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Diffstat (limited to 'docs/articles/prebuilt/2022_dmta_parent.html')
-rw-r--r-- | docs/articles/prebuilt/2022_dmta_parent.html | 475 |
1 files changed, 171 insertions, 304 deletions
diff --git a/docs/articles/prebuilt/2022_dmta_parent.html b/docs/articles/prebuilt/2022_dmta_parent.html index 2da41981..9fdf75f7 100644 --- a/docs/articles/prebuilt/2022_dmta_parent.html +++ b/docs/articles/prebuilt/2022_dmta_parent.html @@ -33,7 +33,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.2.4</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.2.6</span> </span> </div> @@ -74,6 +74,9 @@ <a href="../../articles/prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a> </li> <li> + <a href="../../articles/prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a> + </li> + <li> <a href="../../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a> </li> <li> @@ -135,7 +138,7 @@ with residue data on dimethenamid and dimethenamid-P</h1> 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 30 October 2023</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> @@ -154,7 +157,7 @@ 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 1.2.4. It contains the test data +<p>The mkin package is used in version 1.2.6. 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> @@ -1005,7 +1008,7 @@ 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> @@ -1013,7 +1016,7 @@ 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> @@ -1111,9 +1114,9 @@ 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> @@ -1132,9 +1135,9 @@ 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> @@ -1215,12 +1218,12 @@ 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> @@ -1238,8 +1241,8 @@ 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> @@ -1248,12 +1251,12 @@ 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> @@ -1286,10 +1289,10 @@ Plot of the final NLHM DFOP fit <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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:09 2023 -Date of summary: Thu Apr 20 14:07:10 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:19:13 2023 +Date of summary: Mon Oct 30 11:19:14 2023 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1301,21 +1304,21 @@ Data: Model predictions using solution type analytical -Fitted in 4.175 s +Fitted in 8.975 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 @@ -1328,40 +1331,40 @@ 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 0.863943 1.25965 +b.1 0.029550 0.022529 0.03657 +SD.DMTA_0 2.068581 0.427706 3.70946 +SD.k1 0.598285 0.258235 0.93833 +SD.g 1.016689 0.360057 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 0.4277 3.7095 +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 0.86394 1.25965 +b.1 0.02955 0.02253 0.03657 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> @@ -1462,10 +1465,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:02 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:18:56 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1475,7 +1478,7 @@ Data: Model predictions using solution type analytical -Fitted in 0.982 s +Fitted in 1.899 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1534,10 +1537,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:03 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:19:00 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1547,7 +1550,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.398 s +Fitted in 5.364 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1608,10 +1611,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:02 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:18:57 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1621,7 +1624,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.398 s +Fitted in 2.944 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1653,7 +1656,7 @@ 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 @@ -1685,10 +1688,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:04 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:19:01 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1698,7 +1701,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.044 s +Fitted in 6.228 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1724,38 +1727,38 @@ 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 