From 39b2c2c762b03922a2648b1b226d0f308600cc87 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 6 Jun 2018 01:24:15 +0200 Subject: Static documentation rebuilt by pkgdown 1.1.0 --- docs/articles/FOCUS_D.html | 120 +++++++++++---------- docs/articles/FOCUS_L.html | 102 ++++++++++-------- .../figure-html/unnamed-chunk-12-1.png | Bin 54520 -> 55024 bytes .../figure-html/unnamed-chunk-13-1.png | Bin 21712 -> 22098 bytes .../figure-html/unnamed-chunk-15-1.png | Bin 38347 -> 38740 bytes docs/articles/FOCUS_Z.html | 52 +++++---- .../figure-html/FOCUS_2006_Z_fits_1-1.png | Bin 85456 -> 86312 bytes .../figure-html/FOCUS_2006_Z_fits_10-1.png | Bin 128546 -> 129920 bytes .../figure-html/FOCUS_2006_Z_fits_11-1.png | Bin 128162 -> 129452 bytes .../figure-html/FOCUS_2006_Z_fits_11a-1.png | Bin 101891 -> 97933 bytes .../figure-html/FOCUS_2006_Z_fits_11b-1.png | Bin 22697 -> 22321 bytes .../figure-html/FOCUS_2006_Z_fits_2-1.png | Bin 86036 -> 86923 bytes .../figure-html/FOCUS_2006_Z_fits_3-1.png | Bin 85658 -> 86529 bytes .../figure-html/FOCUS_2006_Z_fits_5-1.png | Bin 101516 -> 102872 bytes .../figure-html/FOCUS_2006_Z_fits_6-1.png | Bin 129164 -> 130096 bytes .../figure-html/FOCUS_2006_Z_fits_7-1.png | Bin 128994 -> 130164 bytes .../figure-html/FOCUS_2006_Z_fits_9-1.png | Bin 108244 -> 109280 bytes docs/articles/compiled_models.html | 42 +++++--- docs/articles/index.html | 35 ++++-- docs/articles/mkin.html | 26 +++-- docs/articles/twa.html | 26 +++-- 21 files changed, 230 insertions(+), 173 deletions(-) (limited to 'docs/articles') diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index a83c2f44..8a1f51d1 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -8,8 +8,8 @@ Example evaluation of FOCUS Example Dataset D • mkin - - + + -
+
-
+

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

-

2018-03-21

-
+

2018-06-06

+ + + + +
-

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 a 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)
@@ -153,10 +160,10 @@

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

summary(fit)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Sun Mar 11 22:11:56 2018 
-## Date of summary: Sun Mar 11 22:11:57 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:49 2018 
+## Date of summary: Wed Jun  6 01:21:50 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -164,7 +171,7 @@
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 0.984 s
+## Fitted with method Port using 153 model solutions performed in 0.633 s
 ## 
 ## Weighting: none
 ## 
@@ -231,51 +238,46 @@
 ## 
 ## Data:
 ##  time variable observed predicted   residual
-##     0   parent    99.46 9.960e+01 -1.385e-01
-##     0   parent   102.04 9.960e+01  2.442e+00
-##     1   parent    93.50 9.024e+01  3.262e+00
-##     1   parent    92.50 9.024e+01  2.262e+00
-##     3   parent    63.23 7.407e+01 -1.084e+01
-##     3   parent    68.99 7.407e+01 -5.083e+00
-##     7   parent    52.32 4.991e+01  2.408e+00
-##     7   parent    55.13 4.991e+01  5.218e+00
-##    14   parent    27.27 2.501e+01  2.257e+00
-##    14   parent    26.64 2.501e+01  1.627e+00
-##    21   parent    11.50 1.253e+01 -1.035e+00
-##    21   parent    11.64 1.253e+01 -8.946e-01
-##    35   parent     2.85 3.148e+00 -2.979e-01
-##    35   parent     2.91 3.148e+00 -2.379e-01
-##    50   parent     0.69 7.162e-01 -2.624e-02
-##    50   parent     0.63 7.162e-01 -8.624e-02
-##    75   parent     0.05 6.074e-02 -1.074e-02
-##    75   parent     0.06 6.074e-02 -7.382e-04
-##   100   parent       NA 5.151e-03         NA
-##   100   parent       NA 5.151e-03         NA
-##   120   parent       NA 7.155e-04         NA
-##   120   parent       NA 7.155e-04         NA
-##     0       m1     0.00 0.000e+00  0.000e+00
-##     0       m1     0.00 0.000e+00  0.000e+00
-##     1       m1     4.84 4.803e+00  3.704e-02
-##     1       m1     5.64 4.803e+00  8.370e-01
-##     3       m1    12.91 1.302e+01 -1.140e-01
-##     3       m1    12.96 1.302e+01 -6.400e-02
-##     7       m1    22.97 2.504e+01 -2.075e+00
-##     7       m1    24.47 2.504e+01 -5.748e-01
-##    14       m1    41.69 3.669e+01  5.000e+00
-##    14       m1    33.21 3.669e+01 -3.480e+00
-##    21       m1    44.37 4.165e+01  2.717e+00
-##    21       m1    46.44 4.165e+01  4.787e+00
-##    35       m1    41.22 4.331e+01 -2.093e+00
-##    35       m1    37.95 4.331e+01 -5.363e+00
-##    50       m1    41.19 4.122e+01 -2.831e-02
-##    50       m1    40.01 4.122e+01 -1.208e+00
-##    75       m1    40.09 3.645e+01  3.643e+00
-##    75       m1    33.85 3.645e+01 -2.597e+00
-##   100       m1    31.04 3.198e+01 -9.416e-01
-##   100       m1    33.13 3.198e+01  1.148e+00
-##   120       m1    25.15 2.879e+01 -3.640e+00
-##   120       m1    33.31 2.879e+01  4.520e+00

