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:

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.

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.

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

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")

Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+               Z2 = mkinsub("SFO"), use_of_ff = "max")

## Successfully compiled differential equation model from auto-generated C code.

m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.5)

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)

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")

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")

## Successfully compiled differential equation model from auto-generated C code.

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$bparms.ode, : Optimisation by method Port did not converge:
+m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
+                     parms.ini = m.Z.5$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)$bpar
+summary(m.Z.FOCUS, data = FALSE)$bpar
 ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.837112   2.058861 47.0343 5.5877e-44 92.703779 100.970445
-## k_Z0        2.215368   0.118098 18.7587 7.6563e-25  1.990525   2.465609
-## k_Z1        0.478302   0.029289 16.3302 3.3408e-22  0.422977   0.540864
-## k_Z2        0.451617   0.044214 10.2144 3.1133e-14  0.371034   0.549702
-## k_Z3        0.058693   0.014296  4.1056 7.2924e-05  0.035994   0.095705
-## f_Z2_to_Z3  0.471516   0.057057  8.2639 2.8156e-11  0.360381   0.585548
-endpoints(m.Z.FOCUS)
+## Z0_0       96.838619   1.994272 48.5584 4.0282e-42 92.826596 100.850642
+## k_Z0        2.215408   0.118459 18.7018 1.0415e-23  1.989468   2.467007
+## k_Z1        0.478300   0.028257 16.9267 6.2407e-22  0.424701   0.538663
+## k_Z2        0.451618   0.042138 10.7177 1.6308e-14  0.374327   0.544869
+## k_Z3        0.058693   0.015246  3.8498 1.7805e-04  0.034804   0.098981
+## f_Z2_to_Z3  0.471508   0.058352  8.0804 9.6647e-11  0.357725   0.588332
+## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736

endpoints(m.Z.FOCUS)

## $ff
 ##   Z2_Z3 Z2_sink 
-## 0.47152 0.52848 
+## 0.47151 0.52849 
 ## 
 ## $SFORB
 ## logical(0)
@@ -213,9 +223,9 @@
 ## $distimes
 ##        DT50    DT90
 ## Z0  0.31288  1.0394
-## Z1  1.44918  4.8141
+## Z1  1.44919  4.8141
 ## Z2  1.53481  5.0985
-## Z3 11.80973 39.2311

+## Z3 11.80962 39.2307

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.

@@ -223,77 +233,116 @@ 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"))

Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))

## Successfully compiled differential equation model from auto-generated C code.

m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.1)

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)

summary(m.Z.mkin.1, data = FALSE)$cov.unscaled

## Warning in summary.mkinfit(m.Z.mkin.1, data = FALSE): Could not estimate
-## covariance matrix; singular system.

## NULL

summary(m.Z.mkin.1, data = FALSE)$cov.unscaled

##                            Z0_0 log_k_Z0_Z1 log_k_Z1_Z2 log_k_Z2_sink
+## Z0_0                 3.8375e+00  5.4918e-03  3.0584e-02    1.2969e-01
+## log_k_Z0_Z1          5.4918e-03  2.7613e-03 -1.8820e-04    2.6634e-04
+## log_k_Z1_Z2          3.0584e-02 -1.8820e-04  3.3807e-03    3.2177e-03
+## log_k_Z2_sink        1.2969e-01  2.6634e-04  3.2177e-03    3.4256e-02
+## log_k_Z2_Z3_free    -2.4223e-02 -2.6169e-04 -1.1845e-03   -8.1134e-03
+## log_k_Z3_free_sink  -6.5467e-02 -4.0815e-04 -3.2978e-03   -3.6010e-02
+## log_k_Z3_free_bound -6.0658e-02 -4.4768e-04 -3.0588e-03   -3.9074e-02
+## log_k_Z3_bound_free  4.7821e+00  5.5819e-03  1.0267e-01    1.1956e+00
+## sigma               -1.4345e-08  8.6519e-11 -6.1861e-10   -4.7499e-10
+##                     log_k_Z2_Z3_free log_k_Z3_free_sink
+## Z0_0                     -2.4223e-02        -6.5467e-02
+## log_k_Z0_Z1              -2.6169e-04        -4.0815e-04
+## log_k_Z1_Z2              -1.1845e-03        -3.2978e-03
+## log_k_Z2_sink            -8.1134e-03        -3.6010e-02
+## log_k_Z2_Z3_free          1.5500e-02         2.1583e-02
+## log_k_Z3_free_sink        2.1583e-02         7.5705e-02
+## log_k_Z3_free_bound       2.5836e-02         1.1964e-01
+## log_k_Z3_bound_free      -2.1303e-01        -9.0584e-01
+## sigma                     5.8776e-10         1.0773e-09
+##                     log_k_Z3_free_bound log_k_Z3_bound_free       sigma
+## Z0_0                        -6.0658e-02          4.7821e+00 -1.4345e-08
+## log_k_Z0_Z1                 -4.4768e-04          5.5819e-03  8.6519e-11
+## log_k_Z1_Z2                 -3.0588e-03          1.0267e-01 -6.1861e-10
+## log_k_Z2_sink               -3.9074e-02          1.1956e+00 -4.7499e-10
+## log_k_Z2_Z3_free             2.5836e-02         -2.1303e-01  5.8776e-10
+## log_k_Z3_free_sink           1.1964e-01         -9.0584e-01  1.0773e-09
+## log_k_Z3_free_bound          6.5902e-01          4.2011e+00  2.1743e-09
+## log_k_Z3_bound_free          4.2011e+00          3.6036e+08  7.2404e-02
+## sigma                        2.1743e-09          7.2404e-02  1.4170e-01

