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mkin

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The R package mkin provides calculation routines for the analysis of chemical degradation data, including multicompartment kinetics as needed for modelling the formation and decline of transformation products, or if several compartments are involved.

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Installation

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You can install the latest released version from CRAN from within R:

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install.packages("mkin")
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Background

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In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance and helpful tools have been developed as detailed in ‘Credits and historical remarks’ below.

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Usage

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For a start, have a look a the code examples provided for plot.mkinfit and plot.mmkin, and at the package vignettes FOCUS L and FOCUS D.

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Documentation

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The HTML documentation is available at jrwb.de, at github and at R-Forge.

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Features

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  • Highly flexible model specification using mkinmod, including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two latent state variables for the observed variable.
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  • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
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  • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
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  • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
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  • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric logration transformation that is now used for the formation fractions.
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  • A side effect of this is that when parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which can not occur in a single experiment with a single defined radiolabel position.
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  • The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.
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  • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
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  • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
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  • Iteratively reweighted least squares fitting is implemented in a similar way as in KinGUII and CAKE (see below). Simply add the argument reweight.method = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.
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  • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
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  • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
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GUI

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There is a graphical user interface that I consider useful for real work. Please refer to its documentation page for installation instructions and a manual.

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News

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There is a ChangeLog, for the latest CRAN release and one for the github master branch.

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Credits and historical remarks

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mkin would not be possible without the underlying software stack consisting of R and the packages deSolve and FME, to say the least.

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It could not have been written without me being introduced to regulatory fate modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories Ltd (formerly RCC Ltd). mkin greatly profits from and largely follows the work done by the FOCUS Degradation Kinetics Workgroup, as detailed in their guidance document from 2006, slightly updated in 2011 and in 2014.

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Also, it was inspired by the first version of KinGUI developed by BayerCropScience, which is based on the MatLab runtime environment.

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The companion package kinfit (now deprecated) was started in 2008 and first published on CRAN on 01 May 2010.

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The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.

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In 2011, Bayer Crop Science started to distribute an R based successor to KinGUI named KinGUII whose R code is based on mkin, but which added, amongst other refinements, a closed source graphical user interface (GUI), iteratively reweighted least squares (IRLS) optimisation of the variance for each of the observed variables, and Markov Chain Monte Carlo (MCMC) simulation functionality, similar to what is available e.g. in the FME package.

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Somewhat in parallel, Syngenta has sponsored the development of an mkin and KinGUII based GUI application called CAKE, which also adds IRLS and MCMC, is more limited in the model formulation, but puts more weight on usability. CAKE is available for download from the CAKE website, where you can also find a zip archive of the R scripts derived from mkin, published under the GPL license.

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Finally, there is KineticEval, which contains a further development of the scripts used for KinGUII, so the different tools will hopefully be able to learn from each other in the future as well.

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Development

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Contributions are welcome! Your mkin fork is just a mouse click away… The master branch on github should always be in good shape, I implement new features in separate branches now. If you prefer subversion, project members for the r-forge project are welcome as well. Generally, the source code of the latest CRAN version should be available there. You can also browse the source code at cgit.jrwb.de/mkin.

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- - - - - - diff --git a/docs/articles/FOCUS_D.R b/docs/articles/FOCUS_D.R deleted file mode 100644 index b831e14e..00000000 --- a/docs/articles/FOCUS_D.R +++ /dev/null @@ -1,24 +0,0 @@ -## ---- include = FALSE---------------------------------------------------- -library(knitr) -opts_chunk$set(tidy = FALSE, cache = TRUE) - -## ----data---------------------------------------------------------------- -library("mkin", quietly = TRUE) -print(FOCUS_2006_D) - -## ----model--------------------------------------------------------------- -SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO")) -print(SFO_SFO$diffs) - -## ----fit----------------------------------------------------------------- -fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) - -## ----plot, fig.height = 6, fig.width = 8--------------------------------- -plot_sep(fit, lpos = c("topright", "bottomright")) - -## ----plot_2, fig.height = 4, fig.width = 8------------------------------- -mkinparplot(fit) - -## ------------------------------------------------------------------------ -summary(fit) - diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index d9dd8ad5..af04f755 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -8,8 +8,11 @@ Example evaluation of FOCUS Example Dataset D • mkin - - + + + + @@ -77,7 +80,7 @@

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

-

2018-01-16

+

2018-03-01

@@ -85,7 +88,7 @@

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)
+print(FOCUS_2006_D)
##      name time  value
 ## 1  parent    0  99.46
 ## 2  parent    0 102.04
@@ -135,13 +138,13 @@
 
The call to mkinmod returns a degradation model. The differential equations represented in R code can be found in the character vector $diffs of the mkinmod object. If a C compiler (gcc) is installed and functional, the differential equation model will be compiled from auto-generated C code.

 
SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))

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

-
print(SFO_SFO$diffs)

+
print(SFO_SFO$diffs)

 
##                                                       parent 
 ## "d_parent = - k_parent_sink * parent - k_parent_m1 * parent" 
 ##                                                           m1 
 ##             "d_m1 = + k_parent_m1 * parent - k_m1_sink * m1"

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

-
fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)

+
fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)

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

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

 

@@ -150,10 +153,10 @@
 

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

 
summary(fit)

-
## mkin version:    0.9.46.1 
-## R version:       3.4.1 
-## Date of fit:     Thu Sep 14 12:15:01 2017 
-## Date of summary: Thu Sep 14 12:15:02 2017 
+
## mkin version:    0.9.46.3 
+## R version:       3.4.3 
+## Date of fit:     Thu Mar  1 14:17:55 2018 
+## Date of summary: Thu Mar  1 14:17:55 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -161,7 +164,7 @@
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 1.14 s
+## Fitted with method Port using 153 model solutions performed in 0.993 s
 ## 
 ## Weighting: none
 ## 
@@ -286,7 +289,7 @@
 
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/articles/FOCUS_D_files/figure-html/plot-1.png b/docs/articles/FOCUS_D_files/figure-html/plot-1.png
index 75c4c299..b4fa2ff4 100644
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diff --git a/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png b/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png
index 94e7e2b3..ba06ce31 100644
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diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html
index 42ec2df1..5de06ad5 100644
--- a/docs/articles/FOCUS_L.html
+++ b/docs/articles/FOCUS_L.html
@@ -8,8 +8,11 @@
 Example evaluation of FOCUS Laboratory Data L1 to L3 • mkin
 
 
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+
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@@ -77,7 +80,7 @@
       
Example evaluation of FOCUS Laboratory Data L1 to L3

                         
Johannes Ranke

             
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2018-01-16

+            
2018-03-01

           
 
     
@@ -88,27 +91,27 @@
 Laboratory Data L1
 
The following code defines example dataset L1 from the FOCUS kinetics report, p. 284:

 
library("mkin", quietly = TRUE)
-FOCUS_2006_L1 = data.frame(
+FOCUS_2006_L1 = data.frame(
   t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2),
   parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6,
              72.0, 71.9, 50.3, 59.4, 47.0, 45.1,
              27.7, 27.3, 10.0, 10.4, 2.9, 4.0))
-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)

+FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)

 
Here we use the assumptions of simple first order (SFO), the case of declining rate constant over time (FOMC) and the case of two different phases of the kinetics (DFOP). For a more detailed discussion of the models, please see the FOCUS kinetics report.

 
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.

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m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
+
m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
 summary(m.L1.SFO)

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:06 2018 
-## Date of summary: Tue Jan 16 06:11:06 2018 
+## Date of fit:     Thu Mar  1 14:31:57 2018 
+## Date of summary: Thu Mar  1 14:31:57 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 0.245 s
+## Fitted with method Port using 37 model solutions performed in 0.24 s
 ## 
 ## Weighting: none
 ## 
@@ -185,28 +188,21 @@ FOCUS_2006_L1_mkin <- 
mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")

 

 
For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked.

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m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)

-
## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation by method Port did not converge.
-## Convergence code is 1

-
plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

+
m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
+plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

 

 
summary(m.L1.FOMC, data = FALSE)

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:07 2018 
-## Date of summary: Tue Jan 16 06:11:07 2018 
-## 
-## 
-## Warning: Optimisation by method Port did not converge.
-## Convergence code is 1 
-## 
+## Date of fit:     Thu Mar  1 14:31:59 2018 
+## Date of summary: Thu Mar  1 14:32:00 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 155 model solutions performed in 0.424 s
+## Fitted with method Port using 611 model solutions performed in 1.375 s
 ## 
 ## Weighting: none
 ## 
@@ -226,16 +222,16 @@ FOCUS_2006_L1_mkin <-   
 Laboratory Data L2
 
The following code defines example dataset L2 from the FOCUS kinetics report, p. 287:

-
FOCUS_2006_L2 = data.frame(
+
FOCUS_2006_L2 = data.frame(
   t = rep(c(0, 1, 3, 7, 14, 28), each = 2),
   parent = c(96.1, 91.8, 41.4, 38.7,
              19.3, 22.3, 4.6, 4.6,
              2.6, 1.2, 0.3, 0.6))
-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)

+FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)

 

 

 SFO fit for L2

 
Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument show_residuals to the plot command.

-
m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
+
m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
 plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - SFO")

 

@@ -286,22 +282,22 @@ FOCUS_2006_L2_mkin <- 
 FOMC fit for L2
 
For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked.

-
m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
+
m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.FOMC, show_residuals = TRUE,
      main = "FOCUS L2 - FOMC")

 

 
summary(m.L2.FOMC, data = FALSE)

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:08 2018 
-## Date of summary: Tue Jan 16 06:11:08 2018 
+## Date of fit:     Thu Mar  1 14:32:00 2018 
+## Date of summary: Thu Mar  1 14:32:00 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 0.158 s
 ## 
 ## Weighting: none
 ## 
@@ -357,15 +353,15 @@ FOCUS_2006_L2_mkin <- 
 DFOP fit for L2
 
Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level.

-
m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
+
m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - DFOP")

 

 
summary(m.L2.DFOP, data = FALSE)

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:09 2018 
-## Date of summary: Tue Jan 16 06:11:09 2018 
+## Date of fit:     Thu Mar  1 14:32:01 2018 
+## Date of summary: Thu Mar  1 14:32:01 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -374,7 +370,7 @@ FOCUS_2006_L2_mkin <-  
 Laboratory Data L3
 
The following code defines example dataset L3 from the FOCUS kinetics report, p. 290.

-
FOCUS_2006_L3 = data.frame(
+
FOCUS_2006_L3 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(97.8, 60, 51, 43, 35, 22, 15, 12))
-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)

+FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)

 

 

 Fit multiple models

 
As of mkin version 0.9-39 (June 2015), we can fit several models to one or more datasets in one call to the function mmkin. The datasets have to be passed in a list, in this case a named list holding only the L3 dataset prepared above.

 
# Only use one core here, not to offend the CRAN checks
 mm.L3 <- mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
-               list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
+               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.