-
+## 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 74.07320 -1.084e+01 +## 3 parent 68.99 74.07320 -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 25.01257 2.257e+00 +## 14 parent 26.64 25.01257 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 +## 0 m1 0.00 0.00000 0.000e+00 +## 0 m1 0.00 0.00000 0.000e+00 +## 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 36.69002 5.000e+00 +## 14 m1 33.21 36.69002 -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 43.31312 -2.093e+00 +## 35 m1 37.95 43.31312 -5.363e+00 +## 50 m1 41.19 41.21831 -2.831e-02 +## 50 m1 40.01 41.21831 -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 31.98163 -9.416e-01 +## 100 m1 33.13 31.98163 1.148e+00 +## 120 m1 25.15 28.78984 -3.640e+00 +## 120 m1 33.31 28.78984 4.520e+00
+ + diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html index 08e144bd..fcd0719d 100644 --- a/docs/articles/FOCUS_L.html +++ b/docs/articles/FOCUS_L.html @@ -8,8 +8,8 @@ Example evaluation of FOCUS Laboratory Data L1 to L3 • mkin - - + + -
+
-
+

Example evaluation of FOCUS Laboratory Data L1 to L3

Johannes Ranke

-

2018-03-21

-
+

2018-06-06

+ + + + +
-

Laboratory Data L1

@@ -101,17 +108,17 @@ FOCUS_2006_L1_mkin <- Since mkin version 0.9-32 (July 2014), we can use shorthand notation like "SFO" for parent only degradation models. The following two lines fit the model and produce the summary report of the model fit. This covers the numerical analysis given in the FOCUS report.

m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
 summary(m.L1.SFO)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:03 2018 
-## Date of summary: Wed Mar 21 18:16:03 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:52 2018 
+## Date of summary: Wed Jun  6 01:21:52 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.257 s
+## Fitted with method Port using 37 model solutions performed in 0.094 s
 ## 
 ## Weighting: none
 ## 
@@ -192,17 +199,17 @@ FOCUS_2006_L1_mkin <- plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

summary(m.L1.FOMC, data = FALSE)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:05 2018 
-## Date of summary: Wed Mar 21 18:16:05 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:53 2018 
+## Date of summary: Wed Jun  6 01:21:53 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 611 model solutions performed in 1.404 s
+## Fitted with method Port using 611 model solutions performed in 1.369 s
 ## 
 ## Weighting: none
 ## 
@@ -287,17 +294,17 @@ FOCUS_2006_L2_mkin <- main = "FOCUS L2 - FOMC")

summary(m.L2.FOMC, data = FALSE)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:06 2018 
-## Date of summary: Wed Mar 21 18:16:06 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:54 2018 
+## Date of summary: Wed Jun  6 01:21:54 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 81 model solutions performed in 0.168 s
+## Fitted with method Port using 81 model solutions performed in 0.173 s
 ## 
 ## Weighting: none
 ## 
@@ -358,10 +365,10 @@ FOCUS_2006_L2_mkin <- main = "FOCUS L2 - DFOP")

summary(m.L2.DFOP, data = FALSE)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:06 2018 
-## Date of summary: Wed Mar 21 18:16:06 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:55 2018 
+## Date of summary: Wed Jun  6 01:21:55 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -370,7 +377,7 @@ FOCUS_2006_L2_mkin <- 2006_L3_mkin <-  mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
                list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
 plot(mm.L3)
-