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"))

Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO"))

## Successfully compiled differential equation model from auto-generated C code.

m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.3)

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)

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"))

Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFO"))

## Successfully compiled differential equation model from auto-generated C code.

m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.4)

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)

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"))

Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))

## Successfully compiled differential equation model from auto-generated C code.

m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.5)

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)

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)
-plot_sep(m.Z.mkin.5a)

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)

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)

endpoints(m.Z.mkin.5a)

## $ff
 ##   Z0_free_Z1        Z1_Z2      Z2_sink   Z2_Z3_free Z3_free_sink 
 ##      1.00000      1.00000      0.46344      0.53656      1.00000 
 ## 
 ## $SFORB
 ##     Z0_b1     Z0_b2     Z3_b1     Z3_b2 
-## 2.4471382 0.0075127 0.0800075 0.0000000 
+## 2.4471355 0.0075125 0.0800068 0.0000000 
 ## 
 ## $distimes
 ##      DT50   DT90 DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
-## Z0 0.3043 1.1848    0.28325     92.264         NA         NA
+## Z0 0.3043 1.1848    0.28325     92.266         NA         NA
 ## Z1 1.5148 5.0320         NA         NA         NA         NA
 ## Z2 1.6414 5.4526         NA         NA         NA         NA
-## Z3     NA     NA         NA         NA     8.6635        Inf

+## Z3 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.

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

Johannes Ranke

2019-03-04

2019-04-10

Example on page 5, upper panel

Example on page 5, lower panel

p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])

## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.

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)

print(p5b)

## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 94.81123 10.10936  7.55871 
@@ -175,28 +174,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)    Lower    Upper
-## parent_0        96.497 2.62e-25 94.77653 98.21774
-## k_parent_sink    0.008 1.35e-14  0.00736  0.00871
+## parent_0        96.497 2.32e-24 94.85271 98.14155
+## k_parent_sink    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 1.02e-29 9.78e+01 9.93e+01
-## k__iore_parent_sink 1.53e-04 1.15e-02 6.60e-05 3.56e-04
-## N_parent            1.94e+00 8.18e-13 1.74e+00 2.14e+00
+## parent_0            9.85e+01 1.17e-28 9.79e+01 9.92e+01
+## k__iore_parent_sink 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 1.90e-28    NA    NA
-## k1       1.55e-02 2.83e-03    NA    NA
-## k2       8.17e-12 5.00e-01    NA    NA
-## g        6.89e-01 1.31e-02    NA    NA
+##          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       1.09e-11 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 1.39e+11 8.48e+10
+## DFOP 83.6 1.04e+11 6.34e+10
 ## 
 ## Representative half-life:
 ## [1] 215.8655

@@ -204,14 +206,12 @@

Example on page 6

p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])

## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.

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)

print(p6)

## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 188.45361  51.00699  42.46931 
@@ -222,28 +222,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)   Lower   Upper
-## parent_0       94.7759 1.25e-24 92.2558 97.2960
-## k_parent_sink   0.0179 2.35e-16  0.0166  0.0194
+## parent_0       94.7759 7.29e-24 92.3479 97.2039
+## k_parent_sink   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 5.62e-27 95.49343 98.75549
-## k__iore_parent_sink  0.00252 3.54e-03  0.00126  0.00502
-## N_parent             1.49587 6.13e-13  1.32380  1.66794
+## parent_0            97.12446 2.63e-26 95.62461 98.62431
+## k__iore_parent_sink  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 4.17e-26    NA    NA
-## k1       2.55e-02 2.12e-05    NA    NA
-## k2       3.09e-11 5.00e-01    NA    NA
-## g        8.61e-01 2.10e-05    NA    NA
+##          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       3.88e-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 1.06e+10 2.24e+10
+## DFOP 34.1 8.42e+09 1.79e+10
 ## 
 ## Representative half-life:
 ## [1] 53.16582

@@ -251,14 +254,12 @@

Example on page 7

p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])

## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.

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)

print(p7)

## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3661.661 3195.030 3174.145 
@@ -269,28 +270,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)    Lower    Upper
-## parent_0      96.41796 1.52e-53 93.29554 99.54038
-## k_parent_sink  0.00735 3.59e-21  0.00641  0.00842
+## parent_0      96.41796 4.80e-53 93.32245 99.51347
+## k_parent_sink  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 7.33e-49 9.53e+01 1.03e+02
-## k__iore_parent_sink 1.60e-05 3.47e-01 9.98e-08 2.57e-03
-## N_parent            2.45e+00 6.14e-05 1.26e+00 3.63e+00
+##                     Estimate Pr(>t)    Lower    Upper
+## parent_0            9.92e+01     NA 9.55e+01 1.03e+02
+## k__iore_parent_sink 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 8.13e-48    NA    NA
-## k1       1.81e-02 2.20e-01    NA    NA
-## k2       3.28e-10 5.00e-01    NA    NA
-## g        6.06e-01 2.60e-01    NA    NA
+##          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       2.57e-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 4.18e+09 2.11e+09
+## DFOP 96.4 5.32e+09 2.69e+09
 ## 
 ## Representative half-life:
 ## [1] 454.5528

@@ -303,7 +307,7 @@

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_sink = 1e-3))

p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent_sink = 1e-3))

## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
 ## singular system.
 
