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Diffstat (limited to 'docs/dev/reference/dimethenamid_2018.html')
| -rw-r--r-- | docs/dev/reference/dimethenamid_2018.html | 126 |
1 files changed, 70 insertions, 56 deletions
diff --git a/docs/dev/reference/dimethenamid_2018.html b/docs/dev/reference/dimethenamid_2018.html index 2454a609..96ec73c6 100644 --- a/docs/dev/reference/dimethenamid_2018.html +++ b/docs/dev/reference/dimethenamid_2018.html @@ -22,7 +22,7 @@ constrained by data protection regulations."><meta name="robots" content="noinde </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.2.2</span> </span> </div> @@ -49,19 +49,25 @@ constrained by data protection regulations."><meta name="robots" content="noinde <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> </li> <li> - <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + <a href="../articles/web_only/benchmarks.html">Benchmark timings for mkin</a> + </li> + <li> + <a href="../articles/web_only/saem_benchmarks.html">Benchmark timings for saem.mmkin</a> </li> </ul></li> <li> @@ -180,17 +186,15 @@ specific pieces of information in the comments.</p> <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-plt img"><img src="dimethenamid_2018-1.png" alt="" width="700" height="433"></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_2018-2.png" alt="" width="700" height="433"></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-plt img"><img src="dimethenamid_2018-3.png" alt="" width="700" height="433"></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> @@ -200,11 +204,11 @@ specific pieces of information in the comments.</p> <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: 3.1 </span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:29:07 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:29:07 2022 </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: 1.2.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.2 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Thu Nov 24 08:05:16 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Thu Nov 24 08:05:16 2022 </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> @@ -217,7 +221,7 @@ specific pieces of information in the comments.</p> <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 797.539 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 819.725 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> @@ -235,69 +239,79 @@ specific pieces of information in the comments.</p> <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 2272 -1120</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 88.5943 84.3961 92.7925</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA -3.0466 -3.5609 -2.5322</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -4.0684 -4.9340 -3.2029</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -3.8628 -4.2627 -3.4628</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -3.9803 -4.4804 -3.4801</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 0.1304 -0.2186 0.4795</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 0.1490 -0.2559 0.5540</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -1.3970 -1.6976 -1.0964</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 0.8229 1.0084</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.1383 0.1215 0.1551</span> +<span class="r-out co"><span class="r-pr">#></span> SD.DMTA_0 3.7280 -0.6951 8.1511</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 0.0309 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -0.0231 -0.0031 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -0.0381 -0.0048 0.0039 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -0.0251 -0.0031 0.0021 0.0830 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 -0.0046 -0.0006 0.0417 -0.0437 0.0328 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 -0.0008 -0.0002 0.0214 -0.0270 -0.0909 -0.0361 </span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -0.1832 -0.0135 0.0434 0.0804 0.0395 -0.0070 0.0059 </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 3.3651 -0.9649 7.6951</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_DMTA 0.6415 0.2774 1.0055</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M23 1.0176 0.3809 1.6543</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M27 0.4538 0.1522 0.7554</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M31 0.5684 0.1905 0.9464</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_1 0.4111 0.1524 0.6699</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_2 0.4788 0.1808 0.7768</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_3 0.3501 0.1316 0.5685</span> +<span class="r-out co"><span class="r-pr">#></span> SD.DMTA_0 3.7280 -0.6951 8.1511</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 0.9349 0.8409 1.029</span> -<span class="r-out co"><span class="r-pr">#></span> b.1 0.1344 0.1178 0.151</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 0.8229 1.0084</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.1383 0.1215 0.1551</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 88.59431 84.396147 92.79246</span> -<span class="r-out co"><span class="r-pr">#></span> k_DMTA 0.04752 0.028413 0.07948</span> -<span class="r-out co"><span class="r-pr">#></span> k_M23 0.01710 0.007198 0.04064</span> -<span class="r-out co"><span class="r-pr">#></span> k_M27 0.02101 0.014084 0.03134</span> -<span class="r-out co"><span class="r-pr">#></span> k_M31 0.01868 0.011329 0.03080</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 0.14498 NA NA</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M27 0.12056 NA NA</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M31 0.11015 NA NA</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 0.1450</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_M27 0.1206</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_M31 0.1101</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_sink 0.6243</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 14.59 48.45</span> -<span class="r-out co"><span class="r-pr">#></span> M23 40.52 134.62</span> -<span class="r-out co"><span class="r-pr">#></span> M27 32.99 109.60</span> -<span class="r-out co"><span class="r-pr">#></span> M31 37.11 123.26</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> |