From 0b754ffa91b9496bdd2f892cf3ca2bd887028dea Mon Sep 17 00:00:00 2001
From: Johannes Ranke
Date: Tue, 27 Jul 2021 18:22:01 +0200
Subject: Fix dimethenamid vignette problems and update docs
---
docs/dev/reference/dimethenamid_2018.html | 217 +++++++++++++++++++++++++++---
1 file changed, 201 insertions(+), 16 deletions(-)
(limited to 'docs/dev/reference/dimethenamid_2018.html')
diff --git a/docs/dev/reference/dimethenamid_2018.html b/docs/dev/reference/dimethenamid_2018.html
index e255765e..160dcaa3 100644
--- a/docs/dev/reference/dimethenamid_2018.html
+++ b/docs/dev/reference/dimethenamid_2018.html
@@ -77,7 +77,7 @@ constrained by data protection regulations." />
mkin
- 1.0.5
+ 1.1.0
@@ -168,7 +168,7 @@ constrained by data protection regulations.
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
-http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-5211
+https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716
Details
The R code used to create this data object is installed with this package
@@ -295,8 +295,11 @@ specific pieces of information in the comments.
#> M31 ~ add(sigma_low_M31) + prop(rsd_high_M31)
#> })
#> }
-#> <environment: 0x555559c2bd78>#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> [====|====|====|====|====|====|====|====|====|====] 0:00:02
#>
#> → calculate sensitivities
#> [====|====|====|====|====|====|====|====|====|====] 0:00:04
#>
#> → calculate ∂(f)/∂(η)
#> [====|====|====|====|====|====|====|====|====|====] 0:00:01
@@ -320,12 +323,13 @@ specific pieces of information in the comments.
#> |.....................| o5 | o6 | o7 | o8 |
#> |.....................| o9 | o10 |...........|...........|
#> calculating covariance matrix
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: S matrix non-positive definite
#> Warning: using R matrix to calculate covariance
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: S matrix non-positive definite
#> Warning: using R matrix to calculate covariance
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> user system elapsed
+#> 227.879 9.742 237.728
#> nlmixr version used for fitting: 2.0.4
-#> mkin version used for pre-fitting: 1.0.5
+#> mkin version used for pre-fitting: 1.1.0
#> R version used for fitting: 4.1.0
-#> Date of fit: Thu Jun 17 14:04:58 2021
-#> Date of summary: Thu Jun 17 14:04:58 2021
+#> Date of fit: Tue Jul 27 16:02:33 2021
+#> Date of summary: Tue Jul 27 16:02:34 2021
#>
#> Equations:
#> d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -346,7 +350,7 @@ specific pieces of information in the comments.
#>
#> Degradation model predictions using RxODE
#>
-#> Fitted in 242.937 s
+#> Fitted in 237.547 s
#>
#> Variance model: Two-component variance function
#>
@@ -480,13 +484,194 @@ specific pieces of information in the comments.
#> M23 34.99 116.24 NA NA NA
#> M27 53.05 176.23 NA NA NA
#> M31 48.48 161.05 NA NA NA
# saem has a problem with this model/data combination, maybe because of the
-# overparameterised error model, to be investigated
-#f_dmta_nlmixr_saem <- nlmixr(f_dmta_mkin_tc, est = "saem",
-# control = saemControl(print = 500))
-#summary(f_dmta_nlmixr_saem)
-#plot(f_dmta_nlmixr_saem)
-# }
+
#> Running main SAEM algorithm
+#> [1] "Tue Jul 27 16:02:34 2021"
+#> ....