@@ -311,9 +315,9 @@
 ## singular system.

## 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)

print(p8)

## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 1996.9408  444.9237  547.5616 
@@ -327,12 +331,14 @@
 ## parent_0            88.16549     NA    NA    NA
 ## k__iore_parent_sink  0.00100     NA    NA    NA
 ## k_parent_sink        0.00803     NA    NA    NA
+## sigma                7.44786     NA    NA    NA
 ## 
 ## $IORE
 ##                     Estimate   Pr(>t)    Lower    Upper
-## parent_0            9.77e+01 1.05e-35 9.44e+01 1.01e+02
-## k__iore_parent_sink 6.14e-05 2.76e-02 2.21e-05 1.71e-04
-## N_parent            2.27e+00 6.00e-19 2.02e+00 2.53e+00
+## parent_0            9.77e+01 7.03e-35 9.44e+01 1.01e+02
+## k__iore_parent_sink 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
@@ -341,6 +347,7 @@
 ## k1                   0.02500     NA    NA    NA
 ## k2                   0.00273     NA    NA    NA
 ## g                    0.58835     NA    NA    NA
+## sigma                3.90001     NA    NA    NA
 ## 
 ## 
 ## DTx values:
@@ -359,14 +366,12 @@
 
 
 Example on page 9, upper panel
-p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+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)
+print(p9a)
 ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 839.35238  88.57064   9.93363 
@@ -377,28 +382,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)   Lower   Upper
-## parent_0       88.1933 1.12e-12 79.7671 96.6195
-## k_parent_sink   0.0409 9.50e-08  0.0326  0.0513
+## parent_0       88.1933 3.06e-12 79.9447 96.4419
+## k_parent_sink   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 5.16e-17 9.50e+01 1.03e+02
-## k__iore_parent_sink 1.93e-05 1.48e-01 2.65e-06 1.40e-04
-## N_parent            2.91e+00 3.74e-09 2.43e+00 3.39e+00
+## parent_0            9.89e+01 1.12e-16 9.54e+01 1.02e+02
+## k__iore_parent_sink 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 1.31e-21    NA    NA
-## k1       1.38e-01 3.63e-09    NA    NA
-## k2       6.02e-13 5.00e-01    NA    NA
-## g        6.52e-01 1.50e-10    NA    NA
+##          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       5.75e-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 2.07e+12 1.15e+12
+## DFOP 10.5 2.17e+12 1.21e+12
 ## 
 ## Representative half-life:
 ## [1] 101.4264
@@ -407,14 +415,17 @@
 
 
 Example on page 9, lower panel
-p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
+## Warning in sqrt(diag(covar)): NaNs wurden erzeugt
+## Warning in sqrt(diag(covar_notrans)): NaNs wurden erzeugt
+## Warning in sqrt(1/diag(V)): NaNs wurden erzeugt
+## Warning in cov2cor(ans$cov.unscaled): 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)
+print(p9b)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 35.64867 23.22334 35.64867 
@@ -424,22 +435,25 @@
 ## 
 ## Parameters:
 ## $SFO
-##               Estimate   Pr(>t)   Lower  Upper
-## parent_0       94.7123 2.21e-20 93.0673 96.357
-## k_parent_sink   0.0389 1.48e-14  0.0369  0.041
+##               Estimate   Pr(>t)  Lower   Upper
+## parent_0       94.7123 2.15e-19 93.178 96.2464
+## k_parent_sink   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 2.91e-19 92.2996 95.426
-## k__iore_parent_sink    0.127 2.73e-02  0.0457  0.354
-## N_parent               0.711 3.13e-05  0.4605  0.961
+## parent_0              93.863 2.32e-18 92.4565 95.269
+## k__iore_parent_sink    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     NA    NA    NA
-## k1         0.0389     NA    NA    NA
-## k2         0.0389     NA    NA    NA
-## g          0.7742     NA    NA    NA
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  94.7123 1.61e-16 93.1355 96.2891
+## k1         0.0389      NaN  0.0316  0.0478
+## k2         0.0389 1.13e-08  0.0203  0.0743
+## g          0.7599      NaN      NA      NA
+## sigma      1.5957 2.50e-04  0.9135  2.2779
 ## 
 ## 
 ## DTx values:
@@ -455,14 +469,12 @@
 
