From af7c6de4db9981ac814362c441fbac22c8faa2d7 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 24 Nov 2022 09:02:26 +0100 Subject: Start online docs of the development version --- docs/dev/articles/FOCUS_D.html | 411 ++--- .../articles/FOCUS_D_files/figure-html/plot-1.png | Bin 79176 -> 79834 bytes .../FOCUS_D_files/figure-html/plot_2-1.png | Bin 24025 -> 24334 bytes docs/dev/articles/FOCUS_L.html | 84 +- docs/dev/articles/index.html | 2 +- docs/dev/articles/mkin.html | 4 +- docs/dev/articles/twa.html | 41 +- docs/dev/articles/web_only/FOCUS_Z.html | 402 ++--- .../figure-html/FOCUS_2006_Z_fits_1-1.png | Bin 66640 -> 66689 bytes .../figure-html/FOCUS_2006_Z_fits_10-1.png | Bin 106038 -> 105896 bytes .../figure-html/FOCUS_2006_Z_fits_11-1.png | Bin 105042 -> 104793 bytes .../figure-html/FOCUS_2006_Z_fits_11a-1.png | Bin 75626 -> 75230 bytes .../figure-html/FOCUS_2006_Z_fits_11b-1.png | Bin 35744 -> 36314 bytes .../figure-html/FOCUS_2006_Z_fits_2-1.png | Bin 66640 -> 66689 bytes .../figure-html/FOCUS_2006_Z_fits_3-1.png | Bin 66424 -> 66448 bytes .../figure-html/FOCUS_2006_Z_fits_5-1.png | Bin 80520 -> 80373 bytes .../figure-html/FOCUS_2006_Z_fits_6-1.png | Bin 105149 -> 105210 bytes .../figure-html/FOCUS_2006_Z_fits_7-1.png | Bin 104479 -> 104538 bytes .../figure-html/FOCUS_2006_Z_fits_9-1.png | Bin 88890 -> 88801 bytes docs/dev/articles/web_only/NAFTA_examples.html | 1611 ++++++++++---------- .../NAFTA_examples_files/figure-html/p10-1.png | Bin 78793 -> 79758 bytes .../NAFTA_examples_files/figure-html/p11-1.png | Bin 75470 -> 76315 bytes .../NAFTA_examples_files/figure-html/p12a-1.png | Bin 80755 -> 81697 bytes .../NAFTA_examples_files/figure-html/p12b-1.png | Bin 69885 -> 70800 bytes .../NAFTA_examples_files/figure-html/p13-1.png | Bin 77126 -> 78121 bytes .../NAFTA_examples_files/figure-html/p14-1.png | Bin 79693 -> 80656 bytes .../NAFTA_examples_files/figure-html/p15a-1.png | Bin 75945 -> 76925 bytes .../NAFTA_examples_files/figure-html/p15b-1.png | Bin 78004 -> 78968 bytes .../NAFTA_examples_files/figure-html/p16-1.png | Bin 93075 -> 93950 bytes .../NAFTA_examples_files/figure-html/p5a-1.png | Bin 81521 -> 82665 bytes .../NAFTA_examples_files/figure-html/p5b-1.png | Bin 79783 -> 80721 bytes .../NAFTA_examples_files/figure-html/p6-1.png | Bin 81974 -> 83052 bytes .../NAFTA_examples_files/figure-html/p7-1.png | Bin 101606 -> 102568 bytes .../NAFTA_examples_files/figure-html/p8-1.png | Bin 91429 -> 92407 bytes .../NAFTA_examples_files/figure-html/p9a-1.png | Bin 77612 -> 78605 bytes .../NAFTA_examples_files/figure-html/p9b-1.png | Bin 75129 -> 76240 bytes docs/dev/articles/web_only/benchmarks.html | 55 +- docs/dev/articles/web_only/compiled_models.html | 25 +- docs/dev/articles/web_only/dimethenamid_2018.html | 50 +- docs/dev/articles/web_only/multistart.html | 13 +- .../figure-html/unnamed-chunk-3-1.png | Bin 59586 -> 64470 bytes .../figure-html/unnamed-chunk-4-1.png | Bin 55154 -> 58448 bytes .../figure-html/unnamed-chunk-5-1.png | Bin 21455 -> 21853 bytes .../figure-html/unnamed-chunk-6-1.png | Bin 54302 -> 52343 bytes docs/dev/articles/web_only/saem_benchmarks.html | 85 +- 45 files changed, 1468 insertions(+), 1315 deletions(-) (limited to 'docs/dev/articles') diff --git a/docs/dev/articles/FOCUS_D.html b/docs/dev/articles/FOCUS_D.html index a35a255a..a7617d55 100644 --- a/docs/dev/articles/FOCUS_D.html +++ b/docs/dev/articles/FOCUS_D.html @@ -20,6 +20,8 @@ + +
+

Example evaluation of FOCUS Example Dataset D

-

Johannes Ranke

+

Johannes Ranke

-

Last change 31 January 2019 (rebuilt 2021-02-15)

+

Last change 31 January 2019 (rebuilt 2022-11-24)

- Source: vignettes/FOCUS_D.rmd + Source: vignettes/FOCUS_D.rmd
@@ -112,207 +123,207 @@

This is just a very simple vignette showing how to fit a degradation model for a parent compound with one transformation product using mkin. After loading the library we look at the data. We have observed concentrations in the column named value at the times specified in column time for the two observed variables named parent and m1.

-library(mkin, quietly = TRUE)
-print(FOCUS_2006_D)
-
##      name time  value
-## 1  parent    0  99.46
-## 2  parent    0 102.04
-## 3  parent    1  93.50
-## 4  parent    1  92.50
-## 5  parent    3  63.23
-## 6  parent    3  68.99
-## 7  parent    7  52.32
-## 8  parent    7  55.13
-## 9  parent   14  27.27
-## 10 parent   14  26.64
-## 11 parent   21  11.50
-## 12 parent   21  11.64
-## 13 parent   35   2.85
-## 14 parent   35   2.91
-## 15 parent   50   0.69
-## 16 parent   50   0.63
-## 17 parent   75   0.05
-## 18 parent   75   0.06
-## 19 parent  100     NA
-## 20 parent  100     NA
-## 21 parent  120     NA
-## 22 parent  120     NA
-## 23     m1    0   0.00
-## 24     m1    0   0.00
-## 25     m1    1   4.84
-## 26     m1    1   5.64
-## 27     m1    3  12.91
-## 28     m1    3  12.96
-## 29     m1    7  22.97
-## 30     m1    7  24.47
-## 31     m1   14  41.69
-## 32     m1   14  33.21
-## 33     m1   21  44.37
-## 34     m1   21  46.44
-## 35     m1   35  41.22
-## 36     m1   35  37.95
-## 37     m1   50  41.19
-## 38     m1   50  40.01
-## 39     m1   75  40.09
-## 40     m1   75  33.85
-## 41     m1  100  31.04
-## 42     m1  100  33.13
-## 43     m1  120  25.15
-## 44     m1  120  33.31
+library(mkin, quietly = TRUE) +print(FOCUS_2006_D)
+
##      name time  value
+## 1  parent    0  99.46
+## 2  parent    0 102.04
+## 3  parent    1  93.50
+## 4  parent    1  92.50
+## 5  parent    3  63.23
+## 6  parent    3  68.99
+## 7  parent    7  52.32
+## 8  parent    7  55.13
+## 9  parent   14  27.27
+## 10 parent   14  26.64
+## 11 parent   21  11.50
+## 12 parent   21  11.64
+## 13 parent   35   2.85
+## 14 parent   35   2.91
+## 15 parent   50   0.69
+## 16 parent   50   0.63
+## 17 parent   75   0.05
+## 18 parent   75   0.06
+## 19 parent  100     NA
+## 20 parent  100     NA
+## 21 parent  120     NA
+## 22 parent  120     NA
+## 23     m1    0   0.00
+## 24     m1    0   0.00
+## 25     m1    1   4.84
+## 26     m1    1   5.64
+## 27     m1    3  12.91
+## 28     m1    3  12.96
+## 29     m1    7  22.97
+## 30     m1    7  24.47
+## 31     m1   14  41.69
+## 32     m1   14  33.21
+## 33     m1   21  44.37
+## 34     m1   21  46.44
+## 35     m1   35  41.22
+## 36     m1   35  37.95
+## 37     m1   50  41.19
+## 38     m1   50  40.01
+## 39     m1   75  40.09
+## 40     m1   75  33.85
+## 41     m1  100  31.04
+## 42     m1  100  33.13
+## 43     m1  120  25.15
+## 44     m1  120  33.31

Next we specify the degradation model: The parent compound degrades with simple first-order kinetics (SFO) to one metabolite named m1, which also degrades with SFO kinetics.

The call to mkinmod returns a degradation model. The differential equations represented in R code can be found in the character vector $diffs of the mkinmod object. If a C compiler (gcc) is installed and functional, the differential equation model will be compiled from auto-generated C code.

-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
-
## Temporary DLL for differentials generated and loaded
+SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
+
## Temporary DLL for differentials generated and loaded
-print(SFO_SFO$diffs)
-
##                                                    parent 
-##                          "d_parent = - k_parent * parent" 
-##                                                        m1 
-## "d_m1 = + f_parent_to_m1 * k_parent * parent - k_m1 * m1"
+print(SFO_SFO$diffs)
+
##                                                    parent 
+##                          "d_parent = - k_parent * parent" 
+##                                                        m1 
+## "d_m1 = + f_parent_to_m1 * k_parent * parent - k_m1 * m1"

We do the fitting without progress report (quiet = TRUE).

-fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
-
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE): Observations with value
-## of zero were removed from the data
+fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE): Observations with value
+## of zero were removed from the data

A plot of the fit including a residual plot for both observed variables is obtained using the plot_sep method for mkinfit objects, which shows separate graphs for all compounds and their residuals.

-plot_sep(fit, lpos = c("topright", "bottomright"))
+plot_sep(fit, lpos = c("topright", "bottomright"))

Confidence intervals for the parameter estimates are obtained using the mkinparplot function.

-mkinparplot(fit)
+mkinparplot(fit)

A comprehensive report of the results is obtained using the summary method for mkinfit objects.

