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<img src="" class="logo" alt=""><h1>Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</h1> + + <h1>Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> <h4 data-toc-skip class="date">Last change on 5 January -2023, last compiled on 16 November 2023</h4> +2023, last compiled on 12 Mai 2025</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/prebuilt/2022_dmta_parent.rmd" class="external-link"><code>vignettes/prebuilt/2022_dmta_parent.rmd</code></a></small> <div class="d-none name"><code>2022_dmta_parent.rmd</code></div> @@ -116,7 +102,7 @@ FOMC, DFOP and HS can be fitted with the mkin package.</p> 173340 (Application of nonlinear hierarchical models to the kinetic evaluation of chemical degradation data) of the German Environment Agency carried out in 2022 and 2023.</p> -<p>The mkin package is used in version 1.2.6. It contains the test data +<p>The mkin package is used in version 1.2.10. It contains the test data and the functions used in the evaluations. The <code>saemix</code> package is used as a backend for fitting the NLHM, but is also loaded to make the convergence plot function available.</p> @@ -1247,11 +1233,11 @@ Plot of the final NLHM DFOP fit <p>Finally, a summary report of the fit is produced.</p> <div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_tc_no_ranef_k2</span><span class="op">)</span></span></code></pre></div> -<pre><code>saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:35 2023 -Date of summary: Thu Nov 16 04:59:35 2023 +<pre><code>saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:46 2025 +Date of summary: Mon May 12 21:06:46 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1263,7 +1249,7 @@ Data: Model predictions using solution type analytical -Fitted in 4.4 s +Fitted in 3.953 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1298,11 +1284,11 @@ DMTA_0 98.256267 96.286112 100.22642 k1 0.064037 0.033281 0.09479 k2 0.008469 0.006002 0.01094 g 0.954167 0.914460 0.99387 -a.1 1.061795 0.863943 1.25965 -b.1 0.029550 0.022529 0.03657 -SD.DMTA_0 2.068581 0.427706 3.70946 +a.1 1.061795 0.878608 1.24498 +b.1 0.029550 0.022593 0.03651 +SD.DMTA_0 2.068581 0.427178 3.70998 SD.k1 0.598285 0.258235 0.93833 -SD.g 1.016689 0.360057 1.67332 +SD.g 1.016689 0.360061 1.67332 Correlation: DMTA_0 k1 k2 @@ -1312,14 +1298,14 @@ g -0.0521 -0.0286 -0.2744 Random effects: est. lower upper -SD.DMTA_0 2.0686 0.4277 3.7095 +SD.DMTA_0 2.0686 0.4272 3.7100 SD.k1 0.5983 0.2582 0.9383 SD.g 1.0167 0.3601 1.6733 Variance model: est. lower upper -a.1 1.06180 0.86394 1.25965 -b.1 0.02955 0.02253 0.03657 +a.1 1.06180 0.87861 1.24498 +b.1 0.02955 0.02259 0.03651 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -1423,11 +1409,11 @@ Erythropoiesis.”