@@ -454,10 +450,10 @@ mm.L3 <- 
summary(mm.L3[["DFOP", 1]])

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:10 2018 
-## Date of summary: Tue Jan 16 06:11:10 2018 
+## Date of fit:     Thu Mar  1 14:32:02 2018 
+## Date of summary: Thu Mar  1 14:32:02 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -542,30 +538,30 @@ mm.L3 <- 
 Laboratory Data L4
 
The following code defines example dataset L4 from the FOCUS kinetics report, p. 293:

-
FOCUS_2006_L4 = data.frame(
+
FOCUS_2006_L4 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(96.6, 96.3, 94.3, 88.8, 74.9, 59.9, 53.5, 49.0))
-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)

+FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)

 
Fits of the SFO and FOMC models, plots and summaries are produced below:

 
# Only use one core here, not to offend the CRAN checks
 mm.L4 <- mmkin(c("SFO", "FOMC"), cores = 1,
-               list("FOCUS L4" = FOCUS_2006_L4_mkin),
+               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:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:10 2018 
-## Date of summary: Tue Jan 16 06:11:10 2018 
+## Date of fit:     Thu Mar  1 14:32:03 2018 
+## Date of summary: Thu Mar  1 14:32:03 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 0.094 s
+## Fitted with method Port using 46 model solutions performed in 0.089 s
 ## 
 ## Weighting: none
 ## 
@@ -615,17 +611,17 @@ mm.L4 <- 
summary(mm.L4[["FOMC", 1]], data = FALSE)

-
## mkin version:    0.9.47.1 
+
## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Tue Jan 16 06:11:10 2018 
-## Date of summary: Tue Jan 16 06:11:10 2018 
+## Date of fit:     Thu Mar  1 14:32:03 2018 
+## Date of summary: Thu Mar  1 14:32:03 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 0.139 s
+## Fitted with method Port using 66 model solutions performed in 0.134 s
 ## 
 ## Weighting: none
 ## 
@@ -690,7 +686,8 @@ mm.L4 <- 
         

-      
Contents

+      

+Contents

       

 
       
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diff --git a/docs/articles/FOCUS_Z.R b/docs/articles/FOCUS_Z.R
deleted file mode 100644
index 4d2dffca..00000000
--- a/docs/articles/FOCUS_Z.R
+++ /dev/null
@@ -1,115 +0,0 @@
-## ---- include = FALSE----------------------------------------------------
-require(knitr)
-options(digits = 5)
-opts_chunk$set(engine='R', tidy = FALSE)
-
-## ---- echo = TRUE, fig = TRUE, fig.width = 8, fig.height = 7-------------
-library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
-
-## ----FOCUS_2006_Z_fits_1, echo=TRUE, fig.height=6------------------------
-Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
-m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.2a)
-summary(m.Z.2a, data = FALSE)$bpar
-
-## ----FOCUS_2006_Z_fits_2, echo=TRUE, fig.height=6------------------------
-Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
-
-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)$bpar
-
-## ----FOCUS_2006_Z_fits_3, echo=TRUE, fig.height=6------------------------
-Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
-m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.3)
-summary(m.Z.3, data = FALSE)$bpar
-
-## ----FOCUS_2006_Z_fits_5, echo=TRUE, fig.height=7------------------------
-Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
-m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.5)
-
-## ----FOCUS_2006_Z_fits_6, echo=TRUE, fig.height=8------------------------
-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")
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
-plot_sep(m.Z.FOCUS)
-summary(m.Z.FOCUS, data = FALSE)$bpar
-endpoints(m.Z.FOCUS)
-
-## ----FOCUS_2006_Z_fits_7, echo=TRUE, fig.height=8------------------------
-Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
-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)$cov.unscaled
-
-## ----FOCUS_2006_Z_fits_9, echo=TRUE, fig.height=8------------------------
-Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
-m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.3)
-
-## ----FOCUS_2006_Z_fits_10, echo=TRUE, fig.height=8-----------------------
-Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.4)
-
-## ----FOCUS_2006_Z_fits_11, echo=TRUE, fig.height=8-----------------------
-Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.5)
-
-## ----FOCUS_2006_Z_fits_11a, echo=TRUE------------------------------------
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
-plot_sep(m.Z.mkin.5a)
-
-## ----FOCUS_2006_Z_fits_11b, echo=TRUE------------------------------------
-mkinparplot(m.Z.mkin.5a)
-
-## ----FOCUS_2006_Z_fits_11b_endpoints, echo=TRUE--------------------------
-endpoints(m.Z.mkin.5a)
-
diff --git a/docs/articles/FOCUS_Z.Rnw b/docs/articles/FOCUS_Z.Rnw
deleted file mode 100644
index 5abda0e1..00000000
--- a/docs/articles/FOCUS_Z.Rnw
+++ /dev/null
@@ -1,274 +0,0 @@
-%\VignetteIndexEntry{Example evaluation of FOCUS dataset Z}
-%\VignetteEngine{knitr::knitr}
-\documentclass[12pt,a4paper]{article}
-\usepackage{a4wide}
-\input{header}
-\hypersetup{
-  pdftitle = {Example evaluation of FOCUS dataset Z},
-  pdfsubject = {Manuscript},
-  pdfauthor = {Johannes Ranke},
-  colorlinks = {true},
-  linkcolor = {blue},
-  citecolor = {blue},
-  urlcolor = {red},
-  hyperindex = {true},
-  linktocpage = {true},
-}
-
-\begin{document}
-
-<>=
-require(knitr)
-opts_chunk$set(engine='R', tidy = FALSE, cache = TRUE)
-options(width=70)
-@
-
-\title{Example evaluation of FOCUS dataset Z}
-\author{\textbf{Johannes Ranke} \\[0.5cm]
-%EndAName
-Wissenschaftlicher Berater\\
-Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany\\[0.5cm]
-and\\[0.5cm]
-University of Bremen\\
-}
-\maketitle
-
-\thispagestyle{empty} \setcounter{page}{0}
-
-\clearpage
-
-\tableofcontents
-
-\textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation
-
-\section{The data}
-
-The following code defines the example dataset from Appendix 7 to the FOCUS kinetics
-report \citep{FOCUSkinetics2011}, p.350.
-
-<>=
-require(mkin)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
-@
-
-\section{Parent compound and one metabolite}
-
-The next step is to set up the models used for the kinetic analysis. As the
-simultaneous fit of parent and the first metabolite is usually straightforward,
-Step 1 (SFO for parent only) is skipped here. We start with the model 2a,
-with formation and decline of metabolite Z1 and the pathway from parent
-directly to sink included (default in mkin).
-
-<>=
-Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
-m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.2a)
-summary(m.Z.2a, data = FALSE)$bpar
-@
-
-As obvious from the parameter summary (the \texttt{bpar} component of the
-summary), the kinetic rate constant from parent compound Z to sink
-is negligible. Accordingly, the exact magnitude of the fitted parameter
-\texttt{log k\_Z0\_sink} is ill-defined and the covariance matrix is not
-returned (not shown, would be visible in the complete summary).
-This suggests, in agreement with the analysis in the FOCUS kinetics report, to
-simplify the model by removing the pathway to sink.
-
-A similar result can be obtained when formation fractions are used in the model
-formulation:
-
-<>=
-Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
-
-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)$bpar
-@
-
-Here, the ilr transformed formation fraction fitted in the model takes a very
-large value, and the backtransformed formation fraction from parent Z to Z1 is
-practically unity. Again, the covariance matrix is not returned as the model is
-overparameterised.
-
-The simplified model is obtained by setting the list component \texttt{sink} to
-\texttt{FALSE}.\footnote{If the model formulation without formation fractions
-is used, the same effect can be obtained by fixing the parameter \texttt{k\_Z\_sink}
-to a value of zero.}
-
-In the following, we use the parameterisation with formation fractions in order
-to be able to compare with the results in the FOCUS guidance, and as it
-makes it easier to use parameters obtained in a previous fit when adding a further
-metabolite.
-
-<>=
-Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
-m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.3)
-summary(m.Z.3, data = FALSE)$bpar
-@
-
-As there is only one transformation product for Z0 and no pathway
-to sink, the formation fraction is internally fixed to unity.
-
-\section{Including 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")
-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),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
-plot_sep(m.Z.FOCUS)
-summary(m.Z.FOCUS, data = FALSE)$bpar
-endpoints(m.Z.FOCUS)
-@
-
-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.
-
-\section{Using the SFORB model for parent and metabolites}
-
-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"))
-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)$cov.unscaled
-@
-
-Therefore, a further stepwise model building is performed starting from the
-stage of parent and two metabolites, starting from the assumption that the model
-fit for the parent compound can be improved by using the SFORB model.
-
-<>=
-Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
-m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.3)
-@
-
-This results in a much better representation of the behaviour of the parent
-compound Z0.
-
-Finally, Z3 is added as well. These models appear overparameterised (no
-covariance matrix returned) if the sink for Z1 is left in the models.
-
-<>=
-Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.4)
-@
-
-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"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.5)
-@
-
-The summary view of the backtransformed parameters shows that we get no
-confidence intervals due to overparameterisation. As the optimized
-\texttt{k\_Z3\_bound\_free} is excessively small, it seems reasonable to fix it to
-zero.
-
-<>=
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
-plot_sep(m.Z.mkin.5a)
-@
-
-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
-\texttt{Z.mkin.5a} 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)
-@
-
-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.
-
-\bibliographystyle{plainnat}
-\bibliography{references}
-
-\end{document}
-% vim: set foldmethod=syntax:
diff --git a/docs/articles/FOCUS_Z.html b/docs/articles/FOCUS_Z.html
index a5cfc616..52a1db77 100644
--- a/docs/articles/FOCUS_Z.html
+++ b/docs/articles/FOCUS_Z.html
@@ -8,8 +8,11 @@
 Example evaluation of FOCUS dataset Z • mkin
 
 
-
-
+
+
+
+
@@ -77,7 +80,7 @@
       
Example evaluation of FOCUS dataset Z

                         
Johannes Ranke

             
-            
2018-01-16

+            
2018-03-01

           

 
     
@@ -90,64 +93,64 @@
 
The following code defines the example dataset from Appendix 7 to the FOCUS kinetics report (FOCUS Work Group on Degradation Kinetics 2014, 354).

 
library(mkin, quietly = TRUE)
 LOD = 0.5
-FOCUS_2006_Z = data.frame(
+FOCUS_2006_Z = data.frame(
   t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
         42, 61, 96, 124),
   Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
          2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
   Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
          25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
 
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)

+FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)

 

 

 

 Parent and one metabolite

 
The next step is to set up the models used for the kinetic analysis. As the simultaneous fit of parent and the first metabolite is usually straightforward, Step 1 (SFO for parent only) is skipped here. We start with the model 2a, with formation and decline of metabolite Z1 and the pathway from parent directly to sink included (default in mkin).

-
Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+
Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
                 Z1 = mkinsub("SFO"))

 
## 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)

+
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   3.553135 2.7304e+01 1.6792e-21 91.4014 102.62838
-## k_Z0_sink 6.2135e-10   0.226894 2.7385e-09 5.0000e-01  0.0000       Inf
-## k_Z0_Z1   2.2360e+00   0.165073 1.3546e+01 7.3939e-14  1.8374   2.72107
-## k_Z1_sink 4.8212e-01   0.065854 7.3212e+00 3.5520e-08  0.4006   0.58024

+
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
+## k_Z0_sink 1.2790e-11   0.226895 5.6368e-11 5.0000e-01    NA    NA
+## k_Z0_Z1   2.2360e+00   0.165073 1.3546e+01 7.3938e-14    NA    NA
+## k_Z1_sink 4.8212e-01   0.065854 7.3212e+00 3.5520e-08    NA    NA

 
As obvious from the parameter summary (the  component of the summary), the kinetic rate constant from parent compound Z to sink is very small and the t-test for this parameter suggests that it is not significantly different from zero. This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify the model by removing the pathway to sink.