-summary(fit)
-
## mkin version used for fitting:    1.0.3.9000 
-## R version used for fitting:       4.0.3 
-## Date of fit:     Mon Feb 15 17:13:36 2021 
-## Date of summary: Mon Feb 15 17:13:37 2021 
-## 
-## Equations:
-## d_parent/dt = - k_parent * parent
-## d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 401 model solutions performed in 0.161 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##                   value   type
-## parent_0       100.7500  state
-## k_parent         0.1000 deparm
-## k_m1             0.1001 deparm
-## f_parent_to_m1   0.5000 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##                      value lower upper
-## parent_0        100.750000  -Inf   Inf
-## log_k_parent     -2.302585  -Inf   Inf
-## log_k_m1         -2.301586  -Inf   Inf
-## f_parent_qlogis   0.000000  -Inf   Inf
-## 
-## Fixed parameter values:
-##      value  type
-## m1_0     0 state
-## 
-## 
-## Warning(s): 
-## Observations with value of zero were removed from the data
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   204.4486 212.6365 -97.22429
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##                 Estimate Std. Error   Lower    Upper
-## parent_0        99.60000    1.57000 96.4000 102.8000
-## log_k_parent    -2.31600    0.04087 -2.3990  -2.2330
-## log_k_m1        -5.24700    0.13320 -5.5180  -4.9770
-## f_parent_qlogis  0.05792    0.08926 -0.1237   0.2395
-## sigma            3.12600    0.35850  2.3960   3.8550
-## 
-## Parameter correlation:
-##                   parent_0 log_k_parent   log_k_m1 f_parent_qlogis      sigma
-## parent_0         1.000e+00    5.174e-01 -1.688e-01      -5.471e-01 -1.172e-06
-## log_k_parent     5.174e-01    1.000e+00 -3.263e-01      -5.426e-01 -8.483e-07
-## log_k_m1        -1.688e-01   -3.263e-01  1.000e+00       7.478e-01  8.205e-07
-## f_parent_qlogis -5.471e-01   -5.426e-01  7.478e-01       1.000e+00  1.305e-06
-## sigma           -1.172e-06   -8.483e-07  8.205e-07       1.305e-06  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##                 Estimate t value    Pr(>t)     Lower     Upper
-## parent_0       99.600000  63.430 2.298e-36 96.400000 1.028e+02
-## k_parent        0.098700  24.470 4.955e-23  0.090820 1.073e-01
-## k_m1            0.005261   7.510 6.165e-09  0.004012 6.898e-03
-## f_parent_to_m1  0.514500  23.070 3.104e-22  0.469100 5.596e-01
-## sigma           3.126000   8.718 2.235e-10  2.396000 3.855e+00
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   6.398       4 15
-## parent     6.459       2  7
-## m1         4.690       2  8
-## 
-## Resulting formation fractions:
-##                 ff
-## parent_m1   0.5145
-## parent_sink 0.4855
-## 
-## Estimated disappearance times:
-##           DT50   DT90
-## parent   7.023  23.33
-## m1     131.761 437.70
-## 
-## Data:
-##  time variable observed predicted   residual
-##     0   parent    99.46  99.59848 -1.385e-01
-##     0   parent   102.04  99.59848  2.442e+00
-##     1   parent    93.50  90.23787  3.262e+00
-##     1   parent    92.50  90.23787  2.262e+00
-##     3   parent    63.23  74.07319 -1.084e+01
-##     3   parent    68.99  74.07319 -5.083e+00
-##     7   parent    52.32  49.91207  2.408e+00
-##     7   parent    55.13  49.91207  5.218e+00
-##    14   parent    27.27  25.01258  2.257e+00
-##    14   parent    26.64  25.01258  1.627e+00
-##    21   parent    11.50  12.53462 -1.035e+00
-##    21   parent    11.64  12.53462 -8.946e-01
-##    35   parent     2.85   3.14787 -2.979e-01
-##    35   parent     2.91   3.14787 -2.379e-01
-##    50   parent     0.69   0.71624 -2.624e-02
-##    50   parent     0.63   0.71624 -8.624e-02
-##    75   parent     0.05   0.06074 -1.074e-02
-##    75   parent     0.06   0.06074 -7.382e-04
-##     1       m1     4.84   4.80296  3.704e-02
-##     1       m1     5.64   4.80296  8.370e-01
-##     3       m1    12.91  13.02400 -1.140e-01
-##     3       m1    12.96  13.02400 -6.400e-02
-##     7       m1    22.97  25.04476 -2.075e+00
-##     7       m1    24.47  25.04476 -5.748e-01
-##    14       m1    41.69  36.69003  5.000e+00
-##    14       m1    33.21  36.69003 -3.480e+00
-##    21       m1    44.37  41.65310  2.717e+00
-##    21       m1    46.44  41.65310  4.787e+00
-##    35       m1    41.22  43.31313 -2.093e+00
-##    35       m1    37.95  43.31313 -5.363e+00
-##    50       m1    41.19  41.21832 -2.832e-02
-##    50       m1    40.01  41.21832 -1.208e+00
-##    75       m1    40.09  36.44704  3.643e+00
-##    75       m1    33.85  36.44704 -2.597e+00
-##   100       m1    31.04  31.98162 -9.416e-01
-##   100       m1    33.13  31.98162  1.148e+00
-##   120       m1    25.15  28.78984 -3.640e+00
-##   120       m1    33.31  28.78984  4.520e+00
+summary(fit) +
## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:04 2022 
+## Date of summary: Thu Nov 24 08:12:05 2022 
+## 
+## Equations:
+## d_parent/dt = - k_parent * parent
+## d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
+## 
+## Model predictions using solution type analytical 
+## 
+## Fitted using 401 model solutions performed in 0.152 s
+## 
+## Error model: Constant variance 
+## 
+## Error model algorithm: OLS 
+## 
+## Starting values for parameters to be optimised:
+##                   value   type
+## parent_0       100.7500  state
+## k_parent         0.1000 deparm
+## k_m1             0.1001 deparm
+## f_parent_to_m1   0.5000 deparm
+## 
+## Starting values for the transformed parameters actually optimised:
+##                      value lower upper
+## parent_0        100.750000  -Inf   Inf
+## log_k_parent     -2.302585  -Inf   Inf
+## log_k_m1         -2.301586  -Inf   Inf
+## f_parent_qlogis   0.000000  -Inf   Inf
+## 
+## Fixed parameter values:
+##      value  type
+## m1_0     0 state
+## 
+## 
+## Warning(s): 
+## Observations with value of zero were removed from the data
+## 
+## Results:
+## 
+##        AIC      BIC    logLik
+##   204.4486 212.6365 -97.22429
+## 
+## Optimised, transformed parameters with symmetric confidence intervals:
+##                 Estimate Std. Error   Lower    Upper
+## parent_0        99.60000    1.57000 96.4000 102.8000
+## log_k_parent    -2.31600    0.04087 -2.3990  -2.2330
+## log_k_m1        -5.24700    0.13320 -5.5180  -4.9770
+## f_parent_qlogis  0.05792    0.08926 -0.1237   0.2395
+## sigma            3.12600    0.35850  2.3960   3.8550
+## 
+## Parameter correlation:
+##                   parent_0 log_k_parent   log_k_m1 f_parent_qlogis      sigma
+## parent_0         1.000e+00    5.174e-01 -1.688e-01      -5.471e-01 -1.172e-06
+## log_k_parent     5.174e-01    1.000e+00 -3.263e-01      -5.426e-01 -8.483e-07
+## log_k_m1        -1.688e-01   -3.263e-01  1.000e+00       7.478e-01  8.205e-07
+## f_parent_qlogis -5.471e-01   -5.426e-01  7.478e-01       1.000e+00  1.305e-06
+## sigma           -1.172e-06   -8.483e-07  8.205e-07       1.305e-06  1.000e+00
+## 
+## Backtransformed parameters:
+## Confidence intervals for internally transformed parameters are asymmetric.
+## t-test (unrealistically) based on the assumption of normal distribution
+## for estimators of untransformed parameters.
+##                 Estimate t value    Pr(>t)     Lower     Upper
+## parent_0       99.600000  63.430 2.298e-36 96.400000 1.028e+02
+## k_parent        0.098700  24.470 4.955e-23  0.090820 1.073e-01
+## k_m1            0.005261   7.510 6.165e-09  0.004012 6.898e-03
+## f_parent_to_m1  0.514500  23.070 3.104e-22  0.469100 5.596e-01
+## sigma           3.126000   8.718 2.235e-10  2.396000 3.855e+00
+## 
+## FOCUS Chi2 error levels in percent:
+##          err.min n.optim df
+## All data   6.398       4 15
+## parent     6.459       2  7
+## m1         4.690       2  8
+## 
+## Resulting formation fractions:
+##                 ff
+## parent_m1   0.5145
+## parent_sink 0.4855
+## 
+## Estimated disappearance times:
+##           DT50   DT90
+## parent   7.023  23.33
+## m1     131.761 437.70
+## 
+## Data:
+##  time variable observed predicted   residual
+##     0   parent    99.46  99.59848 -1.385e-01
+##     0   parent   102.04  99.59848  2.442e+00
+##     1   parent    93.50  90.23787  3.262e+00
+##     1   parent    92.50  90.23787  2.262e+00
+##     3   parent    63.23  74.07319 -1.084e+01
+##     3   parent    68.99  74.07319 -5.083e+00
+##     7   parent    52.32  49.91207  2.408e+00
+##     7   parent    55.13  49.91207  5.218e+00
+##    14   parent    27.27  25.01258  2.257e+00
+##    14   parent    26.64  25.01258  1.627e+00
+##    21   parent    11.50  12.53462 -1.035e+00
+##    21   parent    11.64  12.53462 -8.946e-01
+##    35   parent     2.85   3.14787 -2.979e-01
+##    35   parent     2.91   3.14787 -2.379e-01
+##    50   parent     0.69   0.71624 -2.624e-02
+##    50   parent     0.63   0.71624 -8.624e-02
+##    75   parent     0.05   0.06074 -1.074e-02
+##    75   parent     0.06   0.06074 -7.382e-04
+##     1       m1     4.84   4.80296  3.704e-02
+##     1       m1     5.64   4.80296  8.370e-01
+##     3       m1    12.91  13.02400 -1.140e-01
+##     3       m1    12.96  13.02400 -6.400e-02
+##     7       m1    22.97  25.04476 -2.075e+00
+##     7       m1    24.47  25.04476 -5.748e-01
+##    14       m1    41.69  36.69003  5.000e+00
+##    14       m1    33.21  36.69003 -3.480e+00
+##    21       m1    44.37  41.65310  2.717e+00
+##    21       m1    46.44  41.65310  4.787e+00
+##    35       m1    41.22  43.31313 -2.093e+00
+##    35       m1    37.95  43.31313 -5.363e+00
+##    50       m1    41.19  41.21832 -2.832e-02
+##    50       m1    40.01  41.21832 -1.208e+00
+##    75       m1    40.09  36.44704  3.643e+00
+##    75       m1    33.85  36.44704 -2.597e+00
+##   100       m1    31.04  31.98162 -9.416e-01
+##   100       m1    33.13  31.98162  1.148e+00
+##   120       m1    25.15  28.78984 -3.640e+00
+##   120       m1    33.31  28.78984  4.520e+00
@@ -63,11 +63,14 @@ Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models
  • - Example evaluation of FOCUS Example Dataset Z + Short demo of the multistart method
  • Performance benefit by using compiled model definitions in mkin
    • +
  • + Example evaluation of FOCUS Example Dataset Z +
  • Calculation of time weighted average concentrations with mkin
    • @@ -75,7 +78,10 @@ Example evaluation of NAFTA SOP Attachment examples
  • - Some benchmark timings + Benchmark timings for mkin +
    • +
  • + Benchmark timings for saem.mmkin
    • @@ -106,7 +112,7 @@

    Example evaluation of FOCUS Laboratory Data L1 to L3

    Johannes Ranke

    -

    Last change 18 May 2022 (rebuilt 2022-09-16)

    +

    Last change 18 May 2022 (rebuilt 2022-11-24)

    Source: vignettes/FOCUS_L.rmd @@ -132,17 +138,17 @@ 
     m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
 summary(m.L1.SFO)
    -
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:35 2022 
-## Date of summary: Fri Sep 16 10:31:35 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:09 2022 
+## Date of summary: Thu Nov 24 08:12:09 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 133 model solutions performed in 0.032 s
+## Fitted using 133 model solutions performed in 0.033 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -238,17 +244,17 @@
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:36 2022 
-## Date of summary: Fri Sep 16 10:31:36 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:09 2022 
+## Date of summary: Thu Nov 24 08:12:09 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 369 model solutions performed in 0.081 s
+## Fitted using 369 model solutions performed in 0.091 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -350,17 +356,17 @@
 
    
 
     summary(m.L2.FOMC, data = FALSE)
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:36 2022 
-## Date of summary: Fri Sep 16 10:31:36 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:10 2022 
+## Date of summary: Thu Nov 24 08:12:10 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 239 model solutions performed in 0.049 s
+## Fitted using 239 model solutions performed in 0.048 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -431,10 +437,10 @@
 
    
 
     summary(m.L2.DFOP, data = FALSE)
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:37 2022 
-## Date of summary: Fri Sep 16 10:31:37 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:10 2022 
+## Date of summary: Thu Nov 24 08:12:10 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -443,7 +449,7 @@
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 581 model solutions performed in 0.132 s
+## Fitted using 581 model solutions performed in 0.13 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -537,10 +543,10 @@
 
    We can extract the summary and plot for e.g. the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.
    
 
     summary(mm.L3[["DFOP", 1]])
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:37 2022 
-## Date of summary: Fri Sep 16 10:31:38 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:11 2022 
+## Date of summary: Thu Nov 24 08:12:11 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -549,7 +555,7 @@
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 376 model solutions performed in 0.079 s
+## Fitted using 376 model solutions performed in 0.078 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -650,17 +656,17 @@
 
    The \(\chi^2\) error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the \(\chi^2\) test passes is slightly lower for the FOMC model. However, the difference appears negligible.
    
 
     summary(mm.L4[["SFO", 1]], data = FALSE)
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:38 2022 
-## Date of summary: Fri Sep 16 10:31:38 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:12 2022 
+## Date of summary: Thu Nov 24 08:12:12 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 142 model solutions performed in 0.03 s
+## Fitted using 142 model solutions performed in 0.029 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -715,17 +721,17 @@
 ## parent  106  352
    
 
     summary(mm.L4[["FOMC", 1]], data = FALSE)
    
-
    ## mkin version used for fitting:    1.1.2 
-## R version used for fitting:       4.2.1 
-## Date of fit:     Fri Sep 16 10:31:38 2022 
-## Date of summary: Fri Sep 16 10:31:38 2022 
+
    ## mkin version used for fitting:    1.2.2 
+## R version used for fitting:       4.2.2 
+## Date of fit:     Thu Nov 24 08:12:12 2022 
+## Date of summary: Thu Nov 24 08:12:12 2022 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 224 model solutions performed in 0.045 s
+## Fitted using 224 model solutions performed in 0.044 s
 ## 
 ## Error model: Constant variance 
 ## 
diff --git a/docs/dev/articles/index.html b/docs/dev/articles/index.html
index 395b5f7c..e04302ef 100644
--- a/docs/dev/articles/index.html
+++ b/docs/dev/articles/index.html
@@ -17,7 +17,7 @@
       
       
         mkin
-        1.2.0
+        1.2.2
       
     
 
diff --git a/docs/dev/articles/mkin.html b/docs/dev/articles/mkin.html
index 27e532af..df4df718 100644
--- a/docs/dev/articles/mkin.html
+++ b/docs/dev/articles/mkin.html
@@ -34,7 +34,7 @@
       
       
         mkin
-        1.2.0
+        1.2.2
       
     
 
@@ -112,7 +112,7 @@
       
    Introduction to mkin
    
                         
    Johannes Ranke
    
             
-            
    Last change 15 February 2021 (rebuilt 2022-11-16)
    
+            
    Last change 15 February 2021 (rebuilt 2022-11-24)
    
       
       Source: vignettes/mkin.rmd
       
diff --git a/docs/dev/articles/twa.html b/docs/dev/articles/twa.html
index 30eeb5a6..673d753a 100644
--- a/docs/dev/articles/twa.html
+++ b/docs/dev/articles/twa.html
@@ -20,6 +20,8 @@
 
 
 
+    
+
     
    
       
    
+      
    
   
    
     
    
       
    Calculation of time weighted average concentrations with mkin
    
-                        
    Johannes Ranke
    
+                        
    Johannes Ranke
    
             
-            
    Last change 18 September 2019 (rebuilt 2021-02-15)
    
+            
    Last change 18 September 2019 (rebuilt 2022-11-24)
    
       
-      Source: vignettes/twa.rmd
+      Source: vignettes/twa.rmd
       
 
     
    
@@ -141,10 +152,10 @@
 
    \[f_\textrm{twa} = \frac{1}{t} \left(
   \frac{1}{k_1} \left( 1 - e^{- k_1 t_b} \right) +
   \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)} \right)  \right) \]
    
-
    Note that a method for calculating maximum moving window time weighted average concentrations for a model fitted by ‘mkinfit’ or from parent decline model parameters is included in the max_twa_parent() function. If the same is needed for metabolites, the function pfm::max_twa() from the ‘pfm’ package can be used.
    