</span> <em>BMC Bioinformatics</em> 22 (478). <a href="https:/ Hierarchical mkin fit of the SFO model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:26 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:38 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1437,7 +1423,7 @@ Data: Model predictions using solution type analytical -Fitted in 0.788 s +Fitted in 0.793 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1495,11 +1481,11 @@ DMTA 12.24 40.65 Hierarchical mkin fit of the SFO model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:40 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - k_DMTA * DMTA @@ -1509,7 +1495,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.428 s +Fitted in 2.462 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1537,13 +1523,13 @@ Likelihood computed by importance sampling 798.3 797.1 -393.2 Optimised parameters: - est. lower upper -DMTA_0 97.271822 95.703157 98.84049 -k_DMTA 0.056638 0.029110 0.08417 -a.1 2.660081 2.230398 3.08976 -b.1 0.001665 -0.006911 0.01024 -SD.DMTA_0 1.545520 0.145035 2.94601 -SD.k_DMTA 0.606422 0.262274 0.95057 + est. lower upper +DMTA_0 97.271822 95.70316 98.84049 +k_DMTA 0.056638 0.02911 0.08417 +a.1 2.660081 2.27492 3.04525 +b.1 0.001665 -0.14451 0.14784 +SD.DMTA_0 1.545520 0.14301 2.94803 +SD.k_DMTA 0.606422 0.26227 0.95057 Correlation: DMTA_0 @@ -1551,13 +1537,13 @@ k_DMTA 0.0169 Random effects: est. lower upper -SD.DMTA_0 1.5455 0.1450 2.9460 +SD.DMTA_0 1.5455 0.1430 2.9480 SD.k_DMTA 0.6064 0.2623 0.9506 Variance model: - est. lower upper -a.1 2.660081 2.230398 3.08976 -b.1 0.001665 -0.006911 0.01024 + est. lower upper +a.1 2.660081 2.2749 3.0452 +b.1 0.001665 -0.1445 0.1478 Estimated disappearance times: DT50 DT90 @@ -1569,11 +1555,11 @@ DMTA 12.24 40.65 Hierarchical mkin fit of the FOMC model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:27 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1583,7 +1569,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.28 s +Fitted in 1.408 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1646,11 +1632,11 @@ DMTA 11.41 42.53 12.8 Hierarchical mkin fit of the FOMC model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:40 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA @@ -1660,7 +1646,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.793 s +Fitted in 2.735 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1693,11 +1679,11 @@ Optimised parameters: DMTA_0 99.10577 97.33296 100.87859 alpha 5.46260 2.52199 8.40321 beta 81.66080 30.46664 132.85497 -a.1 1.50219 1.23601 1.76836 -b.1 0.02893 0.02099 0.03687 -SD.DMTA_0 1.61887 -0.03636 3.27411 +a.1 1.50219 1.25801 1.74636 +b.1 0.02893 0.02048 0.03739 +SD.DMTA_0 1.61887 -0.03843 3.27618 SD.alpha 0.58145 0.17364 0.98925 -SD.beta 0.68205 0.21108 1.15303 +SD.beta 0.68205 0.21108 1.15302 Correlation: DMTA_0 alpha @@ -1706,14 +1692,14 @@ beta -0.1430 0.2467 Random effects: est. lower upper -SD.DMTA_0 1.6189 -0.03636 3.2741 +SD.DMTA_0 1.6189 -0.03843 3.2762 SD.alpha 0.5814 0.17364 0.9892 SD.beta 0.6821 0.21108 1.1530 Variance model: est. lower upper -a.1 1.50219 1.23601 1.76836 -b.1 0.02893 0.02099 0.03687 +a.1 1.50219 1.25801 1.74636 +b.1 0.02893 0.02048 0.03739 Estimated disappearance times: DT50 DT90 DT50back @@ -1725,11 +1711,11 @@ DMTA 11.05 42.81 12.89 Hierarchical mkin fit of the DFOP model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:27 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1741,7 +1727,7 @@ Data: Model predictions using solution type analytical -Fitted in 1.752 s +Fitted in 1.769 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1809,11 +1795,11 @@ DMTA 11.79 42.8 12.88 11.09 76.46 