 
A similar result can be obtained when formation fractions are used in the model formulation:

-
Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+
Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
                    Z1 = mkinsub("SFO"),
                    use_of_ff = "max")

 
## 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)

+
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

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

 
##            Estimate se_notrans t value     Pr(>t) Lower Upper
-## Z0_0       97.01488   3.553146 27.3039 1.6793e-21    NA    NA
-## k_Z0        2.23601   0.216847 10.3114 3.6617e-11    NA    NA
+## Z0_0       97.01488   3.553145 27.3039 1.6793e-21    NA    NA
+## k_Z0        2.23601   0.216849 10.3114 3.6623e-11    NA    NA
 ## k_Z1        0.48212   0.065854  7.3211 3.5520e-08    NA    NA
-## f_Z0_to_Z1  1.00000   0.101473  9.8548 9.7071e-11    NA    NA

+## f_Z0_to_Z1  1.00000   0.101473  9.8548 9.7068e-11    NA    NA

 
Here, the ilr transformed formation fraction fitted in the model takes a very large value, and the backtransformed formation fraction from parent Z to Z1 is practically unity. Here, the covariance matrix used for the calculation of confidence intervals is not returned as the model is overparameterised.

 
A simplified model is obtained by removing the pathway to the sink. 

 
In the following, we use the parameterisation with formation fractions in order to be able to compare with the results in the FOCUS guidance, and as it makes it easier to use parameters obtained in a previous fit when adding a further metabolite.

 
Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
                Z1 = mkinsub("SFO"), use_of_ff = "max")

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

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

 

-
summary(m.Z.3, data = FALSE)$bpar

+
summary(m.Z.3, data = FALSE)$bpar

 
##      Estimate se_notrans t value     Pr(>t)    Lower   Upper
-## Z0_0 97.01488   2.681771  36.176 2.3636e-25 91.52152 102.508
-## k_Z0  2.23601   0.146862  15.225 2.2470e-15  1.95453   2.558
+## Z0_0 97.01488   2.681772  36.176 2.3636e-25 91.52152 102.508
+## k_Z0  2.23601   0.146861  15.225 2.2464e-15  1.95453   2.558
 ## k_Z1  0.48212   0.042687  11.294 3.0686e-12  0.40216   0.578

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

 

@@ -159,7 +162,7 @@ FOCUS_2006_Z_mkin <- 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)
+
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.

@@ -169,25 +172,25 @@ FOCUS_2006_Z_mkin <- 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$bparms.ode,
+
m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
+                     parms.ini = m.Z.5$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

 
plot_sep(m.Z.FOCUS)

 

-
summary(m.Z.FOCUS, data = FALSE)$bpar

-
##            Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.84024   2.058814 47.0369 5.5723e-44 92.706852 100.973637
-## k_Z0        2.21540   0.118128 18.7543 7.7369e-25  1.990504   2.465708
-## k_Z1        0.47836   0.029294 16.3298 3.3443e-22  0.423035   0.540918
-## k_Z2        0.45166   0.044186 10.2218 3.0364e-14  0.371065   0.549767
-## k_Z3        0.05869   0.014290  4.1072 7.2560e-05  0.035983   0.095725
-## f_Z2_to_Z3  0.47147   0.057027  8.2676 2.7790e-11  0.360295   0.585556

+
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)

 
## $ff
 ##   Z2_Z3 Z2_sink 
-## 0.47147 0.52853 
+## 0.47152 0.52848 
 ## 
 ## $SFORB
 ## logical(0)
@@ -195,9 +198,9 @@ FOCUS_2006_Z_mkin <- 
@@ -210,17 +213,17 @@ FOCUS_2006_Z_mkin <- 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)
+
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

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

 
## NULL

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

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

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

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

@@ -230,8 +233,8 @@ FOCUS_2006_Z_mkin <- 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$bparms.ode,
+
m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.3$bparms.ode,
                       quiet = TRUE)
 plot_sep(m.Z.mkin.4)

 

@@ -241,36 +244,36 @@ FOCUS_2006_Z_mkin <- 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$bparms.ode[1:4],
+
m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
                       quiet = TRUE)
 plot_sep(m.Z.mkin.5)

 

 
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$bparms.ode[1:7],
+
m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
                                      k_Z3_bound_free = 0),
                        fixed_parms = "k_Z3_bound_free",
                        quiet = TRUE)
-plot_sep(m.Z.mkin.5a)

+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 
-## 2.4471373 0.0075126 0.0800076 0.0000000 
+## 2.4471382 0.0075127 0.0800075 0.0000000 
 ## 
 ## $distimes
 ##      DT50   DT90 DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
-## Z0 0.3043 1.1848    0.28325     92.265         NA         NA
+## Z0 0.3043 1.1848    0.28325     92.264         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

@@ -291,7 +294,8 @@ FOCUS_2006_Z_mkin <- 
         

-      
Contents

+      

+Contents

       

 
       
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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diff --git a/docs/articles/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/articles/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png
index 79f1b87e..891d8d92 100644
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diff --git a/docs/articles/compiled_models.R b/docs/articles/compiled_models.R
deleted file mode 100644
index c5b06c11..00000000
--- a/docs/articles/compiled_models.R
+++ /dev/null
@@ -1,55 +0,0 @@
-## ---- include = FALSE----------------------------------------------------
-library(knitr)
-opts_chunk$set(tidy = FALSE, cache = FALSE)
-
-## ----check_gcc-----------------------------------------------------------
-Sys.which("gcc")
-
-## ----create_SFO_SFO------------------------------------------------------
-library("mkin", quietly = TRUE)
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-
-## ----benchmark_SFO_SFO, fig.height = 3-----------------------------------
-if (require(rbenchmark)) {
-  b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                      solution_type = "deSolve",
-                                      use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                 solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                  solution_type = "deSolve", quiet = TRUE),
-    replications = 3)
-  print(b.1)
-  factor_SFO_SFO <- round(b.1["1", "relative"])
-} else {
-  factor_SFO_SFO <- NA
-  print("R package benchmark is not available")
-}
-
-## ----benchmark_FOMC_SFO, fig.height = 3----------------------------------
-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")
-}
-
-## ----sessionInfo, echo = FALSE-------------------------------------------
-cat(capture.output(sessionInfo())[1:3], sep = "\n")
-if(!inherits(try(cpuinfo <- readLines("/proc/cpuinfo")), "try-error")) {
-  cat(gsub("model name\t: ", "CPU model: ", cpuinfo[grep("model name", cpuinfo)[1]]))
-}
-
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index d5d29a1a..9f0b5708 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -8,8 +8,11 @@
 Performance benefit by using compiled model definitions in mkin • mkin
 
 
-
-
+
+
+
+
@@ -77,7 +80,7 @@
       
Performance benefit by using compiled model definitions in mkin

                         
Johannes Ranke

             
-            
2018-01-16

+            
2018-03-01

           

 
     
@@ -97,73 +100,66 @@ SFO_SFO <- m1 = mkinsub("SFO"))

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

 
We can compare the performance of the Eigenvalue based solution against the compiled version and the R implementation of the differential equations using the benchmark package.

-
if (require(rbenchmark)) {
+
if (require(rbenchmark)) {
   b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
+    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                       solution_type = "deSolve",
                                       use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
+    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                  solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
+    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                   solution_type = "deSolve", quiet = TRUE),
     replications = 3)
   print(b.1)
   factor_SFO_SFO <- round(b.1["1", "relative"])
-} else {
+} else {
   factor_SFO_SFO <- NA
   print("R package benchmark is not available")
 }

 
## Lade nötiges Paket: rbenchmark

-
##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   1.940    1.000     1.940        0
-## 1 deSolve, not compiled            3  13.865    7.147    13.864        0
-## 2      Eigenvalue based            3   2.427    1.251     2.428        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 7 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.

+
## Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
+## logical.return = TRUE, : es gibt kein Paket namens 'rbenchmark'

+
## [1] "R package benchmark is not available"

+
We see that using the compiled model is by a factor of around NA 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)) {
+
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,
+    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
                                       use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, 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 {
+} else {
   factor_FOMC_SFO <- NA
   print("R package benchmark is not available")
 }

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

-
##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   3.432    1.000     3.428        0
-## 1 deSolve, not compiled            3  28.844    8.404    28.840        0
-##   user.child sys.child
-## 2          0         0
-## 1          0         0

-
Here we get a performance benefit of a factor of 8 using the version of the differential equation model compiled from C code!

-
This vignette was built with mkin 0.9.47.1 on

+
## Lade nötiges Paket: rbenchmark

+
## Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
+## logical.return = TRUE, : es gibt kein Paket namens 'rbenchmark'

+
## [1] "R package benchmark is not available"

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

+
This vignette was built with mkin 0.9.46.3 on

 
## R version 3.4.3 (2017-11-30)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 9 (stretch)

-
## CPU model: Intel(R) Core(TM) i7-4710MQ CPU @ 2.50GHz

+
## CPU model: AMD Ryzen 7 1700 Eight-Core Processor

 

 

   

 
   
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/articles/mkin.R b/docs/articles/mkin.R
deleted file mode 100644
index 19e80322..00000000
--- a/docs/articles/mkin.R
+++ /dev/null
@@ -1,34 +0,0 @@
-## ---- include = FALSE----------------------------------------------------
-require(knitr)
-opts_chunk$set(engine='R', tidy=FALSE)
-
-## ---- echo = TRUE, cache = TRUE, fig = TRUE, fig.width = 8, fig.height = 7----
-library("mkin", quietly = TRUE)
-# Define the kinetic model
-m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
-                         M1 = mkinsub("SFO", "M2"),
-                         M2 = mkinsub("SFO"),
-                         use_of_ff = "max", quiet = TRUE)
-
-
-# Produce model predictions using some arbitrary parameters
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
-  c(k_parent = 0.03,
-    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
-    f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
-  c(parent = 100, M1 = 0, M2 = 0),
-  sampling_times)
-
-# Generate a dataset by adding normally distributed errors with
-# standard deviation 3, for two replicates at each sampling time
-d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
-                             sdfunc = function(x) 3,
-                             n = 1, seed = 123456789 )
-
-# Fit the model to the dataset
-f_SFO_SFO_SFO <- mkinfit(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[1]], quiet = TRUE)
-
-# Plot the results separately for parent and metabolites
-plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright", "bottomright"))
-
diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html
index b70918ab..a91da0a4 100644
--- a/docs/articles/mkin.html
+++ b/docs/articles/mkin.html
@@ -8,8 +8,11 @@
 Introduction to mkin • mkin
 
 
-
-
+
+
+
+
@@ -77,7 +80,7 @@
       
Introduction to mkin

                         
Johannes Ranke

             
-            
2018-01-16

+            
2018-03-01

           
 
     
@@ -100,15 +103,15 @@ m_SFO_SFO_SFO <-  c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
   c(k_parent = 0.03,
-    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
-    f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
+    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
+    f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
   c(parent = 100, M1 = 0, M2 = 0),
   sampling_times)
 
 # Generate a dataset by adding normally distributed errors with
 # standard deviation 3, for two replicates at each sampling time
 d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
-                             sdfunc = function(x) 3,
+                             sdfunc = function(x) 3,
                              n = 1, seed = 123456789 )
 
 # Fit the model to the dataset
@@ -208,7 +211,8 @@ f_SFO_SFO_SFO <- 
         

-      
Contents

+      

+Contents

       

 
       
diff --git a/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png b/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png
index fafe8afd..5a3e3b6c 100644
Binary files a/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png and b/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png differ
diff --git a/docs/articles/twa.R b/docs/articles/twa.R
deleted file mode 100644
index 8b137891..00000000
--- a/docs/articles/twa.R
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/docs/articles/twa.html b/docs/articles/twa.html
index 086c8593..400b1383 100644
--- a/docs/articles/twa.html
+++ b/docs/articles/twa.html
@@ -8,8 +8,11 @@
 Calculation of time weighted average concentrations with mkin • mkin
 
 
-
-
+
+
+
+
@@ -77,7 +80,7 @@
       
Calculation of time weighted average concentrations with mkin

                         
Johannes Ranke

             
-            
2018-01-16

+            
2018-03-01

           
 
     
@@ -126,7 +129,7 @@
 
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/authors.html b/docs/authors.html
index 7f3918c8..7abb53de 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -18,12 +18,16 @@
 
 
 
+
+
 
 
 
 
 
-
+  
+  
+
 
 
 
@@ -103,19 +107,19 @@
 
     
    
       
  • 
-        
    Johannes Ranke. Author, maintainer, copyright holder.
-        
    0000-0003-4371-6538
    
+        
    Johannes Ranke. Author, maintainer, copyright holder. 
+        
    
       
    • 
       
  • 
-        
    Katrin Lindenberger. Contributor.
+        
    Katrin Lindenberger. Contributor. 
         