+
    Note that a method for calculating maximum moving window time weighted average concentrations for a model fitted by ‘mkinfit’ or from parent decline model parameters is included in the max_twa_parent() function. If the same is needed for metabolites, the function pfm::max_twa() from the ‘pfm’ package can be used.
    
 
    
 
    
-
    FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in Eu Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
    
+
    FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in Eu Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
    
 
    
 
    
   
    
@@ -158,11 +169,13 @@
 
 
       
    
-  
    Developed by Johannes Ranke.
    
+  
    
+
    Developed by Johannes Ranke.
    
 
    
 
 
    
-  
    Site built with pkgdown 1.6.1.
    
+  
    
+
    Site built with pkgdown 2.0.6.
    
 
    
 
       
    
@@ -171,5 +184,7 @@
   
 
 
+  
+
   
 
diff --git a/docs/dev/articles/web_only/FOCUS_Z.html b/docs/dev/articles/web_only/FOCUS_Z.html
index 694b33ca..eec1ba66 100644
--- a/docs/dev/articles/web_only/FOCUS_Z.html
+++ b/docs/dev/articles/web_only/FOCUS_Z.html
@@ -20,6 +20,8 @@
 
 
 
+    
+
     
    
       
    
+      
    
   
    
     
    
       
    Example evaluation of FOCUS dataset Z
    
-                        
    Johannes Ranke
    
+                        
    Johannes Ranke
    
             
-            
    Last change 16 January 2018 (rebuilt 2021-02-15)
    
+            
    Last change 16 January 2018 (rebuilt 2022-11-24)
    
       
-      Source: vignettes/web_only/FOCUS_Z.rmd
+      Source: vignettes/web_only/FOCUS_Z.rmd
       
 
     
    
 
     
     
-
    Wissenschaftlicher Berater, Kronacher Str. 12, 79639 Grenzach-Wyhlen, Germany
    Privatdozent at the University of Bremen
    
-
    
-
    
-The data
    
+
    Wissenschaftlicher Berater, Kronacher Str. 12, 79639 Grenzach-Wyhlen, Germany
    Privatdozent at the University of Bremen
    
+
    
+
    The data
+
    
 
    The following code defines the example dataset from Appendix 7 to the FOCUS kinetics report (FOCUS Work Group on Degradation Kinetics 2014, 354).
    
 
    -library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
+library(mkin, quietly = TRUE)
+LOD = 0.5
+FOCUS_2006_Z = data.frame(
+  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
+        42, 61, 96, 124),
+  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
+         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
+  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
+         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
+
+FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
 
-
    
-
    
-Parent and one metabolite
    
+
    
+
    Parent and one metabolite
+
    
 
    The next step is to set up the models used for the kinetic analysis. As the simultaneous fit of parent and the first metabolite is usually straightforward, Step 1 (SFO for parent only) is skipped here. We start with the model 2a, with formation and decline of metabolite Z1 and the pathway from parent directly to sink included (default in mkin).
    
 
    -Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
+Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                Z1 = mkinsub("SFO"))
    
+
    ## Temporary DLL for differentials generated and loaded
    
 
    -m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
+m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    ## Warning in mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    
 
    -plot_sep(m.Z.2a)
    
+plot_sep(m.Z.2a)
    
 
    
 
    -summary(m.Z.2a, data = FALSE)$bpar
    
-
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
-## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
-## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
-## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
-## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
+summary(m.Z.2a, data = FALSE)$bpar
    
+
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
+## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
+## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
+## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
+## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
+## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
 
    As obvious from the parameter summary (the  component of the summary), the kinetic rate constant from parent compound Z to sink is very small and the t-test for this parameter suggests that it is not significantly different from zero. This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify the model by removing the pathway to sink.
    
 
    A similar result can be obtained when formation fractions are used in the model formulation:
    
 
    -Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
+Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                   Z1 = mkinsub("SFO"),
+                   use_of_ff = "max")
    
+
    ## Temporary DLL for differentials generated and loaded
    
 
    -m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
+m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    ## Warning in mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    
 
    -plot_sep(m.Z.2a.ff)
    
+plot_sep(m.Z.2a.ff)
    
 
    
 
    -summary(m.Z.2a.ff, data = FALSE)$bpar
    
-
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
-## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
-## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
-## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
-## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
+summary(m.Z.2a.ff, data = FALSE)$bpar
    
+
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
+## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
+## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
+## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
+## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
+## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
 
    Here, the ilr transformed formation fraction fitted in the model takes a very large value, and the backtransformed formation fraction from parent Z to Z1 is practically unity. Here, the covariance matrix used for the calculation of confidence intervals is not returned as the model is overparameterised.
    
 
    A simplified model is obtained by removing the pathway to the sink. 
    
 
    In the following, we use the parameterisation with formation fractions in order to be able to compare with the results in the FOCUS guidance, and as it makes it easier to use parameters obtained in a previous fit when adding a further metabolite.
    
 
    -Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
+Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
+
    ## Temporary DLL for differentials generated and loaded
    
 
    -m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
+m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    ## Warning in mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    
 
    -plot_sep(m.Z.3)
    
+plot_sep(m.Z.3)
    
 
    
 
    -summary(m.Z.3, data = FALSE)$bpar
    
-
    ##       Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0  97.01488   2.597342  37.352 2.0106e-24 91.67597 102.3538
-## k_Z0   2.23601   0.146904  15.221 9.1477e-15  1.95354   2.5593
-## k_Z1   0.48212   0.041727  11.554 4.8268e-12  0.40355   0.5760
-## sigma  4.80411   0.620208   7.746 1.6110e-08  3.52925   6.0790
    
+summary(m.Z.3, data = FALSE)$bpar
    +
    ##       Estimate se_notrans t value     Pr(>t)    Lower    Upper
+## Z0_0  97.01488   2.597342  37.352 2.0106e-24 91.67597 102.3538
+## k_Z0   2.23601   0.146904  15.221 9.1477e-15  1.95354   2.5593
+## k_Z1   0.48212   0.041727  11.554 4.8268e-12  0.40355   0.5760
+## sigma  4.80411   0.620208   7.746 1.6110e-08  3.52925   6.0790

    As there is only one transformation product for Z0 and no pathway to sink, the formation fraction is internally fixed to unity.

    -
    -

    -Metabolites Z2 and Z3

    +
    +

    Metabolites Z2 and Z3 +

    As suggested in the FOCUS report, the pathway to sink was removed for metabolite Z1 as well in the next step. While this step appears questionable on the basis of the above results, it is followed here for the purpose of comparison. Also, in the FOCUS report, it is assumed that there is additional empirical evidence that Z1 quickly and exclusively hydrolyses to Z2.

    -Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO"), use_of_ff = "max")
    +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    -
    ## Warning in mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    +m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    ## Warning in mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    -plot_sep(m.Z.5)
    +plot_sep(m.Z.5)

    Finally, metabolite Z3 is added to the model. We use the optimised differential equation parameter values from the previous fit in order to accelerate the optimization.

    -Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO", "Z3"), + Z3 = mkinsub("SFO"), + use_of_ff = "max") +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
    -
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, :
-## Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation did not converge:
-## false convergence (8)
    +m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, + parms.ini = m.Z.5$bparms.ode, + quiet = TRUE) +
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, :
+## Observations with value of zero were removed from the data
    +
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation did not converge:
+## false convergence (8)
    -plot_sep(m.Z.FOCUS)
    +plot_sep(m.Z.FOCUS) 

    -summary(m.Z.FOCUS, data = FALSE)$bpar
    -
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.838822   1.994274 48.5584 4.0280e-42 92.826981 100.850664
-## k_Z0        2.215393   0.118458 18.7019 1.0413e-23  1.989456   2.466989
-## k_Z1        0.478305   0.028258 16.9266 6.2418e-22  0.424708   0.538666
-## k_Z2        0.451627   0.042139 10.7176 1.6314e-14  0.374339   0.544872
-## k_Z3        0.058692   0.015245  3.8499 1.7803e-04  0.034808   0.098965
-## f_Z2_to_Z3  0.471502   0.058351  8.0805 9.6608e-11  0.357769   0.588274
-## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736
    +summary(m.Z.FOCUS, data = FALSE)$bpar +
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
+## Z0_0       96.838822   1.994274 48.5584 4.0280e-42 92.826981 100.850664
+## k_Z0        2.215393   0.118458 18.7019 1.0413e-23  1.989456   2.466989
+## k_Z1        0.478305   0.028258 16.9266 6.2418e-22  0.424708   0.538666
+## k_Z2        0.451627   0.042139 10.7176 1.6314e-14  0.374339   0.544872
+## k_Z3        0.058692   0.015245  3.8499 1.7803e-04  0.034808   0.098965
+## f_Z2_to_Z3  0.471502   0.058351  8.0805 9.6608e-11  0.357769   0.588274
+## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736
    -endpoints(m.Z.FOCUS)
    -
    ## $ff
-##   Z2_Z3 Z2_sink 
-##  0.4715  0.5285 
-## 
-## $distimes
-##        DT50    DT90
-## Z0  0.31288  1.0394
-## Z1  1.44917  4.8141
-## Z2  1.53478  5.0984
-## Z3 11.80986 39.2315
    +endpoints(m.Z.FOCUS) +
    ## $ff
+##   Z2_Z3 Z2_sink 
+##  0.4715  0.5285 
+## 
+## $distimes
+##        DT50    DT90
+## Z0  0.31288  1.0394
+## Z1  1.44917  4.8141
+## Z2  1.53478  5.0984
+## Z3 11.80986 39.2315

    This fit corresponds to the final result chosen in Appendix 7 of the FOCUS report. Confidence intervals returned by mkin are based on internally transformed parameters, however.

    -
    -

    -Using the SFORB model

    +
    +

    Using the SFORB model +

    As the FOCUS report states, there is a certain tailing of the time course of metabolite Z3. Also, the time course of the parent compound is not fitted very well using the SFO model, as residues at a certain low level remain.

    Therefore, an additional model is offered here, using the single first-order reversible binding (SFORB) model for metabolite Z3. As expected, the \(\chi^2\) error level is lower for metabolite Z3 using this model and the graphical fit for Z3 is improved. However, the covariance matrix is not returned.

    -Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO", "Z3"), + Z3 = mkinsub("SFORB"))
    +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    -
    ## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    +m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    ## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    -plot_sep(m.Z.mkin.1)
    +plot_sep(m.Z.mkin.1) 

    -summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    -
    ## NULL
    +summary(m.Z.mkin.1, data = FALSE)$cov.unscaled +
    ## NULL

    Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the assumption that the model fit for the parent compound can be improved by using the SFORB model.

    -Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO")) +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    -
    ## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    +m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE) +
    ## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
+## value of zero were removed from the data
    -plot_sep(m.Z.mkin.3)
    +plot_sep(m.Z.mkin.3)

    This results in a much better representation of the behaviour of the parent compound Z0.

    Finally, Z3 is added as well. These models appear overparameterised (no covariance matrix returned) if the sink for Z1 is left in the models.

    -Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO", "Z3"), + Z3 = mkinsub("SFO")) +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
    -
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 3$bparms.ode, : Observations with value of zero were removed from the data
    +m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, + parms.ini = m.Z.mkin.3$bparms.ode, + quiet = TRUE) +
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini =
+## m.Z.mkin.3$bparms.ode, : Observations with value of zero were removed from the
+## data
    -plot_sep(m.Z.mkin.4)
    +plot_sep(m.Z.mkin.4)

    The error level of the fit, but especially of metabolite Z3, can be improved if the SFORB model is chosen for this metabolite, as this model is capable of representing the tailing of the metabolite decline phase.