 
 Example on page 10
-p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
 ## 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)
+print(p10)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 899.4089 336.4348 899.4089 
@@ -473,21 +485,24 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)   Lower    Upper
-## parent_0      101.7315 4.95e-11 90.9683 112.4947
-## k_parent_sink   0.0495 3.40e-07  0.0393   0.0624
+## parent_0      101.7315 6.42e-11 91.9259 111.5371
+## k_parent_sink   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 2.71e-12 89.884 103.826
-## k__iore_parent_sink     2.96 1.31e-01  0.461  19.020
-## N_parent                0.00 5.00e-01 -0.473   0.473
+## parent_0               96.86 3.32e-12 90.848 102.863
+## k__iore_parent_sink     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     NA    NA    NA
-## k1         0.0495     NA    NA    NA
-## k2         0.0495     NA    NA    NA
-## g          0.6634     NA    NA    NA
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 101.7315 1.41e-09 91.6534 111.8097
+## k1         0.0495 6.41e-04  0.0303   0.0809
+## k2         0.0495 1.66e-02  0.0201   0.1219
+## g          0.6634 5.00e-01  0.0000   1.0000
+## sigma      8.0152 2.50e-04  4.5886  11.4418
 ## 
 ## 
 ## DTx values:
@@ -507,14 +522,12 @@
 
 
 Example on page 11
-p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+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)
+print(p11)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 579.6805 204.7932 144.7783 
@@ -525,28 +538,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)    Lower    Upper
-## parent_0      96.15820 1.56e-13 89.91373 1.02e+02
-## k_parent_sink  0.00321 5.27e-05  0.00218 4.71e-03
+## parent_0      96.15820 4.83e-13 90.24934 1.02e+02
+## k_parent_sink  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 9.80e+01 1.11e+02
-## k__iore_parent_sink 3.11e-17     NA 6.88e-25 1.41e-09
-## N_parent            8.36e+00     NA 4.40e+00 1.23e+01
+## parent_0            1.05e+02     NA 9.90e+01 1.10e+02
+## k__iore_parent_sink 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 7.50e-13    NA    NA
-## k1       4.41e-02 3.34e-02    NA    NA
-## k2       7.25e-13 5.00e-01    NA    NA
-## g        3.22e-01 7.87e-03    NA    NA
+##          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       9.20e-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 4.21e+11 2.64e+12 9.56e+11
+## DFOP 3.31e+11 2.08e+12 7.53e+11
 ## 
 ## Representative half-life:
 ## [1] 41148169
@@ -560,9 +576,14 @@
 
 
 Example on page 12, upper panel
-p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
+p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
 ## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
 ## singular system.
+## Warning in sqrt(diag(covar)): NaNs wurden erzeugt
+## Warning in sqrt(diag(covar_notrans)): NaNs wurden erzeugt
+## Warning in sqrt(1/diag(V)): NaNs wurden erzeugt
+## Warning in cov2cor(ans$cov.unscaled): 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)
@@ -578,21 +599,24 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)  Lower   Upper
-## parent_0       100.521 5.61e-12 91.687 109.355
-## k_parent_sink    0.124 7.24e-08  0.102   0.152
+## parent_0       100.521 8.75e-12 92.461 108.581
+## k_parent_sink    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 1.24e-13 91.5691 102.078
-## k__iore_parent_sink    2.436 3.89e-02  0.7854   7.556
-## N_parent               0.263 3.64e-02 -0.0288   0.554
+##                     Estimate Pr(>t) Lower Upper
+## parent_0              96.823     NA    NA    NA
+## k__iore_parent_sink    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     NA    NA    NA
-## k1          0.124     NA    NA    NA
-## k2          0.124     NA    NA    NA
-## g           0.877     NA    NA    NA
+##          Estimate   Pr(>t)   Lower   Upper
+## parent_0  100.521 2.74e-10 92.2366 108.805
+## k1          0.124 5.43e-06  0.0959   0.161
+## k2          0.124 6.45e-02  0.0315   0.490
+## g           0.880      NaN      NA      NA
+## sigma       7.048 2.50e-04  4.0349  10.061
 ## 
 ## 
 ## DTx values:
@@ -608,13 +632,19 @@
 
 Example on page 12, lower panel
 p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+## Warning in sqrt(diag(covar)): NaNs wurden erzeugt
+## Warning in qt(alpha/2, rdf): NaNs wurden erzeugt
+## Warning in qt(1 - alpha/2, rdf): NaNs wurden erzeugt
+## Warning in sqrt(diag(covar_notrans)): NaNs wurden erzeugt
+## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs wurden erzeugt
+## Warning in sqrt(1/diag(V)): NaNs wurden erzeugt
+## Warning in cov2cor(ans$cov.unscaled): 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(p12b)
+plot(p12b)
 