    
       
    • 
       
  • 
-        
    René Lehmann. Contributor.
+        
    René Lehmann. Contributor. 
         
    
       
    • 
       
  • 
-        
    Eurofins Regulatory AG. Copyright holder.
+        
    Eurofins Regulatory AG. Copyright holder. 
         
    
       
    • 
     

@@ -131,7 +135,7 @@
 
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/index.html b/docs/index.html
index 2f46d730..c20d124b 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -8,8 +8,18 @@
 Kinetic Evaluation of Chemical Degradation Data • mkin
 
 
-
-
+
+
+
+
@@ -159,8 +169,7 @@
 
GPL

 
Developers

 
    
-
  • Johannes Ranke 
     Author, maintainer, copyright holder  
    (0000-0003-4371-6538)
-
    • 
+
  • Johannes Ranke 
     Author, maintainer, copyright holder   
    • 
 
  • All authors...
    • 
 

 
Dev status

@@ -176,7 +185,7 @@
 
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/news/index.html b/docs/news/index.html
index 64e4e9bc..dfb70875 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -18,12 +18,16 @@
 
 
 
+
+
 
 
 
 
 
-
+  
+  
+
 
 
 
@@ -629,7 +633,7 @@
 
 
 

-  
Site built with pkgdown.

+  
Site built with pkgdown.

 

 
       
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
index fd7b0ba4..181fe639 100644
--- a/docs/pkgdown.css
+++ b/docs/pkgdown.css
@@ -34,13 +34,14 @@ img.icon {
   float: right;
 }
 
-/* Section anchors ---------------------------------*/
-
-.hasAnchor {
-  margin-left: -30px;
+img {
+  max-width: 100%;
 }
 
+/* Section anchors ---------------------------------*/
+
 a.anchor {
+  margin-left: -30px;
   display:inline-block;
   width: 30px;
   height: 30px;
@@ -56,6 +57,13 @@ a.anchor {
   visibility: visible;
 }
 
+@media (max-width: 767px) {
+  .hasAnchor:hover a.anchor {
+    visibility: hidden;
+  }
+}
+
+
 /* Fixes for fixed navbar --------------------------*/
 
 .contents h1, .contents h2, .contents h3, .contents h4 {
@@ -63,6 +71,17 @@ a.anchor {
   margin-top: -60px;
 }
 
+/* Static header placement on mobile devices */
+@media (max-width: 767px) {
+  .navbar-fixed-top {
+    position: absolute;
+  }
+  .navbar {
+    padding: 0;
+  }
+}
+
+
 /* Sidebar --------------------------*/
 
 #sidebar {
@@ -81,33 +100,95 @@ a.anchor {
   margin-bottom: 0.5em;
 }
 
+.orcid {
+  height: 16px;
+  vertical-align: middle;
+}
+
+/* Reference index & topics ----------------------------------------------- */
+
+.ref-index th {font-weight: normal;}
+.ref-index h2 {font-size: 20px;}
+
+.ref-index td {vertical-align: top;}
+.ref-index .alias {width: 40%;}
+.ref-index .title {width: 60%;}
+
+.ref-index .alias {width: 40%;}
+.ref-index .title {width: 60%;}
+
+.ref-arguments th {text-align: right; padding-right: 10px;}
+.ref-arguments th, .ref-arguments td {vertical-align: top;}
+.ref-arguments .name {width: 20%;}
+.ref-arguments .desc {width: 80%;}
+
+/* Nice scrolling for wide elements --------------------------------------- */
+
+table {
+  display: block;
+  overflow: auto;
+}
+
 /* Syntax highlighting ---------------------------------------------------- */
 
-code {
-  background-color: #f7f7f7;
-  color: #333;
+pre {
+  word-wrap: normal;
+  word-break: normal;
+  border: 1px solid #eee;
 }
-code a {
-  color: #375f84;
+
+pre, code {
+  background-color: #f8f8f8;
+  color: #333;
 }
 
-.warning { color: red; }
-.message { font-weight: bolder; }
-.error   { color: red; font-weight: bolder; }
+pre code {
+  overflow: auto;
+  word-wrap: normal;
+  white-space: pre;
+}
 
-.fl,.number {color:rgb(21,20,181);}
-.fu,.functioncall {color:#264D66 ;}
-.ch,.st,.string {color:#375D81 ;}
-.kw,.keyword {color:black;}
-.argument {color:#264D66 ;}
-.co,.comment {color: #777;}
-.formalargs {color: #264D66;}
-.eqformalargs {color:#264D66;}
-.slot {font-style:italic;}
-.symbol {color:black ;}
-.prompt {color:black ;}
+pre .img {
+  margin: 5px 0;
+}
 
-pre img {
+pre .img img {
   background-color: #fff;
   display: block;
+  height: auto;
+}
+
+code a, pre a {
+  color: #375f84;
+}
+
+a.sourceLine:hover {
+  text-decoration: none;
+}
+
+.fl      {color: #1514b5;}
+.fu      {color: #000000;} /* function */
+.ch,.st  {color: #036a07;} /* string */
+.kw      {color: #264D66;} /* keyword */
+.co      {color: #888888;} /* comment */
+
+.message { color: black;   font-weight: bolder;}
+.error   { color: orange;  font-weight: bolder;}
+.warning { color: #6A0366; font-weight: bolder;}
+
+/* Clipboard --------------------------*/
+
+.hasCopyButton {
+  position: relative;
+}
+
+.btn-copy-ex {
+  position: absolute;
+  right: 0;
+  top: 0;
+  visibility: hidden;
+}
+
+.hasCopyButton:hover button.btn-copy-ex {
+  visibility: visible;
 }
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
index c8b38c49..64b20df4 100644
--- a/docs/pkgdown.js
+++ b/docs/pkgdown.js
@@ -1,8 +1,94 @@
 $(function() {
-  $("#sidebar").stick_in_parent({offset_top: 40});
+
+  $("#sidebar")
+    .stick_in_parent({offset_top: 40})
+    .on('sticky_kit:bottom', function(e) {
+      $(this).parent().css('position', 'static');
+    })
+    .on('sticky_kit:unbottom', function(e) {
+      $(this).parent().css('position', 'relative');
+    });
+
   $('body').scrollspy({
     target: '#sidebar',
     offset: 60
   });
 
+  var cur_path = paths(location.pathname);
+  $("#navbar ul li a").each(function(index, value) {
+    if (value.text == "Home")
+      return;
+    if (value.getAttribute("href") === "#")
+      return;
+
+    var path = paths(value.pathname);
+    if (is_prefix(cur_path, path)) {
+      // Add class to parent 
  • , and enclosing 
  •  if in dropdown
+      var menu_anchor = $(value);
+      menu_anchor.parent().addClass("active");
+      menu_anchor.closest("li.dropdown").addClass("active");
+    }
+  });
 });
+
+function paths(pathname) {
+  var pieces = pathname.split("/");
+  pieces.shift(); // always starts with /
+
+  var end = pieces[pieces.length - 1];
+  if (end === "index.html" || end === "")
+    pieces.pop();
+  return(pieces);
+}
+
+function is_prefix(needle, haystack) {
+  if (needle.length > haystack.lengh)
+    return(false);
+
+  for (var i = 0; i < haystack.length; i++) {
+    if (needle[i] != haystack[i])
+      return(false);
+  }
+
+  return(true);
+}
+
+/* Clipboard --------------------------*/
+
+function changeTooltipMessage(element, msg) {
+  var tooltipOriginalTitle=element.getAttribute('data-original-title');
+  element.setAttribute('data-original-title', msg);
+  $(element).tooltip('show');
+  element.setAttribute('data-original-title', tooltipOriginalTitle);
+}
+
+if(Clipboard.isSupported()) {
+  $(document).ready(function() {
+    var copyButton = "";
+
+    $(".examples").addClass("hasCopyButton");
+
+    // Insert copy buttons:
+    $(copyButton).prependTo(".hasCopyButton");
+
+    // Initialize tooltips:
+    $('.btn-copy-ex').tooltip({container: 'body'});
+
+    // Initialize clipboard:
+    var clipboardBtnCopies = new Clipboard('[data-clipboard-copy]', {
+      text: function(trigger) {
+        return trigger.parentNode.textContent;
+      }
+    });
+
+    clipboardBtnCopies.on('success', function(e) {
+      changeTooltipMessage(e.trigger, 'Copied!');
+      e.clearSelection();
+    });
+
+    clipboardBtnCopies.on('error', function() {
+      changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
+    });
+  });
+}
+
diff --git a/docs/reference/DFOP.solution-1.png b/docs/reference/DFOP.solution-1.png
new file mode 100644
index 00000000..1549a73b
Binary files /dev/null and b/docs/reference/DFOP.solution-1.png differ
diff --git a/docs/reference/DFOP.solution-2.png b/docs/reference/DFOP.solution-2.png
deleted file mode 100644
index 0902b9df..00000000
Binary files a/docs/reference/DFOP.solution-2.png and /dev/null differ
diff --git a/docs/reference/DFOP.solution.html b/docs/reference/DFOP.solution.html
index 30b9d057..ff1ad823 100644
--- a/docs/reference/DFOP.solution.html
+++ b/docs/reference/DFOP.solution.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +77,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +94,7 @@
       
       
       
     
   
@@ -146,11 +152,11 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
-    
      plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim=c(0,100))
    
+    
      plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim=c(0,100))
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html
index 5d4eca29..11738484 100644
--- a/docs/reference/Extract.mmkin.html
+++ b/docs/reference/Extract.mmkin.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +76,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +93,7 @@
       
       
       
     
   