    -Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    -
    ## Temporary DLL for differentials generated and loaded
    +Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE), + Z1 = mkinsub("SFO", "Z2", sink = FALSE), + Z2 = mkinsub("SFO", "Z3"), + Z3 = mkinsub("SFORB")) +
    ## Temporary DLL for differentials generated and loaded
    -m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 4$bparms.ode[1:4], : Observations with value of zero were removed from the data
    +m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, + parms.ini = m.Z.mkin.4$bparms.ode[1:4], + quiet = TRUE) +
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini =
+## m.Z.mkin.4$bparms.ode[1:4], : Observations with value of zero were removed from
+## the data
    -plot_sep(m.Z.mkin.5)
    +plot_sep(m.Z.mkin.5)

    The summary view of the backtransformed parameters shows that we get no confidence intervals due to overparameterisation. As the optimized is excessively small, it seems reasonable to fix it to zero.

    -m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = c(m.Z.mkin.
-## 5$bparms.ode[1:7], : Observations with value of zero were removed from the data
    +m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, + parms.ini = c(m.Z.mkin.5$bparms.ode[1:7], + k_Z3_bound_free = 0), + fixed_parms = "k_Z3_bound_free", + quiet = TRUE) +
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini =
+## c(m.Z.mkin.5$bparms.ode[1:7], : Observations with value of zero were removed
+## from the data
    -plot_sep(m.Z.mkin.5a)
    +plot_sep(m.Z.mkin.5a)

    As expected, the residual plots for Z0 and Z3 are more random than in the case of the all SFO model for which they were shown above. In conclusion, the model is proposed as the best-fit model for the dataset from Appendix 7 of the FOCUS report.

    A graphical representation of the confidence intervals can finally be obtained.

    -mkinparplot(m.Z.mkin.5a)
    +mkinparplot(m.Z.mkin.5a)

    The endpoints obtained with this model are

    -endpoints(m.Z.mkin.5a)
    -
    ## $ff
-## Z0_free   Z2_Z3 Z2_sink Z3_free 
-## 1.00000 0.53656 0.46344 1.00000 
-## 
-## $SFORB
-##     Z0_b1     Z0_b2     Z3_b1     Z3_b2 
-## 2.4471322 0.0075125 0.0800069 0.0000000 
-## 
-## $distimes
-##      DT50   DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
-## Z0 0.3043 1.1848  0.35666    0.28325     92.266         NA         NA
-## Z1 1.5148 5.0320       NA         NA         NA         NA         NA
-## Z2 1.6414 5.4526       NA         NA         NA         NA         NA
-## Z3     NA     NA       NA         NA         NA     8.6636        Inf
    +endpoints(m.Z.mkin.5a) +
    ## $ff
+## Z0_free   Z2_Z3 Z2_sink Z3_free 
+## 1.00000 0.53656 0.46344 1.00000 
+## 
+## $SFORB
+##     Z0_b1     Z0_b2      Z0_g     Z3_b1     Z3_b2      Z3_g 
+## 2.4471322 0.0075125 0.9519862 0.0800069 0.0000000 0.9347820 
+## 
+## $distimes
+##      DT50   DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
+## Z0 0.3043 1.1848  0.35666    0.28325     92.266         NA         NA
+## Z1 1.5148 5.0320       NA         NA         NA         NA         NA
+## Z2 1.6414 5.4526       NA         NA         NA         NA         NA
+## Z3     NA     NA       NA         NA         NA     8.6636        Inf

    It is clear the degradation rate of Z3 towards the end of the experiment is very low as DT50_Z3_b2 (the second Eigenvalue of the system of two differential equations representing the SFORB system for Z3, corresponding to the slower rate constant of the DFOP model) is reported to be infinity. However, this appears to be a feature of the data.

    -
    -

    -References

    +
    +

    References +

    -

    FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in Eu Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.

    +

    FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in Eu Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.

    @@ -385,11 +399,13 @@
    -

    Developed by Johannes Ranke.

    +

    +

    Developed by Johannes Ranke.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.6.

    @@ -398,5 +414,7 @@ + + diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png index 2213c446..be652d31 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png index 61b04d3a..bc6efaf7 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png index 409f1203..55c1b645 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png index 4d6820cd..8e63cd04 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png index 2e504961..3902e059 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png index 2213c446..be652d31 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png index 7ab743af..59524035 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png index 2e0dce77..d95cac25 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png index 458299c1..cb333a1c 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png index eb833066..d87105fb 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png index e7501cbb..db807f14 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png differ diff --git a/docs/dev/articles/web_only/NAFTA_examples.html b/docs/dev/articles/web_only/NAFTA_examples.html index b9784415..a054d4a1 100644 --- a/docs/dev/articles/web_only/NAFTA_examples.html +++ b/docs/dev/articles/web_only/NAFTA_examples.html @@ -20,6 +20,8 @@ + +
    +

    Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance

    -

    Johannes Ranke

    +

    Johannes Ranke

    -

    26 February 2019 (rebuilt 2021-02-15)

    +

    26 February 2019 (rebuilt 2022-11-24)

    - Source: vignettes/web_only/NAFTA_examples.rmd + Source: vignettes/web_only/NAFTA_examples.rmd
    -
    -

    -Introduction

    +
    +

    Introduction +

    In this document, the example evaluations provided in Attachment 1 to the SOP of US EPA for using the NAFTA guidance (US EPA 2015) are repeated using mkin. The original evaluations reported in the attachment were performed using PestDF in version 0.8.4. Note that PestDF 0.8.13 is the version distributed at the US EPA website today (2019-02-26).

    The datasets are now distributed with the mkin package.

    -
    -

    -Examples where DFOP did not converge with PestDF 0.8.4

    +
    +

    Examples where DFOP did not converge with PestDF 0.8.4 +

    In attachment 1, it is reported that the DFOP model does not converge for these datasets when PestDF 0.8.4 was used. For all four datasets, the DFOP model can be fitted with mkin (see below). The negative half-life given by PestDF 0.8.4 for these fits appears to be the result of a bug. The results for the other two models (SFO and IORE) are the same.

    -
    -

    -Example on page 5, upper panel

    +
    +

    Example on page 5, upper panel +

    -p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p5a)
    +plot(p5a)

    -print(p5a)
    -
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 465.21753  56.27506  32.06401 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 64.4304
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  95.8401 4.67e-21 92.245 99.4357
-## k_parent   0.0102 3.92e-12  0.009  0.0117
-## sigma      4.8230 3.81e-06  3.214  6.4318
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       1.01e+02     NA 9.91e+01 1.02e+02
-## k__iore_parent 1.54e-05     NA 4.08e-06 5.84e-05
-## N_parent       2.57e+00     NA 2.25e+00 2.89e+00
-## sigma          1.68e+00     NA 1.12e+00 2.24e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 9.99e+01 1.41e-26 98.8116 101.0810
-## k1       2.67e-02 5.05e-06  0.0243   0.0295
-## k2       2.26e-12 5.00e-01  0.0000      Inf
-## g        6.47e-01 3.67e-06  0.6248   0.6677
-## sigma    1.27e+00 8.91e-06  0.8395   1.6929
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  67.7 2.25e+02 6.77e+01
-## IORE 58.2 1.07e+03 3.22e+02
-## DFOP 55.5 5.59e+11 3.07e+11
-## 
-## Representative half-life:
-## [1] 321.51
    +print(p5a)
    +
    ## Sums of squares:
+##       SFO      IORE      DFOP 
+## 465.21753  56.27506  32.06401 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 64.4304
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)  Lower   Upper
+## parent_0  95.8401 4.67e-21 92.245 99.4357
+## k_parent   0.0102 3.92e-12  0.009  0.0117
+## sigma      4.8230 3.81e-06  3.214  6.4318
+## 
+## $IORE
+##                Estimate Pr(>t)    Lower    Upper
+## parent_0       1.01e+02     NA 9.91e+01 1.02e+02
+## k__iore_parent 1.54e-05     NA 4.08e-06 5.84e-05
+## N_parent       2.57e+00     NA 2.25e+00 2.89e+00
+## sigma          1.68e+00     NA 1.12e+00 2.24e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 9.99e+01 1.41e-26 98.8116 101.0810
+## k1       2.67e-02 5.05e-06  0.0243   0.0295
+## k2       2.26e-12 5.00e-01  0.0000      Inf
+## g        6.47e-01 3.67e-06  0.6248   0.6677
+## sigma    1.27e+00 8.91e-06  0.8395   1.6929
+## 
+## 
+## DTx values:
+##      DT50     DT90 DT50_rep
+## SFO  67.7 2.25e+02 6.77e+01
+## IORE 58.2 1.07e+03 3.22e+02
+## DFOP 55.5 5.59e+11 3.07e+11
+## 
+## Representative half-life:
+## [1] 321.51
    -
    -

    -Example on page 5, lower panel

    +
    +

    Example on page 5, lower panel +

    -p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p5b)
    +plot(p5b)

    -print(p5b)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 94.81123 10.10936  7.55871 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 11.77879
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0   96.497 2.32e-24 94.85271 98.14155
-## k_parent    0.008 3.42e-14  0.00737  0.00869
-## sigma       2.295 1.22e-05  1.47976  3.11036
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.85e+01 1.17e-28 9.79e+01 9.92e+01
-## k__iore_parent 1.53e-04 6.50e-03 7.21e-05 3.26e-04
-## N_parent       1.94e+00 5.88e-13 1.76e+00 2.12e+00
-## sigma          7.49e-01 1.63e-05 4.82e-01 1.02e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 9.84e+01 1.24e-27 97.8078 98.9187
-## k1       1.55e-02 4.10e-04  0.0143  0.0167
-## k2       8.63e-12 5.00e-01  0.0000     Inf
-## g        6.89e-01 2.92e-03  0.6626  0.7142
-## sigma    6.48e-01 2.38e-05  0.4147  0.8813
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  86.6 2.88e+02 8.66e+01
-## IORE 85.5 7.17e+02 2.16e+02
-## DFOP 83.6 1.32e+11 8.04e+10
-## 
-## Representative half-life:
-## [1] 215.87
    +print(p5b)
    +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 94.81123 10.10936  7.55871 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 11.77879
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0   96.497 2.32e-24 94.85271 98.14155
+## k_parent    0.008 3.42e-14  0.00737  0.00869
+## sigma       2.295 1.22e-05  1.47976  3.11036
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower    Upper
+## parent_0       9.85e+01 1.17e-28 9.79e+01 9.92e+01
+## k__iore_parent 1.53e-04 6.50e-03 7.21e-05 3.26e-04
+## N_parent       1.94e+00 5.88e-13 1.76e+00 2.12e+00
+## sigma          7.49e-01 1.63e-05 4.82e-01 1.02e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0 9.84e+01 1.24e-27 97.8078 98.9187
+## k1       1.55e-02 4.10e-04  0.0143  0.0167
+## k2       8.63e-12 5.00e-01  0.0000     Inf
+## g        6.89e-01 2.92e-03  0.6626  0.7142
+## sigma    6.48e-01 2.38e-05  0.4147  0.8813
+## 
+## 
+## DTx values:
+##      DT50     DT90 DT50_rep
+## SFO  86.6 2.88e+02 8.66e+01
+## IORE 85.5 7.17e+02 2.16e+02
+## DFOP 83.6 1.32e+11 8.04e+10
+## 
+## Representative half-life:
+## [1] 215.87
    -
    -

    -Example on page 6

    +
    +

    Example on page 6 +

    -p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p6)
    +plot(p6)

    -print(p6)
    -
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 188.45361  51.00699  42.46931 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 58.39888
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7759 7.29e-24 92.3478 97.2039
-## k_parent   0.0179 8.02e-16  0.0166  0.0194
-## sigma      3.0696 3.81e-06  2.0456  4.0936
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       97.12446 2.63e-26 95.62461 98.62431
-## k__iore_parent  0.00252 1.95e-03  0.00134  0.00472
-## N_parent        1.49587 4.07e-13  1.33896  1.65279
-## sigma           1.59698 5.05e-06  1.06169  2.13227
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 9.66e+01 1.57e-25 95.3476 97.8979
-## k1       2.55e-02 7.33e-06  0.0233  0.0278
-## k2       3.22e-11 5.00e-01  0.0000     Inf
-## g        8.61e-01 7.55e-06  0.8314  0.8867
-## sigma    1.46e+00 6.93e-06  0.9661  1.9483
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  38.6 1.28e+02 3.86e+01
-## IORE 34.0 1.77e+02 5.32e+01
-## DFOP 34.1 1.01e+10 2.15e+10
-## 
-## Representative half-life:
-## [1] 53.17
    +print(p6)
    +
    ## Sums of squares:
+##       SFO      IORE      DFOP 
+## 188.45361  51.00699  42.46931 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 58.39888
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  94.7759 7.29e-24 92.3478 97.2039
+## k_parent   0.0179 8.02e-16  0.0166  0.0194
+## sigma      3.0696 3.81e-06  2.0456  4.0936
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower    Upper
+## parent_0       97.12446 2.63e-26 95.62461 98.62431
+## k__iore_parent  0.00252 1.95e-03  0.00134  0.00472
+## N_parent        1.49587 4.07e-13  1.33896  1.65279
+## sigma           1.59698 5.05e-06  1.06169  2.13227
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0 9.66e+01 1.57e-25 95.3476 97.8979
+## k1       2.55e-02 7.33e-06  0.0233  0.0278
+## k2       3.22e-11 5.00e-01  0.0000     Inf
+## g        8.61e-01 7.55e-06  0.8314  0.8867
+## sigma    1.46e+00 6.93e-06  0.9661  1.9483
+## 
+## 
+## DTx values:
+##      DT50     DT90 DT50_rep
+## SFO  38.6 1.28e+02 3.86e+01
+## IORE 34.0 1.77e+02 5.32e+01
+## DFOP 34.1 1.01e+10 2.15e+10
+## 
+## Representative half-life:
+## [1] 53.17
    -
    -