-print(p12b)
+print(p12b)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 58.90242 19.06353 58.90242 
@@ -624,22 +654,25 @@
 ## 
 ## Parameters:
 ## $SFO
-##               Estimate   Pr(>t)   Lower    Upper
-## parent_0       97.6840 5.36e-05 86.3205 109.0475
-## k_parent_sink   0.0589 9.87e-04  0.0432   0.0803
+##               Estimate  Pr(>t)   Lower    Upper
+## parent_0       97.6840 0.00039 85.9388 109.4292
+## k_parent_sink   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 0.000386 84.0963 106.95
-## k__iore_parent_sink    0.333 0.170886  0.0103  10.80
-## N_parent               0.568 0.054881 -0.3161   1.45
+##                     Estimate Pr(>t)     Lower  Upper
+## parent_0              95.523 0.0055 74.539157 116.51
+## k__iore_parent_sink    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     NA    NA    NA
-## k1         0.0589     NA    NA    NA
-## k2         0.0589     NA    NA    NA
-## g          0.6902     NA    NA    NA
+## parent_0  97.6840    NaN   NaN   NaN
+## k1         0.0589    NaN    NA    NA
+## k2         0.0589    NaN    NA    NA
+## g          0.8275    NaN    NA    NA
+## sigma      3.4323    NaN   NaN   NaN
 ## 
 ## 
 ## DTx values:
@@ -654,14 +687,12 @@
 
 
 Example on page 13
-p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+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)
+print(p13)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 174.5971 142.3951 174.5971 
@@ -671,22 +702,25 @@
 ## 
 ## Parameters:
 ## $SFO
-##               Estimate   Pr(>t)   Lower    Upper
-## parent_0      92.73500 1.45e-17 89.3891 96.08094
-## k_parent_sink  0.00258 2.63e-09  0.0022  0.00303
+##               Estimate   Pr(>t)    Lower    Upper
+## parent_0      92.73500 5.99e-17 89.61936 95.85065
+## k_parent_sink  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 2.93e-16 88.08711 95.12
-## k__iore_parent_sink   0.0396 2.81e-01  0.00102  1.53
-## N_parent              0.3541 1.97e-01 -0.51943  1.23
+##                     Estimate   Pr(>t)    Lower  Upper
+## parent_0             91.6016 6.34e-16 88.53086 94.672
+## k__iore_parent_sink   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    NA    NA
-## k1        0.00258     NA    NA    NA
-## k2        0.00258     NA    NA    NA
-## g         0.00442     NA    NA    NA
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 92.73500 9.25e-15 8.95e+01 9.59e+01
+## k1        0.00258 4.28e-01 1.38e-08 4.82e+02
+## k2        0.00258 3.69e-08 2.20e-03 3.03e-03
+## g         0.00442 5.00e-01 0.00e+00 1.00e+00
+## sigma     3.41172 1.35e-04 2.02e+00 4.80e+00
 ## 
 ## 
 ## DTx values:
@@ -702,14 +736,16 @@
 
 
 DT50 not observed in the study and DFOP problems in PestDF
-p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
+## Warning in sqrt(diag(covar)): NaNs wurden erzeugt
+## Warning in sqrt(1/diag(V)): NaNs wurden erzeugt
+## Warning in cov2cor(ans$cov.unscaled): 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)
+print(p14)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 48.43249 28.67746 27.26248 
@@ -720,28 +756,31 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)    Lower    Upper
-## parent_0      99.47124 1.71e-31 98.37313 1.01e+02
-## k_parent_sink  0.00279 2.22e-15  0.00255 3.05e-03
+## parent_0      99.47124 2.06e-30 98.42254 1.01e+02
+## k_parent_sink  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 9.93e+01 1.01e+02
-## k__iore_parent_sink 9.44e-08     NA 6.81e-11 1.31e-04
-## N_parent            3.31e+00     NA 1.69e+00 4.93e+00
+##                     Estimate Pr(>t) Lower Upper
+## parent_0            1.00e+02     NA   NaN   NaN
+## k__iore_parent_sink 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 2.70e-28    NA    NA
-## k1       9.53e-03 3.39e-01    NA    NA
-## k2       9.19e-12 5.00e-01    NA    NA
-## g        3.98e-01 3.92e-01    NA    NA
+##          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       6.17e-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 2.02e+10 1.95e+11 7.54e+10
+## DFOP 3.00e+10 2.91e+11 1.12e+11
 ## 
 ## Representative half-life:
 ## [1] 6697.437
@@ -750,14 +789,17 @@
 
 
 N is less than 1 and DFOP fraction parameter is below zero
-p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
+## Warning in sqrt(diag(covar)): NaNs wurden erzeugt
+## Warning in sqrt(diag(covar_notrans)): NaNs wurden erzeugt
+## Warning in sqrt(1/diag(V)): NaNs wurden erzeugt
+## Warning in cov2cor(ans$cov.unscaled): 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(p15a)
+plot(p15a)
 