Hierarchical mkin fit of the DFOP model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:29 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:41 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1825,7 +1811,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.186 s +Fitted in 3.069 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -1860,12 +1846,12 @@ DMTA_0 98.347470 96.380815 100.31413 k1 0.064524 0.034279 0.09477 k2 0.008304 0.005843 0.01076 g 0.952128 0.909578 0.99468 -a.1 1.068907 0.868694 1.26912 -b.1 0.029265 0.022262 0.03627 -SD.DMTA_0 2.065796 0.428485 3.70311 +a.1 1.068907 0.883665 1.25415 +b.1 0.029265 0.022318 0.03621 +SD.DMTA_0 2.065796 0.427951 3.70364 SD.k1 0.583703 0.251796 0.91561 -SD.k2 0.004167 -7.832168 7.84050 -SD.g 1.064450 0.397476 1.73142 +SD.k2 0.004167 -7.831228 7.83956 +SD.g 1.064450 0.397479 1.73142 Correlation: DMTA_0 k1 k2 @@ -1875,15 +1861,15 @@ g -0.0464 -0.0269 -0.2713 Random effects: est. lower upper -SD.DMTA_0 2.065796 0.4285 3.7031 +SD.DMTA_0 2.065796 0.4280 3.7036 SD.k1 0.583703 0.2518 0.9156 -SD.k2 0.004167 -7.8322 7.8405 +SD.k2 0.004167 -7.8312 7.8396 SD.g 1.064450 0.3975 1.7314 Variance model: est. lower upper -a.1 1.06891 0.86869 1.26912 -b.1 0.02927 0.02226 0.03627 +a.1 1.06891 0.88367 1.25415 +b.1 0.02927 0.02232 0.03621 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -1895,11 +1881,11 @@ DMTA 11.39 41.36 12.45 10.74 83.48 Hierarchical mkin fit of the HS model with error model const </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:28 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:39 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -1909,7 +1895,7 @@ Data: Model predictions using solution type analytical -Fitted in 2.28 s +Fitted in 1.996 s Using 300, 100 iterations and 9 chains Variance model: Constant variance @@ -1977,11 +1963,11 @@ DMTA 8.801 67.91 20.44 8.801 31.13 Hierarchical mkin fit of the HS model with error model tc </caption> <pre><code> -saemix version used for fitting: 3.2 -mkin version used for pre-fitting: 1.2.6 -R version used for fitting: 4.3.2 -Date of fit: Thu Nov 16 04:59:29 2023 -Date of summary: Thu Nov 16 05:00:43 2023 +saemix version used for fitting: 3.3 +mkin version used for pre-fitting: 1.2.10 +R version used for fitting: 4.5.0 +Date of fit: Mon May 12 21:06:41 2025 +Date of summary: Mon May 12 21:07:51 2025 Equations: d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA @@ -1991,7 +1977,7 @@ Data: Model predictions using solution type analytical -Fitted in 3.658 s +Fitted in 3.389 s Using 300, 100 iterations and 9 chains Variance model: Two-component variance function @@ -2026,12 +2012,12 @@ DMTA_0 97.76571 95.81350 99.71791 k1 0.05855 0.03080 0.08630 k2 0.02337 0.01664 0.03010 tb 31.09638 29.38289 32.80987 -a.1 1.08835 0.88590 1.29080 -b.1 0.02964 0.02257 0.03671 -SD.DMTA_0 2.04877 0.42607 3.67147 +a.1 1.08835 0.90059 1.27611 +b.1 0.02964 0.02261 0.03667 +SD.DMTA_0 2.04877 0.42553 3.67200 SD.k1 0.59166 0.25621 0.92711 SD.k2 0.30698 0.09561 0.51835 -SD.tb 0.01274 -0.10914 0.13462 +SD.tb 0.01274 -0.10915 0.13464 Correlation: DMTA_0 k1 k2 @@ -2041,15 +2027,15 @@ tb -0.0668 -0.0103 -0.2013 Random effects: est. lower upper -SD.DMTA_0 2.04877 0.42607 3.6715 +SD.DMTA_0 2.04877 0.42553 3.6720 SD.k1 0.59166 0.25621 0.9271 SD.k2 0.30698 0.09561 0.5183 -SD.tb 0.01274 -0.10914 0.1346 +SD.tb 0.01274 -0.10915 0.1346 Variance model: est. lower upper -a.1 1.08835 0.88590 1.29080 -b.1 0.02964 0.02257 0.03671 +a.1 1.08835 0.90059 1.27611 +b.1 0.02964 0.02261 0.03667 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 @@ -2105,13 +2091,13 @@ Convergence plot for the NLHM HS fit with two-component error <div class="section level3"> <h3 id="session-info">Session info<a class="anchor" aria-label="anchor" href="#session-info"></a> </h3> -<pre><code>R version 4.3.2 (2023-10-31) -Platform: x86_64-pc-linux-gnu (64-bit) +<pre><code>R version 4.5.0 (2025-04-11) +Platform: x86_64-pc-linux-gnu Running under: Debian GNU/Linux 12 (bookworm) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 -LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 +LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0 LAPACK version 3.11.0 locale: [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C @@ -2129,53 +2115,50 @@ attached base packages: [8] base other attached packages: -[1] saemix_3.2 npde_3.3 knitr_1.42 mkin_1.2.6 +[1] rmarkdown_2.29 nvimcom_0.9-167 saemix_3.3 npde_3.5 +[5] knitr_1.49 mkin_1.2.10 loaded via a namespace (and not attached): - [1] sass_0.4.6 utf8_1.2.3 generics_0.1.3 stringi_1.7.12 - [5] lattice_0.21-8 digest_0.6.31 magrittr_2.0.3 evaluate_0.21 - [9] grid_4.3.2 fastmap_1.1.1 rprojroot_2.0.3 jsonlite_1.8.4 -[13] DBI_1.1.3 mclust_6.0.0 gridExtra_2.3 purrr_1.0.1 -[17] fansi_1.0.4 scales_1.2.1 codetools_0.2-19 textshaping_0.3.6 -[21] jquerylib_0.1.4 cli_3.6.1 rlang_1.1.1 munsell_0.5.0 -[25] cachem_1.0.8 yaml_2.3.7 tools_4.3.2 memoise_2.0.1 -[29] dplyr_1.1.2 colorspace_2.1-0 ggplot2_3.4.2 vctrs_0.6.2 -[33] R6_2.5.1 zoo_1.8-12 lifecycle_1.0.3 stringr_1.5.0 -[37] fs_1.6.2 MASS_7.3-60 ragg_1.2.5 pkgconfig_2.0.3 -[41] desc_1.4.2 pkgdown_2.0.7 bslib_0.4.2 pillar_1.9.0 -[45] gtable_0.3.3 glue_1.6.2 systemfonts_1.0.4 highr_0.10 -[49] xfun_0.39 tibble_3.2.1 lmtest_0.9-40 tidyselect_1.2.0 -[53] htmltools_0.5.5 nlme_3.1-163 rmarkdown_2.21 compiler_4.3.2 </code></pre> + [1] gtable_0.3.6 jsonlite_1.9.0 dplyr_1.1.4 compiler_4.5.0 + [5] tidyselect_1.2.1 gridExtra_2.3 jquerylib_0.1.4 systemfonts_1.2.1 + [9] scales_1.3.0 textshaping_1.0.0 yaml_2.3.10 fastmap_1.2.0 +[13] lattice_0.22-6 ggplot2_3.5.1 R6_2.6.1 generics_0.1.3 +[17] lmtest_0.9-40 MASS_7.3-65 htmlwidgets_1.6.4 tibble_3.2.1 +[21] desc_1.4.3 munsell_0.5.1 bslib_0.9.0 pillar_1.10.1 +[25] rlang_1.1.5 cachem_1.1.0 xfun_0.51 fs_1.6.5 +[29] sass_0.4.9 cli_3.6.4 pkgdown_2.1.1 magrittr_2.0.3 +[33] digest_0.6.37 grid_4.5.0 mclust_6.1.1 lifecycle_1.0.4 +[37] nlme_3.1-168 vctrs_0.6.5 evaluate_1.0.3 glue_1.8.0 +[41] codetools_0.2-20 ragg_1.3.3 zoo_1.8-13 colorspace_2.1-1 +[45] tools_4.5.0 pkgconfig_2.0.3 htmltools_0.5.8.1</code></pre> </div> <div class="section level3"> <h3 id="hardware-info">Hardware info<a class="anchor" aria-label="anchor" href="#hardware-info"></a> </h3> <pre><code>CPU model: AMD Ryzen 9 7950X 16-Core Processor</code></pre> -<pre><code>MemTotal: 64927712 kB</code></pre> +<pre><code>MemTotal: 64927780 kB</code></pre> </div> </div> - 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