1.23601 1.76836 +b.1 0.02893 0.02099 0.03687 +SD.DMTA_0 1.61887 -0.03636 3.27411 +SD.alpha 0.58145 0.17364 0.98925 +SD.beta 0.68205 0.21108 1.15303 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 -0.03636 3.2741 +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 1.23601 1.76836 +b.1 0.02893 0.02099 0.03687 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> @@ -1764,10 +1767,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:02 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:18:57 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1779,7 +1782,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.838 s +Fitted in 3.231 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1810,10 +1813,10 @@ 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 @@ -1848,10 +1851,10 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:04 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:19:01 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1863,21 +1866,21 @@ Data: Model predictions using solution type analytical -Fitted in 3.297 s +Fitted in 6.71 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 @@ -1890,42 +1893,42 @@ 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 0.868694 1.26912 +b.1 0.029265 0.022262 0.03627 +SD.DMTA_0 2.065796 0.428485 3.70311 +SD.k1 0.583703 0.251796 0.91561 +SD.k2 0.004167 -7.832168 7.84050 +SD.g 1.064450 0.397476 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 0.4285 3.7031 +SD.k1 0.583703 0.2518 0.9156 +SD.k2 0.004167 -7.8322 7.8405 +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 0.86869 1.26912 +b.1 0.02927 0.02226 0.03627 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> @@ -1934,167 +1937,28 @@ 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:03 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:18:59 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: -d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA - -Data: -155 observations of 1 variable(s) grouped in 6 datasets - -Model predictions using solution type analytical - -Fitted in 1.972 s -Using 300, 100 iterations and 9 chains - -Variance model: Constant variance - -Starting values for degradation parameters: - DMTA_0 k1 k2 tb -97.82176 0.06931 0.02997 11.13945 - -Fixed degradation parameter values: -None - -Starting values for random effects (square root of initial entries in omega): - DMTA_0 k1 k2 tb -DMTA_0 97.82 0 0 0 -k1 0.00 1 0 0 -k2 0.00 0 1 0 -tb 0.00 0 0 1 - -Starting values for error model parameters: -a.1 - 1 - -Results: - -Likelihood computed by importance sampling - AIC BIC logLik - 714 712.1 -348 - -Optimised parameters: - est. lower upper -DMTA_0 98.16102 96.47747 99.84456 -k1 0.07876 0.05261 0.10491 -k2 0.02227 0.01706 0.02747 -tb 13.99089 -7.40049 35.38228 -a.1 1.82305 1.60700 2.03910 -SD.DMTA_0 1.88413 0.56204 3.20622 -SD.k1 0.34292 0.10482 0.58102 -SD.k2 0.19851 0.01718 0.37985 -SD.tb 1.68168 0.58064 2.78272 - -Correlation: - DMTA_0 k1 k2 -k1 0.0142 -k2 0.0001 -0.0025 -tb 0.0165 -0.1256 -0.0301 - -Random effects: - est. lower upper -SD.DMTA_0 1.8841 0.56204 3.2062 -SD.k1 0.3429 0.10482 0.5810 -SD.k2 0.1985 0.01718 0.3798 -SD.tb 1.6817 0.58064 2.7827 - -Variance model: - est. lower upper -a.1 1.823 1.607 2.039 - -Estimated disappearance times: - DT50 DT90 DT50back DT50_k1 DT50_k2 -DMTA 8.801 67.91 20.44 8.801 31.13 - -</code></pre> -<p></p> +d_DMTA/dt = - ifelse(time +<p></p></code> <caption> 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: 1.2.3 -R version used for fitting: 4.2.3 -Date of fit: Thu Apr 20 14:07:04 2023 -Date of summary: Thu Apr 20 14:08:16 2023 +mkin version used for pre-fitting: 1.2.6 +R version used for fitting: 4.3.1 +Date of fit: Mon Oct 30 11:19:02 2023 +Date of summary: Mon Oct 30 11:21:30 2023 Equations: -d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA - -Data: -155 observations of 1 variable(s) grouped in 6 datasets - -Model predictions using solution type analytical - -Fitted in 3.378 s -Using 300, 100 iterations and 9 chains - -Variance model: Two-component variance function - -Starting values for degradation parameters: - DMTA_0 k1 k2 tb -98.45190 0.07525 0.02576 19.19375 - -Fixed degradation parameter values: -None - -Starting values for random effects (square root of initial entries in omega): - DMTA_0 k1 k2 tb -DMTA_0 98.45 0 0 0 -k1 