-print(p15a)
+print(p15a)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 245.5248 135.0132 245.5248 
@@ -767,22 +809,25 @@
 ## 
 ## Parameters:
 ## $SFO
-##               Estimate   Pr(>t)    Lower    Upper
-## parent_0      97.96751 4.98e-16 94.03829 101.8967
-## k_parent_sink  0.00952 5.24e-09  0.00813   0.0112
+##               Estimate   Pr(>t)    Lower   Upper
+## parent_0      97.96751 2.00e-15 94.32049 101.615
+## k_parent_sink  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 8.30e-16 92.5802 99.167
-## k__iore_parent_sink    0.629 2.39e-01  0.0316 12.519
-## N_parent               0.000 5.00e-01 -0.7219  0.722
+##                     Estimate   Pr(>t)  Lower  Upper
+## parent_0              95.874 2.94e-15 92.937 98.811
+## k__iore_parent_sink    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 97.96752     NA    NA    NA
-## k1        0.00952     NA    NA    NA
-## k2        0.00952     NA    NA    NA
-## g         0.17247     NA    NA    NA
+##          Estimate   Pr(>t)    Lower    Upper
+## parent_0 97.96751 2.85e-13 94.21913 101.7159
+## k1        0.00952 5.68e-02  0.00262   0.0347
+## k2        0.00952 1.52e-04  0.00639   0.0142
+## g         0.22357      NaN       NA       NA
+## sigma     4.18778 2.50e-04  2.39747   5.9781
 ## 
 ## 
 ## DTx values:
@@ -793,14 +838,12 @@
 ## 
 ## Representative half-life:
 ## [1] 41.32749
-p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
-## Warning in summary.mkinfit(x): Could not estimate covariance matrix;
-## singular system.
+p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
 ## 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)
+print(p15b)
 ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 106.91629  68.55574 106.91629 
@@ -811,21 +854,24 @@
 ## Parameters:
 ## $SFO
 ##               Estimate   Pr(>t)    Lower    Upper
-## parent_0      1.01e+02 4.99e-18 98.12761 1.04e+02
-## k_parent_sink 4.86e-03 1.76e-10  0.00432 5.46e-03
+## parent_0      1.01e+02 3.06e-17 98.31594 1.03e+02
+## k_parent_sink 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 4.49e-17 97.19753 102.5
-## k__iore_parent_sink     0.38 3.41e-01  0.00206  70.0
-## N_parent                0.00 5.00e-01 -1.20105   1.2
+##                     Estimate   Pr(>t)    Lower  Upper
+## parent_0               99.83 1.81e-16 97.51349 102.14
+## k__iore_parent_sink     0.38 3.22e-01  0.00352  41.05
+## N_parent                0.00 5.00e-01 -1.07695   1.08
+## sigma                   2.21 2.57e-04  1.23245   3.19
 ## 
 ## $DFOP
-##          Estimate Pr(>t) Lower Upper
-## parent_0 1.01e+02     NA    NA    NA
-## k1       4.86e-03     NA    NA    NA
-## k2       4.86e-03     NA    NA    NA
-## g        1.50e-01     NA    NA    NA
+##          Estimate Pr(>t)    Lower    Upper
+## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
+## k1       4.86e-03     NA 6.49e-04 3.64e-02
+## k2       4.86e-03     NA 3.36e-03 7.03e-03
+## g        1.50e-01     NA 0.00e+00 1.00e+00
+## sigma    2.76e+00     NA 1.58e+00 3.94e+00
 ## 
 ## 
 ## DTx values:
@@ -841,14 +887,14 @@
 
 
 The DFOP fraction parameter is greater than 1
-p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
+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)
+print(p16)
 ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3831.804 2062.008 1550.980 
@@ -858,22 +904,25 @@
 ## 
 ## Parameters:
 ## $SFO
-##               Estimate   Pr(>t)  Lower  Upper
-## parent_0        71.953 3.92e-14 61.087 82.819
-## k_parent_sink    0.159 2.27e-06  0.111  0.229
+##               Estimate   Pr(>t)  Lower Upper
+## parent_0        71.953 2.33e-13 60.509 83.40
+## k_parent_sink    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 1.74e-16 7.71e+01 97.70701
-## k__iore_parent_sink 4.55e-04 2.28e-01 3.01e-05  0.00688
-## N_parent            2.70e+00 1.87e-08 1.97e+00  3.42611
+## parent_0            8.74e+01 2.48e-16 7.72e+01 97.52972
+## k__iore_parent_sink 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     NA 79.3673 97.699
-## k1        18.5562     NA  0.0000    Inf
-## k2         0.0776     NA  0.0471  0.128
-## g          0.4733     NA  0.3138  0.639
+##          Estimate   Pr(>t)   Lower  Upper
+## parent_0  88.5333 7.40e-18 79.9836 97.083
+## k1        18.6317 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:
diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png
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diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html
new file mode 100644
index 00000000..403cb1db
--- /dev/null
+++ b/docs/articles/web_only/benchmarks.html
@@ -0,0 +1,292 @@
+
+
+
+
+
+
+
+Benchmark timings for mkin on various systems • mkin
+
+
+
+
+
+
+
+
+
+    
+      
+  
+    
+      
+      
+        mkin
+        0.9.49.4
+      
+    
+
+    
+      
+
+  Functions and data
+
+
+  
+    Articles
+     
+    
+  
+  
+
+      Introduction to mkin
+    
+    
+      Example evaluation of FOCUS Example Dataset D
+    
+    
+      Example evaluation of FOCUS Laboratory Data L1 to L3
+    
+    
+      Example evaluation of FOCUS Example Dataset Z
+    
+    
+      Performance benefit by using compiled model definitions in mkin
+    
+    
+      Calculation of time weighted average concentrations with mkin
+    
+    
+      Example evaluation of NAFTA SOP Attachment examples
+    
+  
+
+
+  News
+
+      
+
+
+
+  
+
+
+
+
+      
+      