@@ -147,16 +152,16 @@
                 cores = 1, quiet = TRUE)
   fits["FOMC", ]
    #>       dataset
 #> model  B       C      
-#>   FOMC List,42 List,42
+#>   FOMC List,45 List,45
 #> attr(,"class")
 #> [1] "mmkin"
      fits[, "B"]
    #>       dataset
 #> model  B      
-#>   SFO  List,42
-#>   FOMC List,42
+#>   SFO  List,45
+#>   FOMC List,45
 #> attr(,"class")
 #> [1] "mmkin"
      fits["SFO", "B"]
    #>      dataset
 #> model B      
-#>   SFO List,42
+#>   SFO List,45
 #> attr(,"class")
 #> [1] "mmkin"
    
   head(
@@ -164,7 +169,7 @@
     fits[["FOMC", "B"]]
   )
    #> $par
 #>  parent_0 log_alpha  log_beta 
-#> 99.666192  2.549849  5.050586 
+#> 99.666193  2.549849  5.050586 
 #> 
 #> $ssr
 #> [1] 28.58291
@@ -180,7 +185,7 @@
 #>       25       78 
 #> 
 #> $counts
-#> [1] "both X-convergence and relative convergence (5)"
+#> [1] "relative convergence (4)"
 #> 
    
   head(
   # The same can be achieved by
@@ -258,7 +263,7 @@
 #> 
 #> $time
 #>    user  system elapsed 
-#>   0.064   0.000   0.063 
+#>   0.058   0.000   0.057 
 #> 
 #> $mkinmod
 #> <mkinmod> model generated with
@@ -398,7 +403,7 @@
 #> {
 #>     assign("calls", calls + 1, inherits = TRUE)
 #>     if (trace_parms) 
-#>         cat(P, "\\n")
+#>         cat(P, "\n")
 #>     if (length(state.ini.optim) > 0) {
 #>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
 #>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
@@ -420,7 +425,7 @@
 #>     if (mC$model < cost.old) {
 #>         if (!quiet) 
 #>             cat("Model cost at call ", calls, ": ", mC$model, 
-#>                 "\\n")
+#>                 "\n")
 #>         if (plot) {
 #>             outtimes_plot = seq(min(observed$time), max(observed$time), 
 #>                 length.out = 100)
@@ -447,8 +452,8 @@
 #>     }
 #>     return(mC)
 #> }
-#> <bytecode: 0x560110508c60>
-#> <environment: 0x56010f8d8c30>
+#> <bytecode: 0x55555ad80908>
+#> <environment: 0x55555b1b4b90>
 #> 
 #> $cost_notrans
 #> function (P) 
@@ -470,8 +475,8 @@
 #>         scaleVar = scaleVar)
 #>     return(mC)
 #> }
-#> <bytecode: 0x56010fede550>
-#> <environment: 0x56010f8d8c30>
+#> <bytecode: 0x55555b174428>
+#> <environment: 0x55555b1b4b90>
 #> 
 #> $hessian_notrans
 #>                   parent_0 k_parent_sink
@@ -512,6 +517,10 @@
 #> $weight.ini
 #> [1] "none"
 #> 
+#> $tc.ini
+#> sigma_low  rsd_high 
+#>      0.50      0.07 
+#> 
 #> $reweight.tol
 #> [1] 1e-08
 #> 
@@ -534,7 +543,13 @@
 #> 99.17407 
 #> 
 #> $date
-#> [1] "Sat Jul 29 15:14:04 2017"
+#> [1] "Thu Mar  1 14:26:09 2018"
+#> 
+#> $version
+#> [1] "0.9.47.1"
+#> 
+#> $Rversion
+#> [1] "3.4.3"
 #> 
 #> attr(,"class")
 #> [1] "mkinfit" "modFit" 
@@ -563,7 +578,7 @@
 
    
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
index d79aaff6..5fb3ccfe 100644
--- a/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
+++ b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -132,7 +141,7 @@ in this fit.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -158,7 +167,7 @@ in this fit.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
index e0da5a8d..c1665dee 100644
--- a/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -131,7 +140,7 @@ in this fit.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -157,7 +166,7 @@ in this fit.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOCUS_2006_HS_ref_A_to_F.html b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
index 720073f2..db3d228d 100644
--- a/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -132,7 +141,7 @@ in this fit.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -158,7 +167,7 @@ in this fit.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
index b12abf8c..cc4fcb1d 100644
--- a/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -130,7 +139,7 @@ in this fit.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -156,7 +165,7 @@ in this fit.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOCUS_2006_datasets.html b/docs/reference/FOCUS_2006_datasets.html
index 65bc572a..4548c983 100644
--- a/docs/reference/FOCUS_2006_datasets.html
+++ b/docs/reference/FOCUS_2006_datasets.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +76,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +93,7 @@
       
       
       
     
   
@@ -123,7 +128,7 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -158,7 +163,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/FOMC.solution-1.png b/docs/reference/FOMC.solution-1.png
new file mode 100644
index 00000000..58178df5
Binary files /dev/null and b/docs/reference/FOMC.solution-1.png differ
diff --git a/docs/reference/FOMC.solution-2.png b/docs/reference/FOMC.solution-2.png
deleted file mode 100644
index a673bc0e..00000000
Binary files a/docs/reference/FOMC.solution-2.png and /dev/null differ
diff --git a/docs/reference/FOMC.solution.html b/docs/reference/FOMC.solution.html
index 9af30b7a..810b0eba 100644
--- a/docs/reference/FOMC.solution.html
+++ b/docs/reference/FOMC.solution.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
-
+  
+  
+
+
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -152,14 +161,14 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
 
    Gustafson DI and Holden LR (1990) Nonlinear pesticide dissipation in soil: A
   new model based on spatial variability. Environmental Science and 
   Technology 24, 1032-1038
    
     
 
     
    Examples
    
-    
      plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
    
+    
      plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/HS.solution-1.png b/docs/reference/HS.solution-1.png
new file mode 100644
index 00000000..e259134e
Binary files /dev/null and b/docs/reference/HS.solution-1.png differ
diff --git a/docs/reference/HS.solution-2.png b/docs/reference/HS.solution-2.png
deleted file mode 100644
index 2e516447..00000000
Binary files a/docs/reference/HS.solution-2.png and /dev/null differ
diff --git a/docs/reference/HS.solution.html b/docs/reference/HS.solution.html
index 8f6bbbe2..79358efb 100644
--- a/docs/reference/HS.solution.html
+++ b/docs/reference/HS.solution.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +77,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +94,7 @@
       
       
       
     
   
@@ -147,11 +153,11 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
-    
      plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
    
+    
      plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/IORE.solution-1.png b/docs/reference/IORE.solution-1.png
new file mode 100644
index 00000000..674c25d3
Binary files /dev/null and b/docs/reference/IORE.solution-1.png differ
diff --git a/docs/reference/IORE.solution-2.png b/docs/reference/IORE.solution-2.png
deleted file mode 100644
index a83d49c7..00000000
Binary files a/docs/reference/IORE.solution-2.png and /dev/null differ
diff --git a/docs/reference/IORE.solution.html b/docs/reference/IORE.solution.html
index 45e090c0..f705ab2f 100644
--- a/docs/reference/IORE.solution.html
+++ b/docs/reference/IORE.solution.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +94,7 @@
       
       
       
     
   
@@ -154,7 +157,7 @@
 
     
    Examples
    
     
      plot(function(x) IORE.solution(x, 100, 0.2, 1.3), 0, 2,
-                                       ylim = c(0, 100))
      fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+                                       ylim = c(0, 100))
      fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
   fit.iore <- mkinfit("IORE", FOCUS_2006_C, quiet = TRUE)
   fit.iore.deS <- mkinfit("IORE", FOCUS_2006_C, solution_type = "deSolve", quiet = TRUE)
 
@@ -191,7 +194,7 @@
 
    
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/SFO.solution-2.png b/docs/reference/SFO.solution-2.png
deleted file mode 100644
index 9626091f..00000000
Binary files a/docs/reference/SFO.solution-2.png and /dev/null differ
diff --git a/docs/reference/SFO.solution.html b/docs/reference/SFO.solution.html
index ef9b8eb7..a7934a35 100644
--- a/docs/reference/SFO.solution.html
+++ b/docs/reference/SFO.solution.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +76,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +93,7 @@
       
       
       
     
   
@@ -136,11 +141,13 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
-    
      plot(function(x) SFO.solution(x, 100, 3), 0, 2)
    
+    
      
    # NOT RUN {
+plot(function(x) SFO.solution(x, 100, 3), 0, 2)
+# }
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/SFORB.solution-2.png b/docs/reference/SFORB.solution-2.png
deleted file mode 100644
index 63a50bf9..00000000
Binary files a/docs/reference/SFORB.solution-2.png and /dev/null differ
diff --git a/docs/reference/SFORB.solution.html b/docs/reference/SFORB.solution.html
index ebe67733..aaae7cdd 100644
--- a/docs/reference/SFORB.solution.html
+++ b/docs/reference/SFORB.solution.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +80,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +97,7 @@
       
       
       
     
   
@@ -149,11 +158,13 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
-    
      plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
    
+    
      
    # NOT RUN {
+plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
+# }
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/add_err-1.png b/docs/reference/add_err-1.png
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diff --git a/docs/reference/add_err.html b/docs/reference/add_err.html
index d56a8728..42bec993 100644
--- a/docs/reference/add_err.html
+++ b/docs/reference/add_err.html
@@ -18,12 +18,21 @@
 
 
 
+
+
 
 
 
 
 
-
+  
+  
+
+
+
+
 
 
 
@@ -195,14 +204,14 @@
                    d_SFO_SFO_err, cores = 1,
                    quiet = TRUE, method.modFit = "Marq")
 
-plot(f_SFO_SFO)
    
+plot(f_SFO_SFO)
    
 # We would like to inspect the fit for dataset 3 more closely
 # Using double brackets makes the returned object an mkinfit object
 # instead of a list of mkinfit objects, so plot.mkinfit is used
-plot(f_SFO_SFO[[3]], show_residuals = TRUE)
    
+plot(f_SFO_SFO[[3]], show_residuals = TRUE)
    
 # If we use single brackets, we should give two indices (model and dataset),
 # and plot.mmkin is used
-plot(f_SFO_SFO[1, 3])
    
+plot(f_SFO_SFO[1, 3])
    
 
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/endpoints.html b/docs/reference/endpoints.html
index ed235a47..c45a0b7c 100644
--- a/docs/reference/endpoints.html
+++ b/docs/reference/endpoints.html
@@ -18,12 +18,22 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +96,7 @@
       
       
       
     
   
@@ -171,7 +176,7 @@ with the advantage that the SFORB model can also be used for metabolites.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/geometric_mean.html b/docs/reference/geometric_mean.html
index 4af50f48..2d46b4de 100644
--- a/docs/reference/geometric_mean.html
+++ b/docs/reference/geometric_mean.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +93,7 @@
       
       
       
     
   
@@ -152,7 +154,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/ilr.html b/docs/reference/ilr.html
index 6c3979c5..2c51001f 100644
--- a/docs/reference/ilr.html
+++ b/docs/reference/ilr.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +93,7 @@
       
       
       
     
   
@@ -176,7 +178,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 4675748c..218194ad 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -18,12 +18,16 @@
 
 
 
+
+
 
 
 
 
 
-
+  
+  
+
 
 
 
@@ -442,7 +446,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/max_twa_parent.html b/docs/reference/max_twa_parent.html
index 0e99e579..5d6baf6a 100644
--- a/docs/reference/max_twa_parent.html
+++ b/docs/reference/max_twa_parent.html
@@ -18,12 +18,23 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +97,7 @@
       