0.00 1 0 0 -k2 0.00 0 1 0 -tb 0.00 0 0 1 - -Starting values for error model parameters: -a.1 b.1 - 1 1 - -Results: - -Likelihood computed by importance sampling - AIC BIC logLik - 667.1 665 -323.6 - -Optimised parameters: - est. lower upper -DMTA_0 97.76570 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 -SD.k1 0.59166 0.25621 0.92711 -SD.k2 0.30698 0.09561 0.51835 -SD.tb 0.01274 -0.10914 0.13462 - -Correlation: - DMTA_0 k1 k2 -k1 0.0160 -k2 -0.0070 -0.0024 -tb -0.0668 -0.0103 -0.2013 - -Random effects: - est. lower upper -SD.DMTA_0 2.04877 0.42607 3.6715 -SD.k1 0.59166 0.25621 0.9271 -SD.k2 0.30698 0.09561 0.5183 -SD.tb 0.01274 -0.10914 0.1346 - -Variance model: - est. lower upper -a.1 1.08835 0.88590 1.29080 -b.1 0.02964 0.02257 0.03671 - -Estimated disappearance times: - DT50 DT90 DT50back DT50_k1 DT50_k2 -DMTA 11.84 51.71 15.57 11.84 29.66 - -</code></pre> -<p></p> +d_DMTA/dt = - ifelse(time +<p></p></code> +</pre></pre> </div> <div class="section level3"> <h3 id="hierarchical-model-convergence-plots">Hierarchical model convergence plots<a class="anchor" aria-label="anchor" href="#hierarchical-model-convergence-plots"></a> @@ -2143,50 +2007,53 @@ 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 4.2.3 (2023-03-15) +<pre><code>R version 4.3.1 (2023-06-16) Platform: x86_64-pc-linux-gnu (64-bit) -Running under: Debian GNU/Linux 12 (bookworm) +Running under: Ubuntu 22.04.3 LTS 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 +BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0 locale: - [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C - [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=de_DE.UTF-8 - [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 - [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C + [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C + [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 + [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 + [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C -[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C +[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C + +time zone: Europe/Zurich +tzcode source: system (glibc) attached base packages: [1] parallel stats graphics grDevices utils datasets methods [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.3 +[1] saemix_3.2 npde_3.3 knitr_1.44 mkin_1.2.6 loaded via a namespace (and not attached): - [1] highr_0.10 pillar_1.9.0 bslib_0.4.2 compiler_4.2.3 - [5] jquerylib_0.1.4 tools_4.2.3 mclust_6.0.0 digest_0.6.31 - [9] tibble_3.2.1 jsonlite_1.8.4 evaluate_0.20 memoise_2.0.1 -[13] lifecycle_1.0.3 nlme_3.1-162 gtable_0.3.3 lattice_0.21-8 -[17] pkgconfig_2.0.3 rlang_1.1.0 DBI_1.1.3 cli_3.6.1 -[21] yaml_2.3.7 pkgdown_2.0.7 xfun_0.38 fastmap_1.1.1 -[25] gridExtra_2.3 dplyr_1.1.1 stringr_1.5.0 generics_0.1.3 -[29] desc_1.4.2 fs_1.6.1 vctrs_0.6.1 sass_0.4.5 -[33] systemfonts_1.0.4 tidyselect_1.2.0 rprojroot_2.0.3 lmtest_0.9-40 -[37] grid_4.2.3 glue_1.6.2 R6_2.5.1 textshaping_0.3.6 -[41] fansi_1.0.4 rmarkdown_2.21 purrr_1.0.1 ggplot2_3.4.2 -[45] magrittr_2.0.3 codetools_0.2-19 scales_1.2.1 htmltools_0.5.5 -[49] colorspace_2.1-0 ragg_1.2.5 utf8_1.2.3 stringi_1.7.12 -[53] munsell_0.5.0 cachem_1.0.7 zoo_1.8-12 </code></pre> + [1] sass_0.4.7 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 + [5] lattice_0.21-9 digest_0.6.33 magrittr_2.0.3 evaluate_0.22 + [9] grid_4.3.1 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.7 +[13] mclust_6.0.0 gridExtra_2.3 purrr_1.0.1 fansi_1.0.4 +[17] scales_1.2.1 codetools_0.2-19 textshaping_0.3.6 jquerylib_0.1.4 +[21] cli_3.6.1 rlang_1.1.1 munsell_0.5.0 cachem_1.0.8 +[25] yaml_2.3.7 tools_4.3.1 memoise_2.0.1 dplyr_1.1.2 +[29] colorspace_2.1-0 ggplot2_3.4.2 vctrs_0.6.3 R6_2.5.1 +[33] zoo_1.8-12 lifecycle_1.0.3 stringr_1.5.0 fs_1.6.3 +[37] MASS_7.3-60 ragg_1.2.5 pkgconfig_2.0.3 desc_1.4.2 +[41] pkgdown_2.0.7 bslib_0.5.1 pillar_1.9.0 gtable_0.3.3 +[45] glue_1.6.2 systemfonts_1.0.4 xfun_0.40 tibble_3.2.1 +[49] lmtest_0.9-40 tidyselect_1.2.0 rstudioapi_0.15.0 htmltools_0.5.6.1 +[53] nlme_3.1-163 rmarkdown_2.23 compiler_4.3.1 </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: 64936316 kB</code></pre> +<pre><code>CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz</code></pre> +<pre><code>MemTotal: 247605564 kB</code></pre> </div> </div> </div> |