From b7901aac76df753ec1213cb02bebea055965ee87 Mon Sep 17 00:00:00 2001 From: Ranke Johannes Date: Mon, 30 Oct 2023 17:09:21 +0100 Subject: Update static docs --- docs/articles/prebuilt/2022_dmta_parent.html | 475 ++++++++++----------------- 1 file changed, 171 insertions(+), 304 deletions(-) (limited to 'docs/articles/prebuilt/2022_dmta_parent.html') 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 @@ mkin - 1.2.4 + 1.2.6 @@ -73,6 +73,9 @@
  • Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P
    • +
  • + Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione +
  • Testing hierarchical pathway kinetics with residue data on cyantraniliprole
    • @@ -135,7 +138,7 @@ with residue data on dimethenamid and dimethenamid-P Ranke

    Last change on 5 January -2023, last compiled on 19 Mai 2023

    +2023, last compiled on 30 October 2023 Source: vignettes/prebuilt/2022_dmta_parent.rmd @@ -154,7 +157,7 @@ FOMC, DFOP and HS can be fitted with the mkin package.

    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.

    -

    The mkin package is used in version 1.2.4. It contains the test data +

    The mkin package is used in version 1.2.6. It contains the test data and the functions used in the evaluations. The saemix package is used as a backend for fitting the NLHM, but is also loaded to make the convergence plot function available.

    @@ -1005,7 +1008,7 @@ updated assuming two-component error.

    DFOP OK OK -C +OK OK C OK @@ -1013,7 +1016,7 @@ updated assuming two-component error.

    HS OK -C +OK OK OK OK @@ -1111,9 +1114,9 @@ the best fits.

    FOMC tc 8 -720.4 -718.8 --352.2 +720.7 +719.1 +-352.4 DFOP const @@ -1132,9 +1135,9 @@ the best fits.

    DFOP tc 10 -665.5 -663.4 --322.8 +665.7 +663.6 +-322.9 HS tc @@ -1215,12 +1218,12 @@ achieved with the argument test = TRUE to the kable(format.args = list(digits = 4)) --++-+ @@ -1238,8 +1241,8 @@ achieved with the argument test = TRUE to the - - + + @@ -1248,12 +1251,12 @@ achieved with the argument test = TRUE to the - - - - + + + + + -
    f_saem_dfop_tc_no_ranef_k2 9663.8661.9663.7661.8 -322.9 NA NA
    f_saem[[“DFOP”, “tc”]] 10665.5663.4-322.80.2809665.7663.6-322.901 10.5961
    @@ -1286,10 +1289,10 @@ Plot of the final NLHM DFOP fit 
     summary(f_saem_dfop_tc_no_ranef_k2)
    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
    + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.45 41.32 12.44 10.82 81.85

    Alternative check of parameter identifiability @@ -1462,10 +1465,10 @@ Hierarchical mkin fit of the SFO model with error model const 
    
 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
 
 
    
 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
 
 
    
 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
 
 
    
 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
 
 
    
 
    
@@ -1764,10 +1767,10 @@ Hierarchical mkin fit of the DFOP model with error model const
 
 
    
 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
 
 
    
 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
 
 
    
 
    
@@ -1934,167 +1937,28 @@ Hierarchical mkin fit of the HS model with error model const
 
 
    
 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
-
-
    
-
    
+d_DMTA/dt = - ifelse(time 
+
    
 
 Hierarchical mkin fit of the HS model with error model tc
 
 
    
 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
-
-
    
-
    
+d_DMTA/dt = - ifelse(time 
+
    
+

    Hierarchical model convergence plots @@ -2143,50 +2007,53 @@ Convergence plot for the NLHM HS fit with two-component error

    Session info

    -
    R version 4.2.3 (2023-03-15)
+
    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       
    
+ [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

    Hardware info

    -
    CPU model: AMD Ryzen 9 7950X 16-Core Processor
    -
    MemTotal:       64936316 kB
    +
    CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz
    +
    MemTotal:       247605564 kB

    -- cgit v1.2.3