    -Example on page 7

    +
    +

    Example on page 7 +

    -p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p7)
    +plot(p7)

    -print(p7)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 3661.661 3195.030 3174.145 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 3334.194
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 96.41796 4.80e-53 93.32245 99.51347
-## k_parent  0.00735 7.64e-21  0.00641  0.00843
-## sigma     7.94557 1.83e-15  6.46713  9.42401
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       9.92e+01     NA 9.55e+01 1.03e+02
-## k__iore_parent 1.60e-05     NA 1.45e-07 1.77e-03
-## N_parent       2.45e+00     NA 1.35e+00 3.54e+00
-## sigma          7.42e+00     NA 6.04e+00 8.80e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 9.89e+01 9.44e-49 95.4640 102.2573
-## k1       1.81e-02 1.75e-01  0.0116   0.0281
-## k2       3.63e-10 5.00e-01  0.0000      Inf
-## g        6.06e-01 2.19e-01  0.4826   0.7178
-## sigma    7.40e+00 2.97e-15  6.0201   8.7754
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  94.3 3.13e+02 9.43e+01
-## IORE 96.7 1.51e+03 4.55e+02
-## DFOP 96.4 3.77e+09 1.91e+09
-## 
-## Representative half-life:
-## [1] 454.55
    +print(p7)
    +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 3661.661 3195.030 3174.145 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 3334.194
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 96.41796 4.80e-53 93.32245 99.51347
+## k_parent  0.00735 7.64e-21  0.00641  0.00843
+## sigma     7.94557 1.83e-15  6.46713  9.42401
+## 
+## $IORE
+##                Estimate Pr(>t)    Lower    Upper
+## parent_0       9.92e+01     NA 9.55e+01 1.03e+02
+## k__iore_parent 1.60e-05     NA 1.45e-07 1.77e-03
+## N_parent       2.45e+00     NA 1.35e+00 3.54e+00
+## sigma          7.42e+00     NA 6.04e+00 8.80e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 9.89e+01 9.44e-49 95.4640 102.2573
+## k1       1.81e-02 1.75e-01  0.0116   0.0281
+## k2       3.63e-10 5.00e-01  0.0000      Inf
+## g        6.06e-01 2.19e-01  0.4826   0.7178
+## sigma    7.40e+00 2.97e-15  6.0201   8.7754
+## 
+## 
+## DTx values:
+##      DT50     DT90 DT50_rep
+## SFO  94.3 3.13e+02 9.43e+01
+## IORE 96.7 1.51e+03 4.55e+02
+## DFOP 96.4 3.77e+09 1.91e+09
+## 
+## Representative half-life:
+## [1] 454.55
    -
    -

    -Examples where the representative half-life deviates from the observed DT50

    -
    -

    -Example on page 8

    +
    +

    Examples where the representative half-life deviates from the observed DT50 +

    +
    +

    Example on page 8 +

    For this dataset, the IORE fit does not converge when the default starting values used by mkin for the IORE model are used. Therefore, a lower value for the rate constant is used here.

    -p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p8)
    +plot(p8)

    -print(p8)
    -
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 1996.9408  444.9237  547.5616 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 477.4924
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 88.16549 6.53e-29 83.37344 92.95754
-## k_parent  0.00803 1.67e-13  0.00674  0.00957
-## sigma     7.44786 4.17e-10  5.66209  9.23363
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.77e+01 7.03e-35 9.44e+01 1.01e+02
-## k__iore_parent 6.14e-05 3.20e-02 2.12e-05 1.78e-04
-## N_parent       2.27e+00 4.23e-18 2.00e+00 2.54e+00
-## sigma          3.52e+00 5.36e-10 2.67e+00 4.36e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 95.70619 8.99e-32 91.87941 99.53298
-## k1        0.02500 5.25e-04  0.01422  0.04394
-## k2        0.00273 6.84e-03  0.00125  0.00597
-## g         0.58835 2.84e-06  0.36595  0.77970
-## sigma     3.90001 6.94e-10  2.96260  4.83741
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  86.3  287     86.3
-## IORE 53.4  668    201.0
-## DFOP 55.6  517    253.0
-## 
-## Representative half-life:
-## [1] 201.03
    +print(p8)
    +
    ## Sums of squares:
+##       SFO      IORE      DFOP 
+## 1996.9408  444.9237  547.5616 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 477.4924
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 88.16549 6.53e-29 83.37344 92.95754
+## k_parent  0.00803 1.67e-13  0.00674  0.00957
+## sigma     7.44786 4.17e-10  5.66209  9.23363
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower    Upper
+## parent_0       9.77e+01 7.03e-35 9.44e+01 1.01e+02
+## k__iore_parent 6.14e-05 3.20e-02 2.12e-05 1.78e-04
+## N_parent       2.27e+00 4.23e-18 2.00e+00 2.54e+00
+## sigma          3.52e+00 5.36e-10 2.67e+00 4.36e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 95.70619 8.99e-32 91.87941 99.53298
+## k1        0.02500 5.25e-04  0.01422  0.04394
+## k2        0.00273 6.84e-03  0.00125  0.00597
+## g         0.58835 2.84e-06  0.36595  0.77970
+## sigma     3.90001 6.94e-10  2.96260  4.83741
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  86.3  287     86.3
+## IORE 53.4  668    201.0
+## DFOP 55.6  517    253.0
+## 
+## Representative half-life:
+## [1] 201.03
    -
    -

    -Examples where SFO was not selected for an abiotic study

    -
    -

    -Example on page 9, upper panel

    +
    +

    Examples where SFO was not selected for an abiotic study +

    +
    +

    Example on page 9, upper panel +

    -p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p9a)
    +plot(p9a)

    -print(p9a)
    -
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 839.35238  88.57064   9.93363 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 105.5678
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  88.1933 3.06e-12 79.9447 96.4419
-## k_parent   0.0409 2.07e-07  0.0324  0.0516
-## sigma      7.2429 3.92e-05  4.4768 10.0090
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.89e+01 1.12e-16 9.54e+01 1.02e+02
-## k__iore_parent 1.93e-05 1.13e-01 3.49e-06 1.06e-04
-## N_parent       2.91e+00 1.45e-09 2.50e+00 3.32e+00
-## sigma          2.35e+00 5.31e-05 1.45e+00 3.26e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)  Lower  Upper
-## parent_0 9.85e+01 2.54e-20 97.390 99.672
-## k1       1.38e-01 3.52e-05  0.131  0.146
-## k2       9.02e-13 5.00e-01  0.000    Inf
-## g        6.52e-01 8.13e-06  0.642  0.661
-## sigma    7.88e-01 6.13e-02  0.481  1.095
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  16.9 5.63e+01 1.69e+01
-## IORE 11.6 3.37e+02 1.01e+02
-## DFOP 10.5 1.38e+12 7.69e+11
-## 
-## Representative half-life:
-## [1] 101.43
    +print(p9a)
    +
    ## Sums of squares:
+##       SFO      IORE      DFOP 
+## 839.35238  88.57064   9.93363 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 105.5678
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  88.1933 3.06e-12 79.9447 96.4419
+## k_parent   0.0409 2.07e-07  0.0324  0.0516
+## sigma      7.2429 3.92e-05  4.4768 10.0090
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower    Upper
+## parent_0       9.89e+01 1.12e-16 9.54e+01 1.02e+02
+## k__iore_parent 1.93e-05 1.13e-01 3.49e-06 1.06e-04
+## N_parent       2.91e+00 1.45e-09 2.50e+00 3.32e+00
+## sigma          2.35e+00 5.31e-05 1.45e+00 3.26e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)  Lower  Upper
+## parent_0 9.85e+01 2.54e-20 97.390 99.672
+## k1       1.38e-01 3.52e-05  0.131  0.146
+## k2       9.02e-13 5.00e-01  0.000    Inf
+## g        6.52e-01 8.13e-06  0.642  0.661
+## sigma    7.88e-01 6.13e-02  0.481  1.095
+## 
+## 
+## DTx values:
+##      DT50     DT90 DT50_rep
+## SFO  16.9 5.63e+01 1.69e+01
+## IORE 11.6 3.37e+02 1.01e+02
+## DFOP 10.5 1.38e+12 7.69e+11
+## 
+## Representative half-life:
+## [1] 101.43

    In this example, the residuals of the SFO indicate a lack of fit of this model, so even if it was an abiotic experiment, the data do not suggest a simple exponential decline.

    -
    -

    -Example on page 9, lower panel

    +
    +

    Example on page 9, lower panel +

    -p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    -
    ## Warning in sqrt(diag(covar)): NaNs produced
    -
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    -
    ## Warning in sqrt(1/diag(V)): NaNs produced
    -
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    +
    ## Warning in sqrt(diag(covar)): NaNs produced
    +
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    +
    ## Warning in sqrt(1/diag(V)): NaNs produced
    +
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p9b)
    +plot(p9b)

    -print(p9b)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 35.64867 23.22334 35.64867 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 28.54188
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  94.7123 2.15e-19 93.178 96.2464
-## k_parent   0.0389 4.47e-14  0.037  0.0408
-## sigma      1.5957 1.28e-04  0.932  2.2595
-## 
-## $IORE
-##                Estimate   Pr(>t)   Lower  Upper
-## parent_0         93.863 2.32e-18 92.4565 95.269
-## k__iore_parent    0.127 1.85e-02  0.0504  0.321
-## N_parent          0.711 1.88e-05  0.4843  0.937
-## sigma             1.288 1.76e-04  0.7456  1.830
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7123 1.61e-16 93.1355 96.2891
-## k1         0.0389 1.08e-04  0.0266  0.0569
-## k2         0.0389 2.23e-04  0.0255  0.0592
-## g          0.5256      NaN      NA      NA
-## sigma      1.5957 2.50e-04  0.9135  2.2779
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  17.8 59.2     17.8
-## IORE 18.4 49.2     14.8
-## DFOP 17.8 59.2     17.8
-## 
-## Representative half-life:
-## [1] 14.8
    +print(p9b) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 35.64867 23.22334 35.64867 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 28.54188
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)  Lower   Upper
+## parent_0  94.7123 2.15e-19 93.178 96.2464
+## k_parent   0.0389 4.47e-14  0.037  0.0408
+## sigma      1.5957 1.28e-04  0.932  2.2595
+## 
+## $IORE
+##                Estimate   Pr(>t)   Lower  Upper
+## parent_0         93.863 2.32e-18 92.4565 95.269
+## k__iore_parent    0.127 1.85e-02  0.0504  0.321
+## N_parent          0.711 1.88e-05  0.4843  0.937
+## sigma             1.288 1.76e-04  0.7456  1.830
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  94.7123 1.61e-16 93.1355 96.2891
+## k1         0.0389 1.08e-04  0.0266  0.0569
+## k2         0.0389 2.23e-04  0.0255  0.0592
+## g          0.5256      NaN      NA      NA
+## sigma      1.5957 2.50e-04  0.9135  2.2779
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  17.8 59.2     17.8
+## IORE 18.4 49.2     14.8
+## DFOP 17.8 59.2     17.8
+## 
+## Representative half-life:
+## [1] 14.8

    Here, mkin gives a longer slow DT50 for the DFOP model (17.8 days) than PestDF (13.5 days). Presumably, this is related to the fact that PestDF gives a negative value for the proportion of the fast degradation which should be between 0 and 1, inclusive. This parameter is called f in PestDF and g in mkin. In mkin, it is restricted to the interval from 0 to 1.