       
       
     
   
@@ -139,7 +145,7 @@ guidance.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -172,7 +178,7 @@ guidance.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mccall81_245T.html b/docs/reference/mccall81_245T.html
index 0111deb3..ec7f8ccd 100644
--- a/docs/reference/mccall81_245T.html
+++ b/docs/reference/mccall81_245T.html
@@ -18,12 +18,21 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +78,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +95,7 @@
       
       
       
     
   
@@ -127,108 +134,25 @@
     
    Source
    
 
     
    McCall P, Vrona SA, Kelley SS (1981) Fate of uniformly carbon-14 ring labeled 2,4,5-Trichlorophenoxyacetic acid and 2,4-dichlorophenoxyacetic acid. J Agric Chem 29, 100-107
-  http://dx.doi.org/10.1021/jf00103a026
    
+  http://dx.doi.org/10.1021/jf00103a026
    
     
 
     
    Examples
    
     
      SFO_SFO_SFO <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
                          phenol = list(type = "SFO", to = "anisole"),
-                         anisole = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+                         anisole = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
      
    # NOT RUN {
     fit.1 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
-    summary(fit.1, data = FALSE)
    #> mkin version:    0.9.46 
-#> R version:       3.4.1 
-#> Date of fit:     Sat Jul 29 15:14:14 2017 
-#> Date of summary: Sat Jul 29 15:14:14 2017 
-#> 
-#> Equations:
-#> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
-#> d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol -
-#>            k_phenol_anisole * phenol
-#> d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 612 model solutions performed in 3.558 s
-#> 
-#> Weighting: none
-#> 
-#> Starting values for parameters to be optimised:
-#>                     value   type
-#> T245_0           100.9000  state
-#> k_T245_sink        0.1000 deparm
-#> k_T245_phenol      0.1001 deparm
-#> k_phenol_sink      0.1002 deparm
-#> k_phenol_anisole   0.1003 deparm
-#> k_anisole_sink     0.1004 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                           value lower upper
-#> T245_0               100.900000  -Inf   Inf
-#> log_k_T245_sink       -2.302585  -Inf   Inf
-#> log_k_T245_phenol     -2.301586  -Inf   Inf
-#> log_k_phenol_sink     -2.300587  -Inf   Inf
-#> log_k_phenol_anisole  -2.299590  -Inf   Inf
-#> log_k_anisole_sink    -2.298593  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>           value  type
-#> phenol_0      0 state
-#> anisole_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                      Estimate Std. Error Lower Upper
-#> T245_0               103.9000         NA    NA    NA
-#> log_k_T245_sink       -4.1130         NA    NA    NA
-#> log_k_T245_phenol     -3.6120         NA    NA    NA
-#> log_k_phenol_sink    -26.8400         NA    NA    NA
-#> log_k_phenol_anisole  -0.9037         NA    NA    NA
-#> log_k_anisole_sink    -5.0090         NA    NA    NA
-#> 
-#> Parameter correlation:
    #> Warning: Could not estimate covariance matrix; singular system:
    #> Could not estimate covariance matrix; singular system:
-#> 
-#> Residual standard error: 2.78 on 18 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                   Estimate   t value    Pr(>t) Lower Upper
-#> T245_0           1.039e+02 4.282e+01 7.236e-20    NA    NA
-#> k_T245_sink      1.636e-02 8.901e-01 1.926e-01    NA    NA
-#> k_T245_phenol    2.701e-02 1.504e+00 7.499e-02    NA    NA
-#> k_phenol_sink    2.212e-12 7.870e-12 5.000e-01    NA    NA
-#> k_phenol_anisole 4.051e-01 2.518e+00 1.075e-02    NA    NA
-#> k_anisole_sink   6.679e-03 8.146e+00 9.469e-08    NA    NA
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data  10.070       6 16
-#> T245       7.908       3  5
-#> phenol   106.445       2  5
-#> anisole    5.379       1  6
-#> 
-#> Resulting formation fractions:
-#>                       ff
-#> T245_sink      3.772e-01
-#> T245_phenol    6.228e-01
-#> phenol_sink    5.462e-12
-#> phenol_anisole 1.000e+00
-#> anisole_sink   1.000e+00
-#> 
-#> Estimated disappearance times:
-#>            DT50    DT90
-#> T245     15.982  53.091
-#> phenol    1.711   5.685
-#> anisole 103.784 344.763
    
-  # No convergence, no covariance matrix ...
+    summary(fit.1, data = FALSE)
+
+# }
      # No convergence, no covariance matrix ...
   # k_phenol_sink is really small, therefore fix it to zero
   fit.2 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"),
                  parms.ini = c(k_phenol_sink = 0),
                  fixed_parms = "k_phenol_sink", quiet = TRUE)
-  summary(fit.2, data = FALSE)
    #> mkin version:    0.9.46 
-#> R version:       3.4.1 
-#> Date of fit:     Sat Jul 29 15:14:15 2017 
-#> Date of summary: Sat Jul 29 15:14:15 2017 
+  summary(fit.2, data = FALSE)
    #> mkin version used for fitting:    0.9.47.1 
+#> R version used for fitting:       3.4.3 
+#> Date of fit:     Thu Mar  1 14:26:15 2018 
+#> Date of summary: Thu Mar  1 14:26:15 2018 
 #> 
 #> Equations:
 #> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
@@ -238,7 +162,7 @@
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted with method Port using 246 model solutions performed in 1.431 s
+#> Fitted with method Port using 246 model solutions performed in 1.359 s
 #> 
 #> Weighting: none
 #> 
@@ -340,7 +264,7 @@
 
    
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkin_long_to_wide.html b/docs/reference/mkin_long_to_wide.html
index 042bdced..a5432dac 100644
--- a/docs/reference/mkin_long_to_wide.html
+++ b/docs/reference/mkin_long_to_wide.html
@@ -18,12 +18,21 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +95,7 @@
       
       
       
     
    
   
@@ -186,7 +190,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkin_wide_to_long.html b/docs/reference/mkin_wide_to_long.html
index ddf28dd9..6798efa6 100644
--- a/docs/reference/mkin_wide_to_long.html
+++ b/docs/reference/mkin_wide_to_long.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +94,7 @@
       
       
       
     
   
@@ -165,7 +168,7 @@
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkinds.html b/docs/reference/mkinds.html
index 2d8d64a5..ab06e903 100644
--- a/docs/reference/mkinds.html
+++ b/docs/reference/mkinds.html
@@ -18,12 +18,19 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +93,7 @@
       
       
       
     
   
@@ -154,7 +156,7 @@ in order to be compatible with mkinfit
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkinerrmin.html b/docs/reference/mkinerrmin.html
index 67b7a35e..496cce15 100644
--- a/docs/reference/mkinerrmin.html
+++ b/docs/reference/mkinerrmin.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +77,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +94,7 @@
       
       
       
     
   
@@ -146,7 +152,7 @@ chi-squared test as defined in the FOCUS kinetics report from 2006.
    
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
     
 
     
    Examples
    
@@ -186,7 +192,7 @@ chi-squared test as defined in the FOCUS kinetics report from 2006.
    
 
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html
index 0102aecb..4fb5ef9a 100644
--- a/docs/reference/mkinfit.html
+++ b/docs/reference/mkinfit.html
@@ -18,12 +18,29 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -395,17 +412,17 @@
     
    Examples
    
     
    # Use shorthand notation for parent only degradation
 fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-summary(fit)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:05:48 2018 
-#> Date of summary: Tue Jan 30 10:05:48 2018 
+summary(fit)
    #> mkin version used for fitting:    0.9.47.1 
+#> R version used for fitting:       3.4.3 
+#> Date of fit:     Thu Mar  1 14:26:18 2018 
+#> Date of summary: Thu Mar  1 14:26:18 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted with method Port using 64 model solutions performed in 0.31 s
+#> Fitted with method Port using 64 model solutions performed in 0.135 s
 #> 
 #> Weighting: none
 #> 
@@ -474,7 +491,7 @@
   m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults
 print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
                            solution_type = "eigen", quiet = TRUE)))
    #>    user  system elapsed 
-#>   1.196   0.000   1.195 
    coef(fit)
    #>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
+#>    0.84    0.00    0.84 
    coef(fit)
    #>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
 #>          99.59848          -3.03822          -2.98030          -5.24750 
    endpoints(fit)
    #> $ff
 #> parent_sink   parent_m1     m1_sink 
 #>    0.485524    0.514476    1.000000 
@@ -486,92 +503,19 @@
 #>              DT50      DT90
 #> parent   7.022929  23.32967
 #> m1     131.760712 437.69961
-#> 
    
+#> 
    # NOT RUN {
 # deSolve is slower when no C compiler (gcc) was available during model generation
 print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D,
-                           solution_type = "deSolve")))
    #> Model cost at call  1 :  18915.53 
-#> Model cost at call  2 :  18915.53 
-#> Model cost at call  6 :  11424.02 
-#> Model cost at call  10 :  11424 
-#> Model cost at call  12 :  4094.396 
-#> Model cost at call  16 :  4094.396 
-#> Model cost at call  19 :  1340.595 
-#> Model cost at call  20 :  1340.593 
-#> Model cost at call  25 :  1072.239 
-#> Model cost at call  28 :  1072.236 
-#> Model cost at call  30 :  874.2614 
-#> Model cost at call  33 :  874.2611 
-#> Model cost at call  35 :  616.2379 
-#> Model cost at call  37 :  616.2374 
-#> Model cost at call  40 :  467.4387 
-#> Model cost at call  42 :  467.4382 
-#> Model cost at call  46 :  398.2913 
-#> Model cost at call  48 :  398.2912 
-#> Model cost at call  49 :  398.2911 
-#> Model cost at call  51 :  395.0711 
-#> Model cost at call  54 :  395.071 
-#> Model cost at call  56 :  378.3298 
-#> Model cost at call  59 :  378.3298 
-#> Model cost at call  62 :  376.9812 
-#> Model cost at call  64 :  376.9811 
-#> Model cost at call  67 :  375.2085 
-#> Model cost at call  69 :  375.2085 
-#> Model cost at call  70 :  375.2085 
-#> Model cost at call  71 :  375.2085 
-#> Model cost at call  72 :  374.5723 
-#> Model cost at call  74 :  374.5723 
-#> Model cost at call  77 :  374.0075 
-#> Model cost at call  79 :  374.0075 
-#> Model cost at call  80 :  374.0075 
-#> Model cost at call  82 :  373.1711 
-#> Model cost at call  84 :  373.1711 
-#> Model cost at call  87 :  372.6445 
-#> Model cost at call  88 :  372.1614 
-#> Model cost at call  90 :  372.1614 
-#> Model cost at call  91 :  372.1614 
-#> Model cost at call  94 :  371.6464 
-#> Model cost at call  99 :  371.4299 
-#> Model cost at call  101 :  371.4299 
-#> Model cost at call  104 :  371.4071 
-#> Model cost at call  106 :  371.4071 
-#> Model cost at call  107 :  371.4071 
-#> Model cost at call  109 :  371.2524 
-#> Model cost at call  113 :  371.2524 
-#> Model cost at call  114 :  371.2136 
-#> Model cost at call  115 :  371.2136 
-#> Model cost at call  116 :  371.2136 
-#> Model cost at call  119 :  371.2134 
-#> Model cost at call  120 :  371.2134 
-#> Model cost at call  122 :  371.2134 
-#> Model cost at call  123 :  371.2134 
-#> Model cost at call  125 :  371.2134 
-#> Model cost at call  126 :  371.2134 
-#> Model cost at call  135 :  371.2134 
-#> Model cost at call  147 :  371.2134 
-#> Model cost at call  151 :  371.2134 
-#> Model cost at call  152 :  371.2134 
-#> Model cost at call  153 :  371.2134 
-#> Optimisation by method Port successfully terminated.
-#>    user  system elapsed 
-#>   1.008   0.000   1.006 
    coef(fit.deSolve)
    #>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
-#>          99.59848          -3.03822          -2.98030          -5.24750 
    endpoints(fit.deSolve)
    #> $ff
-#> parent_sink   parent_m1     m1_sink 
-#>    0.485524    0.514476    1.000000 
-#> 
-#> $SFORB
-#> logical(0)
-#> 
-#> $distimes
-#>              DT50      DT90
-#> parent   7.022929  23.32967
-#> m1     131.760712 437.69961
-#> 
    