+#> Minimisation finished
+#> [1] "Tue Jul 27 16:21:39 2021"
#> user system elapsed
+#> 1213.394 0.087 1213.578
#> With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 98.3427 -3.5148 -3.3187 -3.7728 -2.1163 -2.8457 0.9482 -2.8064 -2.7412 -2.8745 2.7912 0.6805 0.8213 0.8055 0.8578 1.4980 2.9309 0.2850 0.2854 0.2850 4.0990 0.3821 3.5349 0.6537 5.4143 0.0002 4.5093 0.1905
+#> 500: 97.8277 -4.3506 -4.0318 -4.1520 -3.0553 -3.5843 1.1326 -2.0873 -2.0421 -2.0751 0.2960 1.2515 0.2531 0.3807 0.7928 0.8863 6.5211 0.1433 0.1082 0.3353 0.8960 0.0470 0.7501 0.0475 0.9527 0.0281 0.7321 0.0594
#> Calculating covariance matrix
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> user system elapsed
+#> 818.782 3.808 154.926
traceplot(f_dmta_nlmixr_saem$nm)
+
#> Error in traceplot(f_dmta_nlmixr_saem$nm): could not find function "traceplot"
#> nlmixr version used for fitting: 2.0.4
+#> mkin version used for pre-fitting: 1.1.0
+#> R version used for fitting: 4.1.0
+#> Date of fit: Tue Jul 27 16:25:23 2021
+#> Date of summary: Tue Jul 27 16:25:23 2021
+#>
+#> Equations:
+#> d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
+#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
+#> * DMTA
+#> d_M23/dt = + f_DMTA_to_M23 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
+#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
+#> exp(-k2 * time))) * DMTA - k_M23 * M23
+#> d_M27/dt = + f_DMTA_to_M27 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
+#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
+#> exp(-k2 * time))) * DMTA - k_M27 * M27 + k_M31 * M31
+#> d_M31/dt = + f_DMTA_to_M31 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
+#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
+#> exp(-k2 * time))) * DMTA - k_M31 * M31
+#>
+#> Data:
+#> 568 observations of 4 variable(s) grouped in 6 datasets
+#>
+#> Degradation model predictions using RxODE
+#>
+#> Fitted in 154.632 s
+#>
+#> Variance model: Two-component variance function
+#>
+#> Mean of starting values for individual parameters:
+#> DMTA_0 log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1 f_DMTA_ilr_2
+#> 98.7698 -3.9216 -4.3377 -4.2477 0.1380 0.1393
+#> f_DMTA_ilr_3 log_k1 log_k2 g_qlogis
+#> -1.7571 -2.2341 -3.7763 0.4502
+#>
+#> Mean of starting values for error model parameters:
+#> sigma_low_DMTA rsd_high_DMTA sigma_low_M23 rsd_high_M23 sigma_low_M27
+#> 0.69793 0.02577 0.69793 0.02577 0.69793
+#> rsd_high_M27 sigma_low_M31 rsd_high_M31
+#> 0.02577 0.69793 0.02577
+#>
+#> Fixed degradation parameter values:
+#> None
+#>
+#> Results:
+#>
+#> Likelihood calculated by focei
+#> AIC BIC logLik
+#> 2036 2157 -989.8
+#>
+#> Optimised parameters:
+#> est. lower upper
+#> DMTA_0 97.828 96.121 99.535
+#> log_k_M23 -4.351 -5.300 -3.401
+#> log_k_M27 -4.032 -4.470 -3.594
+#> log_k_M31 -4.152 -4.689 -3.615
+#> log_k1 -3.055 -3.785 -2.325
+#> log_k2 -3.584 -4.517 -2.651
+#> g_qlogis 1.133 -2.165 4.430
+#> f_DMTA_tffm0_1_qlogis -2.087 -2.407 -1.768
+#> f_DMTA_tffm0_2_qlogis -2.042 -2.336 -1.748
+#> f_DMTA_tffm0_3_qlogis -2.075 -2.557 -1.593
+#>
+#> Correlation:
+#> DMTA_0 l__M23 l__M27 l__M31 log_k1 log_k2 g_qlgs
+#> log_k_M23 -0.031
+#> log_k_M27 -0.050 0.004
+#> log_k_M31 -0.032 0.003 0.078