    -
    -

    -Example on page 10

    +
    +

    Example on page 10 +

    -p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    -
    ## Warning in sqrt(diag(covar)): NaNs produced
    -
    ## Warning in sqrt(1/diag(V)): NaNs produced
    -
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    +
    ## Warning in sqrt(diag(covar)): NaNs produced
    +
    ## Warning in sqrt(1/diag(V)): NaNs produced
    +
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p10)
    +plot(p10)

    -print(p10)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 899.4089 336.4348 899.4089 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 413.4841
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 101.7315 6.42e-11 91.9259 111.5371
-## k_parent   0.0495 1.70e-07  0.0404   0.0607
-## sigma      8.0152 1.28e-04  4.6813  11.3491
-## 
-## $IORE
-##                Estimate   Pr(>t)  Lower   Upper
-## parent_0          96.86 3.32e-12 90.848 102.863
-## k__iore_parent     2.96 7.91e-02  0.687  12.761
-## N_parent           0.00 5.00e-01 -0.372   0.372
-## sigma              4.90 1.77e-04  2.837   6.968
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 101.7315 1.41e-09 91.6534 111.8097
-## k1         0.0495 6.58e-03  0.0303   0.0809
-## k2         0.0495 2.60e-03  0.0410   0.0598
-## g          0.4487 5.00e-01      NA       NA
-## sigma      8.0152 2.50e-04  4.5886  11.4418
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  14.0 46.5    14.00
-## IORE 16.4 29.4     8.86
-## DFOP 14.0 46.5    14.00
-## 
-## Representative half-life:
-## [1] 8.86
    +print(p10) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 899.4089 336.4348 899.4089 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 413.4841
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 101.7315 6.42e-11 91.9259 111.5371
+## k_parent   0.0495 1.70e-07  0.0404   0.0607
+## sigma      8.0152 1.28e-04  4.6813  11.3491
+## 
+## $IORE
+##                Estimate   Pr(>t)  Lower   Upper
+## parent_0          96.86 3.32e-12 90.848 102.863
+## k__iore_parent     2.96 7.91e-02  0.687  12.761
+## N_parent           0.00 5.00e-01 -0.372   0.372
+## sigma              4.90 1.77e-04  2.837   6.968
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 101.7315 1.41e-09 91.6534 111.8097
+## k1         0.0495 6.58e-03  0.0303   0.0809
+## k2         0.0495 2.60e-03  0.0410   0.0598
+## g          0.4487 5.00e-01      NA       NA
+## sigma      8.0152 2.50e-04  4.5886  11.4418
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  14.0 46.5    14.00
+## IORE 16.4 29.4     8.86
+## DFOP 14.0 46.5    14.00
+## 
+## Representative half-life:
+## [1] 8.86

    Here, a value below N is given for the IORE model, because the data suggests a faster decline towards the end of the experiment, which appears physically rather unlikely in the case of a photolysis study. It seems PestDF does not constrain N to values above zero, thus the slight difference in IORE model parameters between PestDF and mkin.

    -
    -

    -The DT50 was not observed during the study

    -
    -

    -Example on page 11

    +
    +

    The DT50 was not observed during the study +

    +
    +

    Example on page 11 +

    -p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p11)
    +plot(p11)

    -print(p11)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 579.6805 204.7932 144.7783 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 251.6944
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 96.15820 4.83e-13 90.24934 1.02e+02
-## k_parent  0.00321 4.71e-05  0.00222 4.64e-03
-## sigma     6.43473 1.28e-04  3.75822 9.11e+00
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       1.05e+02     NA 9.90e+01 1.10e+02
-## k__iore_parent 3.11e-17     NA 1.35e-20 7.18e-14
-## N_parent       8.36e+00     NA 6.62e+00 1.01e+01
-## sigma          3.82e+00     NA 2.21e+00 5.44e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.05e+02 9.47e-13  99.9990 109.1224
-## k1       4.41e-02 5.95e-03   0.0296   0.0658
-## k2       9.94e-13 5.00e-01   0.0000      Inf
-## g        3.22e-01 1.45e-03   0.2814   0.3650
-## sigma    3.22e+00 3.52e-04   1.8410   4.5906
-## 
-## 
-## DTx values:
-##          DT50     DT90 DT50_rep
-## SFO  2.16e+02 7.18e+02 2.16e+02
-## IORE 9.73e+02 1.37e+08 4.11e+07
-## DFOP 3.07e+11 1.93e+12 6.98e+11
-## 
-## Representative half-life:
-## [1] 41148170
    +print(p11)
    +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 579.6805 204.7932 144.7783 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 251.6944
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 96.15820 4.83e-13 90.24934 1.02e+02
+## k_parent  0.00321 4.71e-05  0.00222 4.64e-03
+## sigma     6.43473 1.28e-04  3.75822 9.11e+00
+## 
+## $IORE
+##                Estimate Pr(>t)    Lower    Upper
+## parent_0       1.05e+02     NA 9.90e+01 1.10e+02
+## k__iore_parent 3.11e-17     NA 1.35e-20 7.18e-14
+## N_parent       8.36e+00     NA 6.62e+00 1.01e+01
+## sigma          3.82e+00     NA 2.21e+00 5.44e+00
+## 
+## $DFOP
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 1.05e+02 9.47e-13  99.9990 109.1224
+## k1       4.41e-02 5.95e-03   0.0296   0.0658
+## k2       9.94e-13 5.00e-01   0.0000      Inf
+## g        3.22e-01 1.45e-03   0.2814   0.3650
+## sigma    3.22e+00 3.52e-04   1.8410   4.5906
+## 
+## 
+## DTx values:
+##          DT50     DT90 DT50_rep
+## SFO  2.16e+02 7.18e+02 2.16e+02
+## IORE 9.73e+02 1.37e+08 4.11e+07
+## DFOP 3.07e+11 1.93e+12 6.98e+11
+## 
+## Representative half-life:
+## [1] 41148170

    In this case, the DFOP fit reported for PestDF resulted in a negative value for the slower rate constant, which is not possible in mkin. The other results are in agreement.

    -
    -

    -N is less than 1 and the DFOP rate constants are like the SFO rate constant

    +
    +

    N is less than 1 and the DFOP rate constants are like the SFO rate constant +

    In the following three examples, the same results are obtained with mkin as reported for PestDF. As in the case on page 10, the N values below 1 are deemed unrealistic and appear to be the result of an overparameterisation.

    -
    -

    -Example on page 12, upper panel

    +
    +

    Example on page 12, upper panel +

    -p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    -
    ## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
-## matrix
    -
    ## Warning in sqrt(diag(covar)): NaNs produced
    -
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    -
    ## Warning in sqrt(1/diag(V)): NaNs produced
    -
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    +
    ## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
+## matrix
    +
    ## Warning in sqrt(diag(covar)): NaNs produced
    +
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    +
    ## Warning in sqrt(1/diag(V)): NaNs produced
    +
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p12a)
    +plot(p12a)

    -print(p12a)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 695.4440 220.0685 695.4440 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 270.4679
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  100.521 8.75e-12 92.461 108.581
-## k_parent    0.124 3.61e-08  0.104   0.148
-## sigma       7.048 1.28e-04  4.116   9.980
-## 
-## $IORE
-##                Estimate Pr(>t) Lower Upper
-## parent_0         96.823     NA    NA    NA
-## k__iore_parent    2.436     NA    NA    NA
-## N_parent          0.263     NA    NA    NA
-## sigma             3.965     NA    NA    NA
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  100.521 2.74e-10 92.2366 108.805
-## k1          0.124 2.53e-05  0.0908   0.170
-## k2          0.124 2.52e-02  0.0456   0.339
-## g           0.793      NaN      NA      NA
-## sigma       7.048 2.50e-04  4.0349  10.061
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  5.58 18.5     5.58
-## IORE 6.49 13.2     3.99
-## DFOP 5.58 18.5     5.58
-## 
-## Representative half-life:
-## [1] 3.99
    +print(p12a)
    +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 695.4440 220.0685 695.4440 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 270.4679
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)  Lower   Upper
+## parent_0  100.521 8.75e-12 92.461 108.581
+## k_parent    0.124 3.61e-08  0.104   0.148
+## sigma       7.048 1.28e-04  4.116   9.980
+## 
+## $IORE
+##                Estimate Pr(>t) Lower Upper
+## parent_0         96.823     NA    NA    NA
+## k__iore_parent    2.436     NA    NA    NA
+## N_parent          0.263     NA    NA    NA
+## sigma             3.965     NA    NA    NA
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  100.521 2.74e-10 92.2366 108.805
+## k1          0.124 2.53e-05  0.0908   0.170
+## k2          0.124 2.52e-02  0.0456   0.339
+## g           0.793      NaN      NA      NA
+## sigma       7.048 2.50e-04  4.0349  10.061
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  5.58 18.5     5.58
+## IORE 6.49 13.2     3.99
+## DFOP 5.58 18.5     5.58
+## 
+## Representative half-life:
+## [1] 3.99
    -
    -

    -Example on page 12, lower panel

    +
    +

    Example on page 12, lower panel +

    -p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    -
    ## Warning in qt(alpha/2, rdf): NaNs produced
    -
    ## Warning in qt(1 - alpha/2, rdf): NaNs produced
    -
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    -
    ## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    +
    ## Warning in qt(alpha/2, rdf): NaNs produced
    +
    ## Warning in qt(1 - alpha/2, rdf): NaNs produced
    +
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    +
    ## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p12b)
    +plot(p12b)

    -print(p12b)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 58.90242 19.06353 58.90242 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 51.51756
-## 
-## Parameters:
-## $SFO
-##          Estimate  Pr(>t)   Lower    Upper
-## parent_0  97.6840 0.00039 85.9388 109.4292
-## k_parent   0.0589 0.00261  0.0431   0.0805
-## sigma      3.4323 0.04356 -1.2377   8.1023
-## 
-## $IORE
-##                Estimate Pr(>t)     Lower  Upper
-## parent_0         95.523 0.0055 74.539157 116.51
-## k__iore_parent    0.333 0.1433  0.000717 154.57
-## N_parent          0.568 0.0677 -0.989464   2.13
-## sigma             1.953 0.0975 -5.893100   9.80
-## 
-## $DFOP
-##          Estimate Pr(>t) Lower Upper
-## parent_0  97.6840    NaN   NaN   NaN
-## k1         0.0589    NaN    NA    NA
-## k2         0.0589    NaN    NA    NA
-## g          0.6473    NaN    NA    NA
-## sigma      3.4323    NaN   NaN   NaN
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  11.8 39.1    11.80
-## IORE 12.9 31.4     9.46
-## DFOP 11.8 39.1    11.80
-## 
-## Representative half-life:
-## [1] 9.46
    +print(p12b) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 58.90242 19.06353 58.90242 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 51.51756
+## 
+## Parameters:
+## $SFO
+##          Estimate  Pr(>t)   Lower    Upper
+## parent_0  97.6840 0.00039 85.9388 109.4292
+## k_parent   0.0589 0.00261  0.0431   0.0805
+## sigma      3.4323 0.04356 -1.2377   8.1023
+## 
+## $IORE
+##                Estimate Pr(>t)     Lower  Upper
+## parent_0         95.523 0.0055 74.539157 116.51
+## k__iore_parent    0.333 0.1433  0.000717 154.57
+## N_parent          0.568 0.0677 -0.989464   2.13
+## sigma             1.953 0.0975 -5.893100   9.80
+## 
+## $DFOP
+##          Estimate Pr(>t) Lower Upper
+## parent_0  97.6840    NaN   NaN   NaN
+## k1         0.0589    NaN    NA    NA
+## k2         0.0589    NaN    NA    NA
+## g          0.6473    NaN    NA    NA
+## sigma      3.4323    NaN   NaN   NaN
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  11.8 39.1    11.80
+## IORE 12.9 31.4     9.46
+## DFOP 11.8 39.1    11.80
+## 
+## Representative half-life:
+## [1] 9.46
    -
    -

    -Example on page 13

    +
    +

    Example on page 13 +

    -p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p13)
    +plot(p13)

    -print(p13)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 174.5971 142.3951 174.5971 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 172.131
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 92.73500 5.99e-17 89.61936 95.85065
-## k_parent  0.00258 2.42e-09  0.00223  0.00299
-## sigma     3.41172 7.07e-05  2.05455  4.76888
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower  Upper
-## parent_0        91.6016 6.34e-16 88.53086 94.672
-## k__iore_parent   0.0396 2.36e-01  0.00207  0.759
-## N_parent         0.3541 1.46e-01 -0.35153  1.060
-## sigma            3.0811 9.64e-05  1.84296  4.319
-## 
-## $DFOP
-##          Estimate Pr(>t)    Lower    Upper
-## parent_0 92.73500     NA 8.95e+01 95.92118
-## k1        0.00258     NA 4.14e-04  0.01611
-## k2        0.00258     NA 1.74e-03  0.00383
-## g         0.16452     NA 0.00e+00  1.00000
-## sigma     3.41172     NA 2.02e+00  4.79960
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO   269  892      269
-## IORE  261  560      169
-## DFOP  269  892      269
-## 
-## Representative half-life:
-## [1] 168.51
    +print(p13) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 174.5971 142.3951 174.5971 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 172.131
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 92.73500 5.99e-17 89.61936 95.85065
+## k_parent  0.00258 2.42e-09  0.00223  0.00299
+## sigma     3.41172 7.07e-05  2.05455  4.76888
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower  Upper
+## parent_0        91.6016 6.34e-16 88.53086 94.672
+## k__iore_parent   0.0396 2.36e-01  0.00207  0.759
+## N_parent         0.3541 1.46e-01 -0.35153  1.060
+## sigma            3.0811 9.64e-05  1.84296  4.319
+## 
+## $DFOP
+##          Estimate Pr(>t)    Lower    Upper
+## parent_0 92.73500     NA 8.95e+01 95.92118
+## k1        0.00258     NA 4.14e-04  0.01611
+## k2        0.00258     NA 1.74e-03  0.00383
+## g         0.16452     NA 0.00e+00  1.00000
+## sigma     3.41172     NA 2.02e+00  4.79960
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO   269  892      269
+## IORE  261  560      169
+## DFOP  269  892      269
+## 
+## Representative half-life:
+## [1] 168.51
    -
    -

