out co"><span class="r-pr">#></span> Meta information $meta:</span> -<span class="r-out co"><span class="r-pr">#></span> study usda_soil_type study_moisture_ref_type rel_moisture</span> -<span class="r-out co"><span class="r-pr">#></span> Calke Unsworth 2014 Sandy loam pF2 1.00</span> -<span class="r-out co"><span class="r-pr">#></span> Borstel Staudenmaier 2009 Sand pF1 0.50</span> -<span class="r-out co"><span class="r-pr">#></span> Elliot 1 Wendt 1997 Clay loam pF2.5 0.75</span> -<span class="r-out co"><span class="r-pr">#></span> Elliot 2 Wendt 1997 Clay loam pF2.5 0.75</span> -<span class="r-out co"><span class="r-pr">#></span> Flaach König 1996 Sandy clay loam pF1 0.40</span> -<span class="r-out co"><span class="r-pr">#></span> BBA 2.2 König 1995 Loamy sand pF1 0.40</span> -<span class="r-out co"><span class="r-pr">#></span> BBA 2.3 König 1995 Sandy loam pF1 0.40</span> -<span class="r-out co"><span class="r-pr">#></span> study_ref_moisture temperature</span> -<span class="r-out co"><span class="r-pr">#></span> Calke NA 20</span> -<span class="r-out co"><span class="r-pr">#></span> Borstel 23.00 20</span> -<span class="r-out co"><span class="r-pr">#></span> Elliot 1 33.37 23</span> -<span class="r-out co"><span class="r-pr">#></span> Elliot 2 33.37 23</span> -<span class="r-out co"><span class="r-pr">#></span> Flaach NA 20</span> -<span class="r-out co"><span class="r-pr">#></span> BBA 2.2 NA 20</span> -<span class="r-out co"><span class="r-pr">#></span> BBA 2.3 NA 20</span> -<span class="r-in"><span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span></span> -<span class="r-in"><span> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span></span> -<span class="r-in"><span> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span></span> -<span class="r-in"><span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span></span> -<span class="r-in"><span> <span class="va">ds_i</span></span></span> -<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></span> -<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></span> -<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> -<span class="r-in"><span><span class="co"># We don't use DFOP for the parent compound, as this gives numerical</span></span></span> -<span class="r-in"><span><span class="co"># instabilities in the fits</span></span></span> -<span class="r-in"><span><span class="va">sfo_sfo3p</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> -<span class="r-in"><span> DMTA <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</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">"M23"</span>, <span class="st">"M27"</span>, <span class="st">"M31"</span><span class="op">)</span><span class="op">)</span>,</span></span> -<span class="r-in"><span> M23 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span></span> -<span class="r-in"><span> M27 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span></span> -<span class="r-in"><span> M31 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M27"</span>, sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span></span> -<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span></span></span> -<span class="r-in"><span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="va">dmta_sfo_sfo3p_tc</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"SFO-SFO3+"</span> <span class="op">=</span> <span class="va">sfo_sfo3p</span><span class="op">)</span>,</span></span> -<span class="r-in"><span> <span class="va">dmta_ds</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> -<span class="r-in"><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">dmta_sfo_sfo3p_tc</span><span class="op">)</span></span></span> -<span class="r-out co"><span class="r-pr">#></span> <mmkin> object</span> -<span class="r-out co"><span class="r-pr">#></span> Status of individual fits:</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> dataset</span> -<span class="r-out co"><span class="r-pr">#></span> model Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot</span> -<span class="r-out co"><span class="r-pr">#></span> SFO-SFO3+ OK OK OK OK OK OK </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> -<span class="r-in"><span><span class="co"># The default (test_log_parms = FALSE) gives an undue</span></span></span> -<span class="r-in"><span><span class="co"># influence of ill-defined rate constants that have</span></span></span> -<span class="r-in"><span><span class="co"># extremely small values:</span></span></span> -<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="co"># If we disregards ill-defined rate constants, the results</span></span></span> -<span class="r-in"><span><span class="co"># look more plausible, but the truth is likely to be in</span></span></span> -<span class="r-in"><span><span class="co"># between these variants</span></span></span> -<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> -<span class="r-plt img"><img src="dimethenamid_2018-1.png" alt="" width="700" height="433"></span> -<span class="r-in"><span><span class="co"># We can also specify a default value for the failing</span></span></span> -<span class="r-in"><span><span class="co"># log parameters, to mimic FOCUS guidance</span></span></span> -<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>,</span></span> -<span