+

The \(\chi^2\) error level of 21% as well as the plot suggest that the SFO model does not fit very well. The FOMC model performs better, with an error level at which the \(\chi^2\) test passes of 7%. Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level considerably.

@@ -450,10 +457,10 @@ mm.L3 <- 
summary(mm.L3[["DFOP", 1]])
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:07 2018 
-## Date of summary: Wed Mar 21 18:16:07 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:56 2018 
+## Date of summary: Wed Jun  6 01:21:56 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -462,7 +469,7 @@ mm.L3 <-  
plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
-

+

Here, a look to the model plot, the confidence intervals of the parameters and the correlation matrix suggest that the parameter estimates are reliable, and the DFOP model can be used as the best-fit model based on the \(\chi^2\) error level criterion for laboratory data L3.

This is also an example where the standard t-test for the parameter g_ilr is misleading, as it tests for a significant difference from zero. In this case, zero appears to be the correct value for this parameter, and the confidence interval for the backtransformed parameter g is quite narrow.

@@ -548,20 +555,20 @@ mm.L4 <- list("FOCUS L4" = FOCUS_2006_L4_mkin), quiet = TRUE) plot(mm.L4)
-

+

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:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:08 2018 
-## Date of summary: Wed Mar 21 18:16:08 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:56 2018 
+## Date of summary: Wed Jun  6 01:21:57 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.092 s
+## Fitted with method Port using 46 model solutions performed in 0.099 s
 ## 
 ## Weighting: none
 ## 
@@ -611,17 +618,17 @@ mm.L4 <- 
summary(mm.L4[["FOMC", 1]], data = FALSE)
-
## mkin version:    0.9.46.3 
-## R version:       3.4.4 
-## Date of fit:     Wed Mar 21 18:16:08 2018 
-## Date of summary: Wed Mar 21 18:16:08 2018 
+
## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.0 
+## Date of fit:     Wed Jun  6 01:21:57 2018 
+## Date of summary: Wed Jun  6 01:21:57 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 66 model solutions performed in 0.138 s
+## Fitted with method Port using 66 model solutions performed in 0.146 s
 ## 
 ## Weighting: none
 ## 
@@ -680,7 +687,6 @@ mm.L4 <-  
 
-
-
+
+
 
 
 
 
 
-    

+    

       

-  

+  

     

       
Example evaluation of FOCUS dataset Z

                         
Johannes Ranke

             
-            
2018-03-21

-          

+            
2018-06-06

+      
+      
+      
+
+    

 
     
     
-

 
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)

-

+

 
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)

-

+

 
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)

-

+

 
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)

-

+

 
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)

-

+

 
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)
-

+

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)
-

+

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)
-

+

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)
-

+

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)
-

+

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.

 
 
-
 
   
 
@@ -320,5 +326,7 @@ FOCUS_2006_Z_mkin <- 
 
 
+  
+
   
 
diff --git a/docs/articles/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png b/docs/articles/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png
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 Performance benefit by using compiled model definitions in mkin • mkin
 
 
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Performance benefit by using compiled model definitions in mkin

                         
Johannes Ranke

             
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 Model that can also be solved with Eigenvalues

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Articles version 0.9.47.1

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 Introduction to mkin • mkin
 
 
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Introduction to mkin

                         
Johannes Ranke

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

 

 

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Calculation of time weighted average concentrations with mkin

                         
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Since version 0.9.45.1 of the ‘mkin’ package, a function for calculating time weighted average concentrations for decline kinetics (i.e. only for the compound applied in the experiment) is included. Strictly speaking, they are maximum moving window time weighted average concentrations, i.e. the maximum time weighted average concentration that can be found when moving a time window of a specified width over the decline curve.

 
Time weighted average concentrations for the SFO, FOMC and the DFOMP model are calculated using the formulas given in the FOCUS kinetics guidance (FOCUS Work Group on Degradation Kinetics 2014, 251):

 
SFO:

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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.

 

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