-
-# Use stepwise fitting, using optimised parameters from parent only fit, FOMC
-
+                           solution_type = "deSolve")))
+coef(fit.deSolve)
+endpoints(fit.deSolve)
+# }
    
+# Use stepwise fitting, using optimised parameters from parent only fit, FOMC
+
    # NOT RUN {
 FOMC_SFO <- mkinmod(
   parent = mkinsub("FOMC", "m1"),
-  m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults
+  m1 = mkinsub("SFO"))
+# Fit the model to the FOCUS example dataset D using defaults
 fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE)
 # Use starting parameters from parent only FOMC fit
 fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, quiet = TRUE)
@@ -581,739 +525,40 @@
 # Use stepwise fitting, using optimised parameters from parent only fit, SFORB
 SFORB_SFO <- mkinmod(
   parent = list(type = "SFORB", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults
+  m1 = list(type = "SFO"))
+# Fit the model to the FOCUS example dataset D using defaults
 fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, quiet = TRUE)
 fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve",
                                  quiet = TRUE)
 # Use starting parameters from parent only SFORB fit (not really needed in this case)
 fit.SFORB = mkinfit("SFORB", FOCUS_2006_D, quiet = TRUE)
 fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode, quiet = TRUE)
-
-
-
+# }
    
+
    # NOT RUN {
 # Weighted fits, including IRLS
 SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"),
-                      m1 = mkinsub("SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
-summary(f.noweight)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:00 2018 
-#> Date of summary: Tue Jan 30 10:06:00 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 185 model solutions performed in 0.739 s
-#> 
-#> Weighting: none
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error   Lower    Upper
-#> parent_0       99.60000    1.61400 96.3300 102.9000
-#> log_k_parent   -2.31600    0.04187 -2.4010  -2.2310
-#> log_k_m1       -5.24800    0.13610 -5.5230  -4.9720
-#> f_parent_ilr_1  0.04096    0.06477 -0.0904   0.1723
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5178  -0.1701        -0.5489
-#> log_k_parent     0.5178       1.0000  -0.3285        -0.5451
-#> log_k_m1        -0.1701      -0.3285   1.0000         0.7466
-#> f_parent_ilr_1  -0.5489      -0.5451   0.7466         1.0000
-#> 
-#> Residual standard error: 3.211 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.600000  61.720 2.024e-38 96.330000 1.029e+02
-#> k_parent        0.098700  23.880 5.701e-24  0.090660 1.074e-01
-#> k_m1            0.005261   7.349 5.758e-09  0.003992 6.933e-03
-#> f_parent_to_m1  0.514500  22.490 4.374e-23  0.468100 5.606e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.398       4 15
-#> parent     6.459       2  7
-#> m1         4.690       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5145
-#> parent_sink 0.4855
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   7.023  23.33
-#> m1     131.761 437.70
-#> 
-#> Data:
-#>  time variable observed predicted   residual
-#>     0   parent    99.46  99.59848 -1.385e-01
-#>     0   parent   102.04  99.59848  2.442e+00
-#>     1   parent    93.50  90.23787  3.262e+00
-#>     1   parent    92.50  90.23787  2.262e+00
-#>     3   parent    63.23  74.07319 -1.084e+01
-#>     3   parent    68.99  74.07319 -5.083e+00
-#>     7   parent    52.32  49.91206  2.408e+00
-#>     7   parent    55.13  49.91206  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 -7.381e-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  36.44703  3.643e+00
-#>    75       m1    33.85  36.44703 -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
    f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs", quiet = TRUE)
-summary(f.irls)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:02 2018 
-#> Date of summary: Tue Jan 30 10:06:02 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 523 model solutions performed in 2.151 s
-#> 
-#> Weighting: none
-#> 
-#> Iterative reweighting with method obs 
-#> Final mean squared residuals of observed variables:
-#>    parent        m1 
-#> 11.573408  7.407845 
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower   Upper
-#> parent_0       99.67000    1.79200 96.04000 103.300
-#> log_k_parent   -2.31200    0.04560 -2.40400  -2.219
-#> log_k_m1       -5.25100    0.12510 -5.50500  -4.998
-#> f_parent_ilr_1  0.03785    0.06318 -0.09027   0.166
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5083  -0.1979        -0.6148
-#> log_k_parent     0.5083       1.0000  -0.3894        -0.6062
-#> log_k_m1        -0.1979      -0.3894   1.0000         0.7417
-#> f_parent_ilr_1  -0.6148      -0.6062   0.7417         1.0000
-#> 
-#> Residual standard error: 1.054 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.67000  55.630 8.184e-37 96.040000 1.033e+02
-#> k_parent        0.09906  21.930 1.016e-22  0.090310 1.087e-01
-#> k_m1            0.00524   7.996 8.486e-10  0.004066 6.753e-03
-#> f_parent_to_m1  0.51340  23.000 2.038e-23  0.468100 5.584e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.399       4 15
-#> parent     6.466       2  7
-#> m1         4.679       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5134
-#> parent_sink 0.4866
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.997  23.24
-#> m1     132.282 439.43
-#> 
-#> Data:
-#>  time variable observed predicted   residual   err
-#>     0   parent    99.46  99.67218 -2.122e-01 3.402
-#>     0   parent   102.04  99.67218  2.368e+00 3.402
-#>     1   parent    93.50  90.27153  3.228e+00 3.402
-#>     1   parent    92.50  90.27153  2.228e+00 3.402
-#>     3   parent    63.23  74.04648 -1.082e+01 3.402
-#>     3   parent    68.99  74.04648 -5.056e+00 3.402
-#>     7   parent    52.32  49.82092  2.499e+00 3.402
-#>     7   parent    55.13  49.82092  5.309e+00 3.402
-#>    14   parent    27.27  24.90287  2.367e+00 3.402
-#>    14   parent    26.64  24.90287  1.737e+00 3.402
-#>    21   parent    11.50  12.44764 -9.476e-01 3.402
-#>    21   parent    11.64  12.44764 -8.076e-01 3.402
-#>    35   parent     2.85   3.11002 -2.600e-01 3.402
-#>    35   parent     2.91   3.11002 -2.000e-01 3.402
-#>    50   parent     0.69   0.70374 -1.374e-02 3.402
-#>    50   parent     0.63   0.70374 -7.374e-02 3.402
-#>    75   parent     0.05   0.05913 -9.134e-03 3.402
-#>    75   parent     0.06   0.05913  8.662e-04 3.402
-#>     0       m1     0.00   0.00000  0.000e+00 2.722
-#>     0       m1     0.00   0.00000  0.000e+00 2.722
-#>     1       m1     4.84   4.81328  2.672e-02 2.722
-#>     1       m1     5.64   4.81328  8.267e-01 2.722
-#>     3       m1    12.91  13.04779 -1.378e-01 2.722
-#>     3       m1    12.96  13.04779 -8.779e-02 2.722
-#>     7       m1    22.97  25.07615 -2.106e+00 2.722
-#>     7       m1    24.47  25.07615 -6.062e-01 2.722
-#>    14       m1    41.69  36.70729  4.983e+00 2.722
-#>    14       m1    33.21  36.70729 -3.497e+00 2.722
-#>    21       m1    44.37  41.65050  2.720e+00 2.722
-#>    21       m1    46.44  41.65050  4.790e+00 2.722
-#>    35       m1    41.22  43.28866 -2.069e+00 2.722
-#>    35       m1    37.95  43.28866 -5.339e+00 2.722
-#>    50       m1    41.19  41.19338 -3.383e-03 2.722
-#>    50       m1    40.01  41.19338 -1.183e+00 2.722
-#>    75       m1    40.09  36.43820  3.652e+00 2.722
-#>    75       m1    33.85  36.43820 -2.588e+00 2.722
-#>   100       m1    31.04  31.98971 -9.497e-01 2.722
-#>   100       m1    33.13  31.98971  1.140e+00 2.722
-#>   120       m1    25.15  28.80897 -3.659e+00 2.722
-#>   120       m1    33.31  28.80897  4.501e+00 2.722
    f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", quiet = TRUE)
-summary(f.w.mean)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:03 2018 
-#> Date of summary: Tue Jan 30 10:06:03 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 155 model solutions performed in 0.675 s
-#> 
-#> Weighting: mean
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower    Upper
-#> parent_0        99.7300    1.93200 95.81000 103.6000
-#> log_k_parent    -2.3090    0.04837 -2.40700  -2.2110
-#> log_k_m1        -5.2550    0.12070 -5.49900  -5.0100
-#> f_parent_ilr_1   0.0354    0.06344 -0.09327   0.1641
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5004  -0.2143        -0.6514
-#> log_k_parent     0.5004       1.0000  -0.4282        -0.6383
-#> log_k_m1        -0.2143      -0.4282   1.0000         0.7390
-#> f_parent_ilr_1  -0.6514      -0.6383   0.7390         1.0000
-#> 
-#> Residual standard error: 0.09829 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)    Lower     Upper
-#> parent_0       99.730000  51.630 1.166e-35 95.81000 1.036e+02
-#> k_parent        0.099360  20.670 7.303e-22  0.09007 1.096e-01
-#> k_m1            0.005224   8.287 3.649e-10  0.00409 6.672e-03
-#> f_parent_to_m1  0.512500  22.860 2.497e-23  0.46710 5.578e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.401       4 15
-#> parent     6.473       2  7
-#> m1         4.671       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5125
-#> parent_sink 0.4875
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.976  23.18
-#> m1     132.696 440.81
-#> 
-#> Data:
-#>  time variable observed predicted   residual
-#>     0   parent    99.46  99.73057  -0.270570
-#>     0   parent   102.04  99.73057   2.309430
-#>     1   parent    93.50  90.29805   3.201945
-#>     1   parent    92.50  90.29805   2.201945
-#>     3   parent    63.23  74.02503 -10.795028
-#>     3   parent    68.99  74.02503  -5.035028
-#>     7   parent    52.32  49.74838   2.571618
-#>     7   parent    55.13  49.74838   5.381618
-#>    14   parent    27.27  24.81588   2.454124
-#>    14   parent    26.64  24.81588   1.824124
-#>    21   parent    11.50  12.37885  -0.878849
-#>    21   parent    11.64  12.37885  -0.738849
-#>    35   parent     2.85   3.08022  -0.230219
-#>    35   parent     2.91   3.08022  -0.170219
-#>    50   parent     0.69   0.69396  -0.003958
-#>    50   parent     0.63   0.69396  -0.063958
-#>    75   parent     0.05   0.05789  -0.007888
-#>    75   parent     0.06   0.05789   0.002112
-#>     0       m1     0.00   0.00000   0.000000
-#>     0       m1     0.00   0.00000   0.000000
-#>     1       m1     4.84   4.82149   0.018512
-#>     1       m1     5.64   4.82149   0.818512
-#>     3       m1    12.91  13.06669  -0.156692
-#>     3       m1    12.96  13.06669  -0.106692
-#>     7       m1    22.97  25.10106  -2.131058
-#>     7       m1    24.47  25.10106  -0.631058
-#>    14       m1    41.69  36.72092   4.969077
-#>    14       m1    33.21  36.72092  -3.510923
-#>    21       m1    44.37  41.64835   2.721647
-#>    21       m1    46.44  41.64835   4.791647
-#>    35       m1    41.22  43.26923  -2.049225
-#>    35       m1    37.95  43.26923  -5.319225
-#>    50       m1    41.19  41.17364   0.016361
-#>    50       m1    40.01  41.17364  -1.163639
-#>    75       m1    40.09  36.43122   3.658776
-#>    75       m1    33.85  36.43122  -2.581224
-#>   100       m1    31.04  31.99612  -0.956124
-#>   100       m1    33.13  31.99612   1.133876
-#>   120       m1    25.15  28.82413  -3.674128
-#>   120       m1    33.31  28.82413   4.485872
    f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value",
+                      m1 = mkinsub("SFO"), use_of_ff = "max")
+f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+summary(f.noweight)
+f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs", quiet = TRUE)
+summary(f.irls)
+f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", quiet = TRUE)
+summary(f.w.mean)
+f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value",
                      quiet = TRUE)
-summary(f.w.value)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:04 2018 
-#> Date of summary: Tue Jan 30 10:06:04 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 174 model solutions performed in 0.68 s
-#> 
-#> Weighting: manual
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower    Upper
-#> parent_0        99.6600   2.712000 94.14000 105.2000
-#> log_k_parent    -2.2980   0.008118 -2.31500  -2.2820
-#> log_k_m1        -5.2410   0.096690 -5.43800  -5.0450
-#> f_parent_ilr_1   0.0231   0.057990 -0.09474   0.1409
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0        1.00000       0.6844 -0.08687        -0.7564
-#> log_k_parent    0.68435       1.0000 -0.12694        -0.5812
-#> log_k_m1       -0.08687      -0.1269  1.00000         0.5195
-#> f_parent_ilr_1 -0.75644      -0.5812  0.51951         1.0000
-#> 
-#> Residual standard error: 0.08396 on 34 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)    Lower     Upper
-#> parent_0       99.660000   36.75 2.957e-29 94.14000 1.052e+02
-#> k_parent        0.100400  123.20 5.927e-47  0.09878 1.021e-01
-#> k_m1            0.005295   10.34 2.447e-12  0.00435 6.444e-03
-#> f_parent_to_m1  0.508200   24.79 1.184e-23  0.46660 5.497e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.461       4 15
-#> parent     6.520       2  7
-#> m1         4.744       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5082
-#> parent_sink 0.4918
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.902  22.93
-#> m1     130.916 434.89
-#> 
-#> Data:
-#>  time variable observed predicted   residual    err
-#>     0   parent    99.46  99.65571  -0.195714  99.46
-#>     0   parent   102.04  99.65571   2.384286 102.04
-#>     1   parent    93.50  90.13383   3.366170  93.50
-#>     1   parent    92.50  90.13383   2.366170  92.50
-#>     3   parent    63.23  73.73252 -10.502518  63.23
-#>     3   parent    68.99  73.73252  -4.742518  68.99
-#>     7   parent    52.32  49.34027   2.979728  52.32
-#>     7   parent    55.13  49.34027   5.789728  55.13
-#>    14   parent    27.27  24.42873   2.841271  27.27
-#>    14   parent    26.64  24.42873   2.211271  26.64
-#>    21   parent    11.50  12.09484  -0.594842  11.50
-#>    21   parent    11.64  12.09484  -0.454842  11.64
-#>    35   parent     2.85   2.96482  -0.114824   2.85
-#>    35   parent     2.91   2.96482  -0.054824   2.91
-#>    50   parent     0.69   0.65733   0.032670   0.69
-#>    50   parent     0.63   0.65733  -0.027330   0.63
-#>    75   parent     0.05   0.05339  -0.003386   0.05
-#>    75   parent     0.06   0.05339   0.006614   0.06
-#>     1       m1     4.84   4.82570   0.014301   4.84
-#>     1       m1     5.64   4.82570   0.814301   5.64
-#>     3       m1    12.91  13.06402  -0.154020  12.91
-#>     3       m1    12.96  13.06402  -0.104020  12.96
-#>     7       m1    22.97  25.04656  -2.076564  22.97
-#>     7       m1    24.47  25.04656  -0.576564  24.47
-#>    14       m1    41.69  36.53601   5.153988  41.69
-#>    14       m1    33.21  36.53601  -3.326012  33.21
-#>    21       m1    44.37  41.34639   3.023609  44.37
-#>    21       m1    46.44  41.34639   5.093609  46.44
-#>    35       m1    41.22  42.82669  -1.606690  41.22
-#>    35       m1    37.95  42.82669  -4.876690  37.95
-#>    50       m1    41.19  40.67342   0.516578  41.19
-#>    50       m1    40.01  40.67342  -0.663422  40.01
-#>    75       m1    40.09  35.91105   4.178947  40.09
-#>    75       m1    33.85  35.91105  -2.061053  33.85
-#>   100       m1    31.04  31.48161  -0.441612  31.04
-#>   100       m1    33.13  31.48161   1.648388  33.13
-#>   120       m1    25.15  28.32018  -3.170181  25.15
-#>   120       m1    33.31  28.32018   4.989819  33.31
    