class="r-in"><span> default_log_parms <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">2</span><span class="op">)</span><span class="op">/</span><span class="fl">1000</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="co"># As these attempts are not satisfying, we use nonlinear mixed-effects models</span></span></span> -<span class="r-in"><span><span class="co"># f_dmta_nlme_tc <- nlme(dmta_sfo_sfo3p_tc)</span></span></span> -<span class="r-in"><span><span class="co"># nlme reaches maxIter = 50 without convergence</span></span></span> -<span class="r-in"><span><span class="va">f_dmta_saem_tc</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span></span></span> -<span class="r-in"><span><span class="co"># I am commenting out the convergence plot as rendering them</span></span></span> -<span class="r-in"><span><span class="co"># with pkgdown fails (at least without further tweaks to the</span></span></span> -<span class="r-in"><span><span class="co"># graphics device used)</span></span></span> -<span class="r-in"><span><span class="co">#saemix::plot(f_dmta_saem_tc$so, plot.type = "convergence")</span></span></span> -<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_dmta_saem_tc</span><span class="op">)</span></span></span> -<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.2 </span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.2.3 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.3 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Sun Apr 16 08:30:03 2023 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Sun Apr 16 08:30:03 2023 </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Equations:</span> -<span class="r-out co"><span class="r-pr">#></span> d_DMTA/dt = - k_DMTA * DMTA</span> -<span class="r-out co"><span class="r-pr">#></span> d_M23/dt = + f_DMTA_to_M23 * k_DMTA * DMTA - k_M23 * M23</span> -<span class="r-out co"><span class="r-pr">#></span> d_M27/dt = + f_DMTA_to_M27 * k_DMTA * DMTA - k_M27 * M27 + k_M31 * M31</span> -<span class="r-out co"><span class="r-pr">#></span> d_M31/dt = + f_DMTA_to_M31 * k_DMTA * DMTA - k_M31 * M31</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Data:</span> -<span class="r-out co"><span class="r-pr">#></span> 563 observations of 4 variable(s) grouped in 6 datasets</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type deSolve </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted in 304.528 s</span> -<span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 9 chains</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Variance model: Two-component variance function </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Starting values for degradation parameters:</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 log_k_DMTA log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1 </span> -<span class="r-out co"><span class="r-pr">#></span> 95.5662 -2.9048 -3.8130 -4.1600 -4.1486 0.1341 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 f_DMTA_ilr_3 </span> -<span class="r-out co"><span class="r-pr">#></span> 0.1385 -1.6700 </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> -<span class="r-out co"><span class="r-pr">#></span> None</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Starting values for random effects (square root of initial entries in omega):</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 log_k_DMTA log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 4.802 0.0000 0.0000 0.000 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA 0.000 0.9834 0.0000 0.000 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 0.000 0.0000 0.6983 0.000 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 0.000 0.0000 0.0000 1.028 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 0.000 0.0000 0.0000 0.000 0.9841 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 0.000 0.0000 0.0000 0.000 0.0000 0.7185</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 0.000 0.0000 0.0000 0.000 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 0.000 0.0000 0.0000 0.000 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 f_DMTA_ilr_3</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 0.0000 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 0.7378 0.0000</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 0.0000 0.4451</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Starting values for error model parameters:</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 b.1 </span> -<span class="r-out co"><span class="r-pr">#></span> 1 1 </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Results:</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> -<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> -<span class="r-out co"><span class="r-pr">#></span> 2276 2273 -1120</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Optimised parameters:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 88.3192 83.8656 92.7729</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA -3.0530 -3.5686 -2.5373</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -4.0620 -4.9202 -3.2038</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -3.8633 -4.2668 -3.4598</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -3.9731 -4.4763 -3.4699</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 