    -DT50 not observed in the study and DFOP problems in PestDF

    +
    +

    DT50 not observed in the study and DFOP problems in PestDF +

    -p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    -
    ## Warning in sqrt(diag(covar)): NaNs produced
    -
    ## Warning in sqrt(1/diag(V)): NaNs produced
    -
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    +
    ## Warning in sqrt(diag(covar)): NaNs produced
    +
    ## Warning in sqrt(1/diag(V)): NaNs produced
    +
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p14)
    +plot(p14)

    -print(p14)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 48.43249 28.67746 27.26248 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 32.83337
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 99.47124 2.06e-30 98.42254 1.01e+02
-## k_parent  0.00279 3.75e-15  0.00256 3.04e-03
-## sigma     1.55616 3.81e-06  1.03704 2.08e+00
-## 
-## $IORE
-##                Estimate Pr(>t) Lower Upper
-## parent_0       1.00e+02     NA   NaN   NaN
-## k__iore_parent 9.44e-08     NA   NaN   NaN
-## N_parent       3.31e+00     NA   NaN   NaN
-## sigma          1.20e+00     NA 0.796   1.6
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
-## k1       9.53e-03 1.20e-01  0.00638   0.0143
-## k2       6.08e-12 5.00e-01  0.00000      Inf
-## g        3.98e-01 2.19e-01  0.30481   0.4998
-## sigma    1.17e+00 7.68e-06  0.77406   1.5610
-## 
-## 
-## DTx values:
-##          DT50     DT90 DT50_rep
-## SFO  2.48e+02 8.25e+02 2.48e+02
-## IORE 4.34e+02 2.22e+04 6.70e+03
-## DFOP 3.05e+10 2.95e+11 1.14e+11
-## 
-## Representative half-life:
-## [1] 6697.44
    +print(p14) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 48.43249 28.67746 27.26248 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 32.83337
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 99.47124 2.06e-30 98.42254 1.01e+02
+## k_parent  0.00279 3.75e-15  0.00256 3.04e-03
+## sigma     1.55616 3.81e-06  1.03704 2.08e+00
+## 
+## $IORE
+##                Estimate Pr(>t) Lower Upper
+## parent_0       1.00e+02     NA   NaN   NaN
+## k__iore_parent 9.44e-08     NA   NaN   NaN
+## N_parent       3.31e+00     NA   NaN   NaN
+## sigma          1.20e+00     NA 0.796   1.6
+## 
+## $DFOP
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
+## k1       9.53e-03 1.20e-01  0.00638   0.0143
+## k2       6.08e-12 5.00e-01  0.00000      Inf
+## g        3.98e-01 2.19e-01  0.30481   0.4998
+## sigma    1.17e+00 7.68e-06  0.77406   1.5610
+## 
+## 
+## DTx values:
+##          DT50     DT90 DT50_rep
+## SFO  2.48e+02 8.25e+02 2.48e+02
+## IORE 4.34e+02 2.22e+04 6.70e+03
+## DFOP 3.05e+10 2.95e+11 1.14e+11
+## 
+## Representative half-life:
+## [1] 6697.44

    The slower rate constant reported by PestDF is negative, which is not physically realistic, and not possible in mkin. The other fits give the same results in mkin and PestDF.

    -
    -

    -N is less than 1 and DFOP fraction parameter is below zero

    +
    +

    N is less than 1 and DFOP fraction parameter is below zero +

    -p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p15a)
    +plot(p15a)

    -print(p15a)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 245.5248 135.0132 245.5248 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 165.9335
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower   Upper
-## parent_0 97.96751 2.00e-15 94.32049 101.615
-## k_parent  0.00952 4.93e-09  0.00824   0.011
-## sigma     4.18778 1.28e-04  2.44588   5.930
-## 
-## $IORE
-##                Estimate   Pr(>t)  Lower  Upper
-## parent_0         95.874 2.94e-15 92.937 98.811
-## k__iore_parent    0.629 2.11e-01  0.044  8.982
-## N_parent          0.000 5.00e-01 -0.642  0.642
-## sigma             3.105 1.78e-04  1.795  4.416
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 97.96751 2.85e-13 94.21913 101.7159
-## k1        0.00952 6.28e-02  0.00250   0.0363
-## k2        0.00952 1.27e-04  0.00646   0.0140
-## g         0.21241 5.00e-01  0.00000   1.0000
-## sigma     4.18778 2.50e-04  2.39747   5.9781
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  72.8  242     72.8
-## IORE 76.3  137     41.3
-## DFOP 72.8  242     72.8
-## 
-## Representative half-life:
-## [1] 41.33
    +print(p15a) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 245.5248 135.0132 245.5248 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 165.9335
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower   Upper
+## parent_0 97.96751 2.00e-15 94.32049 101.615
+## k_parent  0.00952 4.93e-09  0.00824   0.011
+## sigma     4.18778 1.28e-04  2.44588   5.930
+## 
+## $IORE
+##                Estimate   Pr(>t)  Lower  Upper
+## parent_0         95.874 2.94e-15 92.937 98.811
+## k__iore_parent    0.629 2.11e-01  0.044  8.982
+## N_parent          0.000 5.00e-01 -0.642  0.642
+## sigma             3.105 1.78e-04  1.795  4.416
+## 
+## $DFOP
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 97.96751 2.85e-13 94.21913 101.7159
+## k1        0.00952 6.28e-02  0.00250   0.0363
+## k2        0.00952 1.27e-04  0.00646   0.0140
+## g         0.21241 5.00e-01  0.00000   1.0000
+## sigma     4.18778 2.50e-04  2.39747   5.9781
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  72.8  242     72.8
+## IORE 76.3  137     41.3
+## DFOP 72.8  242     72.8
+## 
+## Representative half-life:
+## [1] 41.33
    -p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    -
    ## Warning in sqrt(diag(covar)): NaNs produced
    -
    ## Warning in sqrt(1/diag(V)): NaNs produced
    -
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The half-life obtained from the IORE model may be used
    +p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]]) +
    ## Warning in sqrt(diag(covar)): NaNs produced
    +
    ## Warning in sqrt(1/diag(V)): NaNs produced
    +
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The half-life obtained from the IORE model may be used
    -plot(p15b)
    +plot(p15b) 

    -print(p15b)
    -
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 106.91629  68.55574 106.91629 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 84.25618
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.01e+02 3.06e-17 98.31594 1.03e+02
-## k_parent 4.86e-03 2.48e-10  0.00435 5.42e-03
-## sigma    2.76e+00 1.28e-04  1.61402 3.91e+00
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower  Upper
-## parent_0          99.83 1.81e-16 97.51349 102.14
-## k__iore_parent     0.38 3.22e-01  0.00352  41.05
-## N_parent           0.00 5.00e-01 -1.07696   1.08
-## sigma              2.21 2.57e-04  1.23245   3.19
-## 
-## $DFOP
-##          Estimate Pr(>t)    Lower    Upper
-## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
-## k1       4.86e-03     NA 8.63e-04 2.73e-02
-## k2       4.86e-03     NA 3.21e-03 7.35e-03
-## g        1.88e-01     NA       NA       NA
-## sigma    2.76e+00     NA 1.58e+00 3.94e+00
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO   143  474    143.0
-## IORE  131  236     71.2
-## DFOP  143  474    143.0
-## 
-## Representative half-life:
-## [1] 71.18
    +print(p15b) +
    ## Sums of squares:
+##       SFO      IORE      DFOP 
+## 106.91629  68.55574 106.91629 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 84.25618
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 1.01e+02 3.06e-17 98.31594 1.03e+02
+## k_parent 4.86e-03 2.48e-10  0.00435 5.42e-03
+## sigma    2.76e+00 1.28e-04  1.61402 3.91e+00
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower  Upper
+## parent_0          99.83 1.81e-16 97.51349 102.14
+## k__iore_parent     0.38 3.22e-01  0.00352  41.05
+## N_parent           0.00 5.00e-01 -1.07696   1.08
+## sigma              2.21 2.57e-04  1.23245   3.19
+## 
+## $DFOP
+##          Estimate Pr(>t)    Lower    Upper
+## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
+## k1       4.86e-03     NA 8.63e-04 2.73e-02
+## k2       4.86e-03     NA 3.21e-03 7.35e-03
+## g        1.88e-01     NA       NA       NA
+## sigma    2.76e+00     NA 1.58e+00 3.94e+00
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO   143  474    143.0
+## IORE  131  236     71.2
+## DFOP  143  474    143.0
+## 
+## Representative half-life:
+## [1] 71.18

    In mkin, only the IORE fit is affected (deemed unrealistic), as the fraction parameter of the DFOP model is restricted to the interval between 0 and 1 in mkin. The SFO fits give the same results for both mkin and PestDF.

    -
    -

    -The DFOP fraction parameter is greater than 1

    +
    +

    The DFOP fraction parameter is greater than 1 +

    -p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    -
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    -
    ## The representative half-life of the IORE model is longer than the one corresponding
    -
    ## to the terminal degradation rate found with the DFOP model.
    -
    ## The representative half-life obtained from the DFOP model may be used
    +p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    +
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    +
    ## The representative half-life of the IORE model is longer than the one corresponding
    +
    ## to the terminal degradation rate found with the DFOP model.
    +
    ## The representative half-life obtained from the DFOP model may be used
    -plot(p16)
    +plot(p16)

    -print(p16)
    -
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 3831.804 2062.008 1550.980 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 2247.348
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower Upper
-## parent_0   71.953 2.33e-13 60.509 83.40
-## k_parent    0.159 4.86e-05  0.102  0.25
-## sigma      11.302 1.25e-08  8.308 14.30
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       8.74e+01 2.48e-16 7.72e+01 97.52972
-## k__iore_parent 4.55e-04 2.16e-01 3.48e-05  0.00595
-## N_parent       2.70e+00 1.21e-08 1.99e+00  3.40046
-## sigma          8.29e+00 1.61e-08 6.09e+00 10.49062
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower  Upper
-## parent_0  88.5333 7.40e-18 79.9836 97.083
-## k1        18.8461 5.00e-01  0.0000    Inf
-## k2         0.0776 1.41e-05  0.0518  0.116
-## g          0.4733 1.41e-09  0.3674  0.582
-## sigma      7.1902 2.11e-08  5.2785  9.102
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  4.35 14.4     4.35
-## IORE 1.48 32.1     9.67
-## DFOP 0.67 21.4     8.93
-## 
-## Representative half-life:
-## [1] 8.93
    +print(p16) +
    ## Sums of squares:
+##      SFO     IORE     DFOP 
+## 3831.804 2062.008 1550.980 
+## 
+## Critical sum of squares for checking the SFO model:
+## [1] 2247.348
+## 
+## Parameters:
+## $SFO
+##          Estimate   Pr(>t)  Lower Upper
+## parent_0   71.953 2.33e-13 60.509 83.40
+## k_parent    0.159 4.86e-05  0.102  0.25
+## sigma      11.302 1.25e-08  8.308 14.30
+## 
+## $IORE
+##                Estimate   Pr(>t)    Lower    Upper
+## parent_0       8.74e+01 2.48e-16 7.72e+01 97.52972
+## k__iore_parent 4.55e-04 2.16e-01 3.48e-05  0.00595
+## N_parent       2.70e+00 1.21e-08 1.99e+00  3.40046
+## sigma          8.29e+00 1.61e-08 6.09e+00 10.49062
+## 
+## $DFOP
+##          Estimate   Pr(>t)   Lower  Upper
+## parent_0  88.5333 7.40e-18 79.9836 97.083
+## k1        18.8461 5.00e-01  0.0000    Inf
+## k2         0.0776 1.41e-05  0.0518  0.116
+## g          0.4733 1.41e-09  0.3674  0.582
+## sigma      7.1902 2.11e-08  5.2785  9.102
+## 
+## 
+## DTx values:
+##      DT50 DT90 DT50_rep
+## SFO  4.35 14.4     4.35
+## IORE 1.48 32.1     9.67
+## DFOP 0.67 21.4     8.93
+## 
+## Representative half-life:
+## [1] 8.93

    In PestDF, the DFOP fit seems to have stuck in a local minimum, as mkin finds a solution with a much lower \(\chi^2\) error level. As the half-life from the slower rate constant of the DFOP model is larger than the IORE derived half-life, the NAFTA recommendation obtained with mkin is to use the DFOP representative half-life of 8.9 days.

    -
    -

    -Conclusions

    +
    +

    Conclusions +

    The results obtained with mkin deviate from the results obtained with PestDF either in cases where one of the interpretive rules would apply, i.e. the IORE parameter N is less than one or the DFOP k values obtained with PestDF are equal to the SFO k values, or in cases where the DFOP model did not converge, which often lead to negative rate constants returned by PestDF.

    Therefore, mkin appears to suitable for kinetic evaluations according to the NAFTA guidance.

    -
    -

    -References

    +
    +

    References +

    US EPA. 2015. “Standard Operating Procedure for Using the NAFTA Guidance to Calculate Representative Half-Life Values and Characterizing Pesticide Degradation.”

