Example evaluation of FOCUS dataset Z

2018-06-06

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FOCUS_Z.Rmd

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Wissenschaftlicher Berater, Kronacher Str. 12, 79639 Grenzach-Wyhlen, Germany
Privatdozent at the University of Bremen

@@ -116,7 +123,7 @@ FOCUS_2006_Z_mkin <- ## Successfully compiled differential equation model from auto-generated C code.

m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.2a)

summary(m.Z.2a, data = FALSE)$bpar

##             Estimate se_notrans    t value     Pr(>t) Lower Upper
 ## Z0_0      9.7015e+01   3.553140 2.7304e+01 1.6793e-21    NA    NA
@@ -131,7 +138,7 @@ FOCUS_2006_Z_mkin <- ## Successfully compiled differential equation model from auto-generated C code.


 m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.2a.ff)
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 summary(m.Z.2a.ff, data = FALSE)$bpar
 ##            Estimate se_notrans t value     Pr(>t) Lower Upper
 ## Z0_0       97.01488   3.553145 27.3039 1.6793e-21    NA    NA
@@ -146,7 +153,7 @@ FOCUS_2006_Z_mkin <- ## Successfully compiled differential equation model from auto-generated C code.

 m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.3)
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 summary(m.Z.3, data = FALSE)$bpar
 ##      Estimate se_notrans t value     Pr(>t)    Lower   Upper
 ## Z0_0 97.01488   2.681772  36.176 2.3636e-25 91.52152 102.508
@@ -164,7 +171,7 @@ FOCUS_2006_Z_mkin <- ## 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)
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 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),
@@ -175,10 +182,10 @@ FOCUS_2006_Z_mkin <- 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$bparms.ode, : Optimisation by method Port did not converge.
-## Convergence code is 1
+## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation by method Port did not converge:
+## false convergence (8)
 plot_sep(m.Z.FOCUS)
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 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
@@ -215,7 +222,7 @@ FOCUS_2006_Z_mkin <- ## 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)
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 summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
 ## NULL
 Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the assumption that the model fit for the parent compound can be improved by using the SFORB model.
@@ -225,7 +232,7 @@ FOCUS_2006_Z_mkin <- ## Successfully compiled differential equation model from auto-generated C code.
 m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.mkin.3)
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 This results in a much better representation of the behaviour of the parent compound Z0.
 Finally, Z3 is added as well. These models appear overparameterised (no covariance matrix returned) if the sink for Z1 is left in the models.
 Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
@@ -237,7 +244,7 @@ FOCUS_2006_Z_mkin <- parms.ini = m.Z.mkin.3$bparms.ode,
                       quiet = TRUE)
 plot_sep(m.Z.mkin.4)
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 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),
@@ -248,7 +255,7 @@ FOCUS_2006_Z_mkin <- parms.ini = m.Z.mkin.4$bparms.ode[1:4],
                       quiet = TRUE)
 plot_sep(m.Z.mkin.5)
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 The summary view of the backtransformed parameters shows that we get no confidence intervals due to overparameterisation. As the optimized  is excessively small, it seems reasonable to fix it to zero.
 m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                        parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
@@ -256,11 +263,11 @@ FOCUS_2006_Z_mkin <- fixed_parms = "k_Z3_bound_free",
                        quiet = TRUE)
 plot_sep(m.Z.mkin.5a)
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 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)
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 The endpoints obtained with this model are
 endpoints(m.Z.mkin.5a)
 ## $ff
@@ -288,7 +295,6 @@ FOCUS_2006_Z_mkin <- 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.

Johannes Ranke

2018-03-21

2018-06-06