0.1346 -0.2150 0.4841</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 0.1449 -0.2593 0.5491</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -1.3882 -1.7011 -1.0753</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 0.9156 0.8217 1.0095</span> -<span class="r-out co"><span class="r-pr">#></span> b.1 0.1383 0.1216 0.1550</span> -<span class="r-out co"><span class="r-pr">#></span> SD.DMTA_0 3.7280 -0.6949 8.1508</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_DMTA 0.6431 0.2781 1.0080</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M23 1.0096 0.3782 1.6409</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M27 0.4583 0.1541 0.7625</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M31 0.5738 0.1942 0.9533</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_1 0.4119 0.1528 0.6709</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_2 0.4780 0.1806 0.7754</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_3 0.3657 0.1383 0.5931</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Correlation: </span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 l__DMTA lg__M23 lg__M27 lg__M31 f_DMTA__1 f_DMTA__2</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA 0.0303 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -0.0229 -0.0032 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -0.0372 -0.0049 0.0041 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -0.0245 -0.0032 0.0022 0.0815 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 -0.0046 -0.0006 0.0415 -0.0433 0.0324 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 -0.0008 -0.0002 0.0214 -0.0267 -0.0893 -0.0361 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -0.1755 -0.0135 0.0423 0.0775 0.0377 -0.0066 0.0060 </span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> SD.DMTA_0 3.7280 -0.6949 8.1508</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_DMTA 0.6431 0.2781 1.0080</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M23 1.0096 0.3782 1.6409</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M27 0.4583 0.1541 0.7625</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M31 0.5738 0.1942 0.9533</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_1 0.4119 0.1528 0.6709</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_2 0.4780 0.1806 0.7754</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_3 0.3657 0.1383 0.5931</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Variance model:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 0.9156 0.8217 1.009</span> -<span class="r-out co"><span class="r-pr">#></span> b.1 0.1383 0.1216 0.155</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 88.31924 83.865625 92.77286</span> -<span class="r-out co"><span class="r-pr">#></span> k_DMTA 0.04722 0.028196 0.07908</span> -<span class="r-out co"><span class="r-pr">#></span> k_M23 0.01721 0.007298 0.04061</span> -<span class="r-out co"><span class="r-pr">#></span> k_M27 0.02100 0.014027 0.03144</span> -<span class="r-out co"><span class="r-pr">#></span> k_M31 0.01882 0.011375 0.03112</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 0.14608 NA NA</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M27 0.12077 NA NA</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M31 0.11123 NA NA</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> -<span class="r-out co"><span class="r-pr">#></span> ff</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_M23 0.1461</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_M27 0.1208</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_M31 0.1112</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_sink 0.6219</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> -<span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA 14.68 48.76</span> -<span class="r-out co"><span class="r-pr">#></span> M23 40.27 133.76</span> -<span class="r-out co"><span class="r-pr">#></span> M27 33.01 109.65</span> -<span class="r-out co"><span class="r-pr">#></span> M31 36.84 122.38</span> -<span class="r-in"><span><span class="co"># As the confidence interval for the random effects of DMTA_0</span></span></span> -<span class="r-in"><span><span class="co"># includes zero, we could try an alternative model without</span></span></span> -<span class="r-in"><span><span class="co"># such random effects</span></span></span> -<span class="r-in"><span><span class="co"># f_dmta_saem_tc_2 <- saem(dmta_sfo_sfo3p_tc,</span></span></span> -<span class="r-in"><span><span class="co"># covariance.model = diag(c(0, rep(1, 7))))</span></span></span> -<span class="r-in"><span><span class="co"># saemix::plot(f_dmta_saem_tc_2$so, plot.type = "convergence")</span></span></span> -<span class="r-in"><span><span class="co"># This does not perform better judged by AIC and BIC</span></span></span> -<span class="r-in"><span><span class="co"># saemix::compare.saemix(f_dmta_saem_tc$so, f_dmta_saem_tc_2$so)</span></span></span> -<span class="r-in"><span><span class="co"># }</span></span></span> -</code></pre></div> - </div> - </div> - <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> - </nav></div> -</div> - - - <footer><div class="copyright"> - <p></p><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> - - </footer></div> - - - - - - - </body></html> - |