+#> log_k1 0.014 -0.002 -0.002 -0.001
+#> log_k2 0.059 0.006 -0.001 0.002 -0.037
+#> g_qlogis -0.077 0.005 0.009 0.004 0.035 -0.201
+#> f_DMTA_tffm0_1_qlogis -0.104 0.066 0.009 0.006 0.000 -0.011 0.014
+#> f_DMTA_tffm0_2_qlogis -0.120 0.013 0.081 -0.033 -0.002 -0.013 0.017
+#> f_DMTA_tffm0_3_qlogis -0.086 0.010 0.060 0.078 -0.002 -0.005 0.010
+#> f_DMTA_0_1 f_DMTA_0_2
+#> log_k_M23
+#> log_k_M27
+#> log_k_M31
+#> log_k1
+#> log_k2
+#> g_qlogis
+#> f_DMTA_tffm0_1_qlogis
+#> f_DMTA_tffm0_2_qlogis 0.026
+#> f_DMTA_tffm0_3_qlogis 0.019 0.002
+#>
+#> Random effects (omega):
+#> eta.DMTA_0 eta.log_k_M23 eta.log_k_M27 eta.log_k_M31
+#> eta.DMTA_0 0.296 0.000 0.0000 0.0000
+#> eta.log_k_M23 0.000 1.252 0.0000 0.0000
+#> eta.log_k_M27 0.000 0.000 0.2531 0.0000
+#> eta.log_k_M31 0.000 0.000 0.0000 0.3807
+#> eta.log_k1 0.000 0.000 0.0000 0.0000
+#> eta.log_k2 0.000 0.000 0.0000 0.0000
+#> eta.g_qlogis 0.000 0.000 0.0000 0.0000
+#> eta.f_DMTA_tffm0_1_qlogis 0.000 0.000 0.0000 0.0000
+#> eta.f_DMTA_tffm0_2_qlogis 0.000 0.000 0.0000 0.0000
+#> eta.f_DMTA_tffm0_3_qlogis 0.000 0.000 0.0000 0.0000
+#> eta.log_k1 eta.log_k2 eta.g_qlogis
+#> eta.DMTA_0 0.0000 0.0000 0.000
+#> eta.log_k_M23 0.0000 0.0000 0.000
+#> eta.log_k_M27 0.0000 0.0000 0.000
+#> eta.log_k_M31 0.0000 0.0000 0.000
+#> eta.log_k1 0.7928 0.0000 0.000
+#> eta.log_k2 0.0000 0.8863 0.000
+#> eta.g_qlogis 0.0000 0.0000 6.521
+#> eta.f_DMTA_tffm0_1_qlogis 0.0000 0.0000 0.000
+#> eta.f_DMTA_tffm0_2_qlogis 0.0000 0.0000 0.000
+#> eta.f_DMTA_tffm0_3_qlogis 0.0000 0.0000 0.000
+#> eta.f_DMTA_tffm0_1_qlogis eta.f_DMTA_tffm0_2_qlogis
+#> eta.DMTA_0 0.0000 0.0000
+#> eta.log_k_M23 0.0000 0.0000
+#> eta.log_k_M27 0.0000 0.0000
+#> eta.log_k_M31 0.0000 0.0000
+#> eta.log_k1 0.0000 0.0000
+#> eta.log_k2 0.0000 0.0000
+#> eta.g_qlogis 0.0000 0.0000
+#> eta.f_DMTA_tffm0_1_qlogis 0.1433 0.0000
+#> eta.f_DMTA_tffm0_2_qlogis 0.0000 0.1082
+#> eta.f_DMTA_tffm0_3_qlogis 0.0000 0.0000
+#> eta.f_DMTA_tffm0_3_qlogis
+#> eta.DMTA_0 0.0000
+#> eta.log_k_M23 0.0000
+#> eta.log_k_M27 0.0000
+#> eta.log_k_M31 0.0000
+#> eta.log_k1 0.0000
+#> eta.log_k2 0.0000
+#> eta.g_qlogis 0.0000
+#> eta.f_DMTA_tffm0_1_qlogis 0.0000
+#> eta.f_DMTA_tffm0_2_qlogis 0.0000
+#> eta.f_DMTA_tffm0_3_qlogis 0.3353
+#>
+#> Variance model:
+#> sigma_low_DMTA rsd_high_DMTA sigma_low_M23 rsd_high_M23 sigma_low_M27
+#> 0.89603 0.04704 0.75015 0.04753 0.95265
+#> rsd_high_M27 sigma_low_M31 rsd_high_M31
+#> 0.02810 0.73212 0.05942
+#>
+#> Backtransformed parameters:
+#> est. lower upper
+#> DMTA_0 97.82774 96.120503 99.53498
+#> k_M23 0.01290 0.004991 0.03334
+#> k_M27 0.01774 0.011451 0.02749
+#> k_M31 0.01573 0.009195 0.02692
+#> f_DMTA_to_M23 0.11033 NA NA
+#> f_DMTA_to_M27 0.10218 NA NA
+#> f_DMTA_to_M31 0.08784 NA NA
+#> k1 0.04711 0.022707 0.09773
+#> k2 0.02775 0.010918 0.07056
+#> g 0.75632 0.102960 0.98823
+#>
+#> Resulting formation fractions:
+#> ff
+#> DMTA_M23 0.11033
+#> DMTA_M27 0.10218
+#> DMTA_M31 0.08784
+#> DMTA_sink 0.69965
+#>
+#> Estimated disappearance times:
+#> DT50 DT90 DT50back DT50_k1 DT50_k2
+#> DMTA 16.59 57.44 17.29 14.71 24.97
+#> M23 53.74 178.51 NA NA NA
+#> M27 39.07 129.78 NA NA NA
+#> M31 44.06 146.36 NA NA NA
# }