+  
+    
+      Benchmark timings for mkin on various systems
+                        Johannes Ranke
+            
+            2019-04-10
+      
+      
+      benchmarks.Rmd
+
+    
+
+    
+    
+
+
+Systems
+Each system is characterized by its CPU type, the operating system type and the mkin version.
+cpu_model <- benchmarkme::get_cpu()$model_name
+operating_system <- Sys.info()[["sysname"]]
+mkin_version <- as.character(packageVersion("mkin"))
+system_string <- paste0(operating_system, ", ", cpu_model, ", mkin version ", mkin_version)
+load("~/git/mkin/inst/benchmark_data/mkin_benchmarks.rda")
+mkin_benchmarks[system_string, c("CPU", "OS", "mkin")] <- c(cpu_model, operating_system, mkin_version)
+
+if (mkin_version > "0.9.48.1") {
+  mmkin_bench <- function(models, datasets, error_model = "const") mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE)
+} else {
+  mmkin_bench <- function(models, datasets, error_model = NULL) mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE)
+}
+# Parent only
+t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_2006_C, FOCUS_2006_D)))[["elapsed"]]
+t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_2006_C, FOCUS_2006_D), error_model = "tc"))[["elapsed"]]
+
+# One metabolite
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+## Successfully compiled differential equation model from auto-generated C code.
+FOMC_SFO <- mkinmod(
+  parent = mkinsub("FOMC", "m1"),
+  m1 = mkinsub("SFO"))
+## Successfully compiled differential equation model from auto-generated C code.
+DFOP_SFO <- mkinmod(
+  parent = mkinsub("FOMC", "m1"),
+  m1 = mkinsub("SFO"))
+## Successfully compiled differential equation model from auto-generated C code.
+t3 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_2006_D)))[["elapsed"]]
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(subset(FOCUS_2006_D, value != 0)), error_model = "tc"))[["elapsed"]]
+t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_2006_D), error_model = "obs"))[["elapsed"]]
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+
+## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...):
+## Observations with value of zero were removed from the data
+# Two metabolites, synthetic data
+m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
+                           M1 = mkinsub("SFO", "M2"),
+                           M2 = mkinsub("SFO"),
+                           use_of_ff = "max", quiet = TRUE)
+
+m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
+                           M1 = mkinsub("SFO"),
+                           M2 = mkinsub("SFO"),
+                           use_of_ff = "max", quiet = TRUE)
+
+SFO_lin_a <- synthetic_data_for_UBA_2014[[1]]$data
+
+DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
+
+t6 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a)))["elapsed"]
+t7 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c)))["elapsed"]
+
+t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), error_model = "tc"))["elapsed"]
+t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "tc"))["elapsed"]
+
+t10 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), error_model = "obs"))["elapsed"]
+t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "obs"))["elapsed"]
+
+mkin_benchmarks[system_string, paste0("t", 1:11)] <- c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11)
+mkin_benchmarks
+##                                                                                                       CPU
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 AMD Ryzen 7 1700 Eight-Core Processor
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 AMD Ryzen 7 1700 Eight-Core Processor
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 AMD Ryzen 7 1700 Eight-Core Processor
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 AMD Ryzen 7 1700 Eight-Core Processor
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 AMD Ryzen 7 1700 Eight-Core Processor
+##                                                                        OS
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 Linux
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 Linux
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 Linux
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 Linux
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 Linux
+##                                                                         mkin
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 0.9.48.1
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 0.9.49.1
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 0.9.49.2
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 0.9.49.3
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 0.9.49.4
+##                                                                        t1
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.610
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 8.184
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.064
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.296
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 6.303
+##                                                                         t2
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 11.019
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 22.889
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 12.558
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 21.239
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 21.837
+##                                                                        t3
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.764
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.649
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.786
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.510
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.487
+##                                                                         t4
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 14.347
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 13.789
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2  8.461
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 13.805
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 14.162
+##                                                                        t5
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 9.495
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 6.395
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.675
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.386
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 6.021
+##                                                                        t6
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 2.623
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 2.542
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 2.723
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 2.643
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 2.657
+##                                                                        t7
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 4.587
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.128
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.478
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.374
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.523
+##                                                                        t8
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 7.525
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.632
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.862
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3  7.02
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4  4.72
+##                                                                         t9
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 16.621
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1  8.171
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2  7.618
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 11.124
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4  8.364
+##                                                                       t10
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 8.576
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 3.676
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 3.579
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 5.388
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 3.623
+##                                                                        t11
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 31.267
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1  5.636
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2  5.574
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3  7.365
+## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4   5.95
+save(mkin_benchmarks, file = "~/git/mkin/inst/benchmark_data/mkin_benchmarks.rda")
+
+  
+
+  
+        
+      
+Contents
+      
+Systems
+      
+
+      
+
+
+
+
+      
+  Developed by Johannes Ranke.
+
+
+
+  Site built with pkgdown 1.3.0.9000.
+
+      
+
+
+  
+
+  
+
diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html
index 269b1098..597b7c55 100644
--- a/docs/articles/web_only/compiled_models.html
+++ b/docs/articles/web_only/compiled_models.html
@@ -30,7 +30,7 @@
       
       
         mkin
-        0.9.48.1
+        0.9.49.4
       
     