    @@ -1016,11 +1027,13 @@
    -

    Developed by Johannes Ranke.

    +

    +

    Developed by Johannes Ranke.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.6.

    @@ -1029,5 +1042,7 @@ + + diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png index f5420ce8..75611a70 100644 Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png differ diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p11-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p11-1.png index 0ae4bd9f..55466e47 100644 Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p11-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p11-1.png differ diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p12a-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p12a-1.png index 57a48119..d3143afa 100644 Binary files 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a/docs/dev/articles/web_only/benchmarks.html +++ b/docs/dev/articles/web_only/benchmarks.html @@ -34,7 +34,7 @@ mkin - 1.2.0 + 1.2.2
    @@ -112,7 +112,7 @@

    Benchmark timings for mkin

    Johannes Ranke

    -

    Last change 14 July 2022 (rebuilt 2022-11-15)

    +

    Last change 14 July 2022 (rebuilt 2022-11-24)

    Source: vignettes/web_only/benchmarks.rmd @@ -351,8 +351,16 @@ Ryzen 7 1700 4.2.2 1.2.0 -2.129 -3.784 +2.140 +3.774 + + +Linux +Ryzen 7 1700 +4.2.2 +1.2.2 +2.187 +3.851 @@ -530,9 +538,18 @@ Ryzen 7 1700 4.2.2 1.2.0 -1.559 -6.097 -2.841 +1.554 +6.193 +2.843 + + +Linux +Ryzen 7 1700 +4.2.2 +1.2.2 +1.585 +6.335 +3.003 @@ -764,12 +781,24 @@ Ryzen 7 1700 4.2.2 1.2.0 -0.911 -1.328 -1.519 -2.986 -1.957 -2.769 +0.913 +1.345 +1.539 +3.011 +1.987 +2.802 + + +Linux +Ryzen 7 1700 +4.2.2 +1.2.2 +0.935 +1.381 +1.551 +3.209 +1.976 +3.013 diff --git a/docs/dev/articles/web_only/compiled_models.html b/docs/dev/articles/web_only/compiled_models.html index ade86bc5..e9d80420 100644 --- a/docs/dev/articles/web_only/compiled_models.html +++ b/docs/dev/articles/web_only/compiled_models.html @@ -34,7 +34,7 @@ mkin - 1.2.0 + 1.2.2
    @@ -78,7 +78,10 @@ Example evaluation of NAFTA SOP Attachment examples
  • - Some benchmark timings + Benchmark timings for mkin +
    • +
  • + Benchmark timings for saem.mmkin
    • @@ -109,7 +112,7 @@

    Performance benefit by using compiled model definitions in mkin

    Johannes Ranke

    -

    2022-11-01

    +

    2022-11-24

    Source: vignettes/web_only/compiled_models.rmd @@ -167,10 +170,10 @@ print("R package rbenchmark is not available") }
    ##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.186
-## 3     deSolve, compiled            1    1.656   0.308
-## 2      Eigenvalue based            1    2.102   0.391
-## 1 deSolve, not compiled            1   38.968   7.248
    +## 4 analytical 1 1.000 0.221 +## 3 deSolve, compiled 1 1.561 0.345 +## 2 Eigenvalue based 1 1.932 0.427 +## 1 deSolve, not compiled 1 33.629 7.432

    We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.

    @@ -197,10 +200,10 @@ }
    ## Temporary DLL for differentials generated and loaded
    ##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.452
-## 1 deSolve, not compiled            1   29.431  13.303
    -

    Here we get a performance benefit of a factor of 29 using the version of the differential equation model compiled from C code!

    -

    This vignette was built with mkin 1.2.0 on

    +## 2 deSolve, compiled 1 1.000 0.482 +## 1 deSolve, not compiled 1 27.865 13.431 +

    Here we get a performance benefit of a factor of 28 using the version of the differential equation model compiled from C code!

    +

    This vignette was built with mkin 1.2.2 on

    ## R version 4.2.2 (2022-10-31)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 11 (bullseye)
    diff --git a/docs/dev/articles/web_only/dimethenamid_2018.html b/docs/dev/articles/web_only/dimethenamid_2018.html index 60f1ab5a..ec7f54d8 100644 --- a/docs/dev/articles/web_only/dimethenamid_2018.html +++ b/docs/dev/articles/web_only/dimethenamid_2018.html @@ -34,7 +34,7 @@ mkin - 1.1.2 + 1.2.2
    @@ -63,11 +63,14 @@ Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models
  • - Example evaluation of FOCUS Example Dataset Z + Short demo of the multistart method
  • Performance benefit by using compiled model definitions in mkin
    • +
  • + Example evaluation of FOCUS Example Dataset Z +
  • Calculation of time weighted average concentrations with mkin
    • @@ -75,7 +78,10 @@ Example evaluation of NAFTA SOP Attachment examples
  • - Some benchmark timings + Benchmark timings for mkin +
    • +
  • + Benchmark timings for saem.mmkin
    • @@ -106,7 +112,7 @@

    Example evaluations of the dimethenamid data from 2018

    Johannes Ranke

    -

    Last change 1 July 2022, built on 16 Sep 2022

    +

    Last change 1 July 2022, built on 24 Nov 2022

    Source: vignettes/web_only/dimethenamid_2018.rmd @@ -366,7 +372,7 @@ DFOP tc more iterations 665.88 663.80 ) print(AIC_parent_saemix_methods_defaults) 
        is     gq    lin 
-668.27 718.36 666.49
    +669.77 669.36 670.95
    @@ -437,7 +443,7 @@ DFOP tc more iterations 665.88 663.80 -
    R version 4.2.1 (2022-06-23)
+
    R version 4.2.2 (2022-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
 Running under: Debian GNU/Linux 11 (bullseye)
 
@@ -457,24 +463,24 @@ attached base packages:
 [1] stats     graphics  grDevices utils     datasets  methods   base     
 
 other attached packages:
-[1] nlme_3.1-158 mkin_1.1.2   knitr_1.39  
+[1] saemix_3.2   npde_3.2     nlme_3.1-160 mkin_1.2.2   knitr_1.41  
 
 loaded via a namespace (and not attached):
- [1] deSolve_1.33       zoo_1.8-10         tidyselect_1.1.2   xfun_0.31         
- [5] bslib_0.4.0        purrr_0.3.4        lattice_0.20-45    colorspace_2.0-3  
- [9] vctrs_0.4.1        generics_0.1.3     htmltools_0.5.3    yaml_2.3.5        
-[13] utf8_1.2.2         rlang_1.0.4        pkgdown_2.0.6      saemix_3.1        
-[17] jquerylib_0.1.4    pillar_1.8.0       glue_1.6.2         DBI_1.1.3         
-[21] lifecycle_1.0.1    stringr_1.4.0      munsell_0.5.0      gtable_0.3.0      
-[25] ragg_1.2.2         memoise_2.0.1      evaluate_0.15      npde_3.2          
-[29] fastmap_1.1.0      lmtest_0.9-40      parallel_4.2.1     fansi_1.0.3       
-[33] highr_0.9          KernSmooth_2.23-20 scales_1.2.0       cachem_1.0.6      
-[37] desc_1.4.1         jsonlite_1.8.0     systemfonts_1.0.4  fs_1.5.2          
-[41] textshaping_0.3.6  gridExtra_2.3      ggplot2_3.3.6      digest_0.6.29     
-[45] stringi_1.7.8      dplyr_1.0.9        grid_4.2.1         rprojroot_2.0.3   
-[49] cli_3.3.0          tools_4.2.1        magrittr_2.0.3     sass_0.4.2        
-[53] tibble_3.1.8       pkgconfig_2.0.3    assertthat_0.2.1   rmarkdown_2.14.3  
-[57] mclust_5.4.10      R6_2.5.1           compiler_4.2.1    
    
+ [1] deSolve_1.34      zoo_1.8-11        tidyselect_1.2.0  xfun_0.35        
+ [5] bslib_0.4.1       purrr_0.3.5       lattice_0.20-45   colorspace_2.0-3 
+ [9] vctrs_0.5.1       generics_0.1.3    htmltools_0.5.3   yaml_2.3.6       
+[13] utf8_1.2.2        rlang_1.0.6       pkgdown_2.0.6     jquerylib_0.1.4  
+[17] pillar_1.8.1      glue_1.6.2        DBI_1.1.3         lifecycle_1.0.3  
+[21] stringr_1.4.1     munsell_0.5.0     gtable_0.3.1      ragg_1.2.4       
+[25] codetools_0.2-18  memoise_2.0.1     evaluate_0.18     fastmap_1.1.0    
+[29] lmtest_0.9-40     parallel_4.2.2    fansi_1.0.3       highr_0.9        
+[33] scales_1.2.1      cachem_1.0.6      desc_1.4.2        jsonlite_1.8.3   
+[37] systemfonts_1.0.4 fs_1.5.2          textshaping_0.3.6 gridExtra_2.3    
+[41] ggplot2_3.4.0     digest_0.6.30     stringi_1.7.8     dplyr_1.0.10     
+[45] grid_4.2.2        rprojroot_2.0.3   cli_3.4.1         tools_4.2.2      
+[49] magrittr_2.0.3    sass_0.4.3        tibble_3.1.8      pkgconfig_2.0.3  
+[53] assertthat_0.2.1  rmarkdown_2.18    R6_2.5.1          mclust_6.0.0     
+[57] compiler_4.2.2

    References diff --git a/docs/dev/articles/web_only/multistart.html b/docs/dev/articles/web_only/multistart.html index 50a57d1b..fd05f340 100644 --- a/docs/dev/articles/web_only/multistart.html +++ b/docs/dev/articles/web_only/multistart.html @@ -34,7 +34,7 @@ mkin - 1.2.0 + 1.2.2

    @@ -78,7 +78,10 @@ Example evaluation of NAFTA SOP Attachment examples
  • - Some benchmark timings + Benchmark timings for mkin +
    • +
  • + Benchmark timings for saem.mmkin
    • @@ -109,7 +112,7 @@

    Short demo of the multistart method

    Johannes Ranke

    -

    Last change 26 September 2022 (rebuilt 2022-11-01)

    +

    Last change 26 September 2022 (rebuilt 2022-11-24)

    Source: vignettes/web_only/multistart.rmd @@ -163,8 +166,8 @@ 
    ## Data: 155 observations of 1 variable(s) grouped in 6 datasets
 ## 
 ##                            npar    AIC    BIC     Lik Chisq Df Pr(>Chisq)
-## best(f_saem_reduced_multi)    9 663.64 661.77 -322.82                    
-## f_saem_full                  10 668.27 666.19 -324.13     0  1          1
    +## best(f_saem_reduced_multi) 9 663.69 661.82 -322.85 +## f_saem_full 10 669.77 667.69 -324.89 0 1 1

    While AIC and BIC are lower for the reduced model, the likelihood ratio test does not indicate a significant difference between the fits.

    diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png index 79543765..13bdb94b 100644 Binary files a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png and b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png differ diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png index 4466d437..56147ae2 100644 Binary files a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png and b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png differ diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png index 3dd36f91..f0b89dba 100644 Binary files a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png and b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png differ diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png index 3963e993..c57c247f 100644 Binary files a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png and b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png differ diff --git a/docs/dev/articles/web_only/saem_benchmarks.html b/docs/dev/articles/web_only/saem_benchmarks.html index afff038f..66f4b075 100644 --- a/docs/dev/articles/web_only/saem_benchmarks.html +++ b/docs/dev/articles/web_only/saem_benchmarks.html @@ -34,7 +34,7 @@ mkin - 1.2.0 + 1.2.2 @@ -112,7 +112,7 @@

    Benchmark timings for saem.mmkin

    Johannes Ranke

    -

    Last change 14 November 2022 (rebuilt 2022-11-16)

    +

    Last change 14 November 2022 (rebuilt 2022-11-24)

    Source: vignettes/web_only/saem_benchmarks.rmd @@ -304,16 +304,28 @@ t3 t4 - + + Ryzen 7 1700 Linux 1.2.0 3.2 -2.156 -4.647 -4.296 -4.951 - +2.140 +4.626 +4.328 +4.998 + + +Ryzen 7 1700 +Linux +1.2.2 +3.2 +2.427 +4.550 +4.217 +4.851 + +

    Two-component error fits for SFO, DFOP, SFORB and HS.

    @@ -327,16 +339,28 @@ - + + - - - - - + + + + + + + + + + + + + + + +
    t7 t8
    Ryzen 7 1700 Linux 1.2.0 3.25.6457.4157.8487.967
    5.6787.4418.0007.980
    Ryzen 7 1700Linux1.2.23.25.3527.2018.1748.401
    @@ -352,14 +376,24 @@ t9 t10 - + + Ryzen 7 1700 Linux 1.2.0 3.2 -24.182 -783.932 - +24.465 +800.266 + + +Ryzen 7 1700 +Linux +1.2.2 +3.2 +25.193 +798.580 + +
    @@ -374,13 +408,22 @@ saemix t11 - + + Ryzen 7 1700 Linux 1.2.0 3.2 -1322.5 - +1289.198 + + +Ryzen 7 1700 +Linux +1.2.2 +3.2 +1312.445 + +
    -- cgit v1.2.1