 
@@ -88,7 +88,7 @@
       Performance benefit by using compiled model definitions in mkin
                         Johannes Ranke
             
-            2019-03-04
+            2019-04-10
       
       
       compiled_models.Rmd
@@ -125,49 +125,103 @@
   factor_SFO_SFO <- round(b.1["1", "relative"])
 } else {
   factor_SFO_SFO <- NA
-  print("R package benchmark is not available")
+  print("R package rbenchmark is not available")
 }

 ## Lade nötiges Paket: rbenchmark
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
+## use_compiled = FALSE, : Observations with value of zero were removed from
+## the data
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
+## TRUE): Observations with value of zero were removed from the data
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
+## = TRUE): Observations with value of zero were removed from the data
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
+## use_compiled = FALSE, : Observations with value of zero were removed from
+## the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
+## use_compiled = FALSE, : Observations with value of zero were removed from
+## the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
+## use_compiled = FALSE, : Observations with value of zero were removed from
+## the data
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
+## TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
+## TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
+## TRUE): Observations with value of zero were removed from the data
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
+## = TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
+## = TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
+## = TRUE): Observations with value of zero were removed from the data
 ##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   2.310    1.000     2.308        0
-## 1 deSolve, not compiled            3  17.509    7.580    17.500        0
-## 2      Eigenvalue based            3   2.859    1.238     2.858        0
+## 3     deSolve, compiled            3   3.215    1.000     3.213        0
+## 1 deSolve, not compiled            3  42.468   13.209    42.445        0
+## 2      Eigenvalue based            3   4.666    1.451     4.663        0
 ##   user.child sys.child
 ## 3          0         0
 ## 1          0         0
 ## 2          0         0
-We see that using the compiled model is by a factor of around 8 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs.
+We see that using the compiled model is by a factor of around 13 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs.
 

 
 
 Model that can not be solved with Eigenvalues
 This evaluation is also taken from the example section of mkinfit.
-if (require(rbenchmark)) {
-  FOMC_SFO <- mkinmod(
-    parent = mkinsub("FOMC", "m1"),
-    m1 = mkinsub( "SFO"))
-
-  b.2 <- benchmark(
-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
-                                      use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
-    replications = 3)
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
-} else {
-  factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
-}
+if (require(rbenchmark)) {
+  FOMC_SFO <- mkinmod(
+    parent = mkinsub("FOMC", "m1"),
+    m1 = mkinsub( "SFO"))
+
+  b.2 <- benchmark(
+    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
+                                      use_compiled = FALSE, quiet = TRUE),
+    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
+    replications = 3)
+  print(b.2)
+  factor_FOMC_SFO <- round(b.2["1", "relative"])
+} else {
+  factor_FOMC_SFO <- NA
+  print("R package benchmark is not available")
+}
 ## Successfully compiled differential equation model from auto-generated C code.
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
+## TRUE): Observations with value of zero were removed from the data
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
+## value of zero were removed from the data
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
+## TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
+## TRUE): Observations with value of zero were removed from the data
+
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
+## TRUE): Observations with value of zero were removed from the data
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
+## value of zero were removed from the data
+
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
+## value of zero were removed from the data
+
+## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
+## value of zero were removed from the data
 ##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   4.074    1.000     4.072        0
-## 1 deSolve, not compiled            3  37.219    9.136    37.203        0
+## 2     deSolve, compiled            3   4.906    1.000     4.902        0
+## 1 deSolve, not compiled            3  70.459   14.362    70.421        0
 ##   user.child sys.child
 ## 2          0         0
 ## 1          0         0
-Here we get a performance benefit of a factor of 9 using the version of the differential equation model compiled from C code!
-This vignette was built with mkin 0.9.48.1 on
-## R version 3.5.2 (2018-12-20)
+Here we get a performance benefit of a factor of 14 using the version of the differential equation model compiled from C code!
+This vignette was built with mkin 0.9.49.4 on
+## R version 3.5.3 (2019-03-11)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 9 (stretch)
 ## CPU model: AMD Ryzen 7 1700 Eight-Core Processor
-- 
cgit v1.2.1

Example evaluation of FOCUS dataset Z

Johannes Ranke

2019-03-04

2019-04-10

Metabolites Z2 and Z3

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

Johannes Ranke

2019-03-04

2019-04-10

Example on page 5, upper panel

Example on page 5, lower panel

Example on page 6

Example on page 7

Example on page 8

Example on page 9, upper panel

Example on page 9, lower panel

Example on page 10

Example on page 11

Example on page 12, upper panel

Example on page 12, lower panel

Example on page 13

DT50 not observed in the study and DFOP problems in PestDF

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

The DFOP fraction parameter is greater than 1

Benchmark timings for mkin on various systems

Johannes Ranke

2019-04-10

+Systems

+Contents

Performance benefit by using compiled model definitions in mkin

Johannes Ranke

2019-03-04

2019-04-10

Model that can not be solved with Eigenvalues