-
-
+summary(f.w.value)
+# }
    
+
    # NOT RUN {
 # Manual weighting
 dw <- FOCUS_2006_D
 errors <- c(parent = 2, m1 = 1)
 dw$err.man <- errors[FOCUS_2006_D$name]
 f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE)
-summary(f.w.man)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:05 2018 
-#> Date of summary: Tue Jan 30 10:06:05 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 297 model solutions performed in 1.178 s
-#> 
-#> Weighting: manual
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error   Lower    Upper
-#> parent_0       99.49000    1.33200 96.7800 102.2000
-#> log_k_parent   -2.32100    0.03550 -2.3930  -2.2490
-#> log_k_m1       -5.24100    0.21280 -5.6730  -4.8100
-#> f_parent_ilr_1  0.04571    0.08966 -0.1361   0.2275
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0        1.00000       0.5312 -0.09456        -0.3351
-#> log_k_parent    0.53123       1.0000 -0.17800        -0.3360
-#> log_k_m1       -0.09456      -0.1780  1.00000         0.7616
-#> f_parent_ilr_1 -0.33514      -0.3360  0.76156         1.0000
-#> 
-#> Residual standard error: 2.628 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.490000   74.69 2.221e-41 96.780000 1.022e+02
-#> k_parent        0.098140   28.17 2.012e-26  0.091320 1.055e-01
-#> k_m1            0.005292    4.70 1.873e-05  0.003437 8.148e-03
-#> f_parent_to_m1  0.516200   16.30 1.686e-18  0.452000 5.798e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.400       4 15
-#> parent     6.454       2  7
-#> m1         4.708       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5162
-#> parent_sink 0.4838
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   7.063  23.46
-#> m1     130.971 435.08
-#> 
-#> Data:
-#>  time variable observed predicted   residual err
-#>     0   parent    99.46  99.48598  -0.025976   1
-#>     0   parent   102.04  99.48598   2.554024   1
-#>     1   parent    93.50  90.18612   3.313883   1
-#>     1   parent    92.50  90.18612   2.313883   1
-#>     3   parent    63.23  74.11316 -10.883162   1
-#>     3   parent    68.99  74.11316  -5.123162   1
-#>     7   parent    52.32  50.05029   2.269705   1
-#>     7   parent    55.13  50.05029   5.079705   1
-#>    14   parent    27.27  25.17975   2.090250   1
-#>    14   parent    26.64  25.17975   1.460250   1
-#>    21   parent    11.50  12.66765  -1.167654   1
-#>    21   parent    11.64  12.66765  -1.027654   1
-#>    35   parent     2.85   3.20616  -0.356164   1
-#>    35   parent     2.91   3.20616  -0.296164   1
-#>    50   parent     0.69   0.73562  -0.045619   1
-#>    50   parent     0.63   0.73562  -0.105619   1
-#>    75   parent     0.05   0.06326  -0.013256   1
-#>    75   parent     0.06   0.06326  -0.003256   1
-#>     0       m1     0.00   0.00000   0.000000   2
-#>     0       m1     0.00   0.00000   0.000000   2
-#>     1       m1     4.84   4.78729   0.052713   2
-#>     1       m1     5.64   4.78729   0.852713   2
-#>     3       m1    12.91  12.98785  -0.077848   2
-#>     3       m1    12.96  12.98785  -0.027848   2
-#>     7       m1    22.97  24.99695  -2.026945   2
-#>     7       m1    24.47  24.99695  -0.526945   2
-#>    14       m1    41.69  36.66353   5.026473   2
-#>    14       m1    33.21  36.66353  -3.453527   2
-#>    21       m1    44.37  41.65681   2.713187   2
-#>    21       m1    46.44  41.65681   4.783187   2
-#>    35       m1    41.22  43.35031  -2.130312   2
-#>    35       m1    37.95  43.35031  -5.400312   2
-#>    50       m1    41.19  41.25637  -0.066365   2
-#>    50       m1    40.01  41.25637  -1.246365   2
-#>    75       m1    40.09  36.46057   3.629433   2
-#>    75       m1    33.85  36.46057  -2.610567   2
-#>   100       m1    31.04  31.96929  -0.929288   2
-#>   100       m1    33.13  31.96929   1.160712   2
-#>   120       m1    25.15  28.76062  -3.610616   2
-#>   120       m1    33.31  28.76062   4.549384   2
    f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE,
+summary(f.w.man)
+f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE,
                        reweight.method = "obs")
-summary(f.w.man.irls)
    #> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:08 2018 
-#> Date of summary: Tue Jan 30 10:06:08 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 692 model solutions performed in 2.733 s
-#> 
-#> Weighting: manual
-#> 
-#> Iterative reweighting with method obs 
-#> Final mean squared residuals of observed variables:
-#>    parent        m1 
-#> 11.573407  7.407845 
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower   Upper
-#> parent_0       99.67000    1.79200 96.04000 103.300
-#> log_k_parent   -2.31200    0.04560 -2.40400  -2.220
-#> log_k_m1       -5.25100    0.12510 -5.50500  -4.998
-#> f_parent_ilr_1  0.03785    0.06318 -0.09027   0.166
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5083  -0.1979        -0.6148
-#> log_k_parent     0.5083       1.0000  -0.3894        -0.6062
-#> log_k_m1        -0.1979      -0.3894   1.0000         0.7417
-#> f_parent_ilr_1  -0.6148      -0.6062   0.7417         1.0000
-#> 
-#> Residual standard error: 1.054 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.67000  55.630 8.184e-37 96.040000 1.033e+02
-#> k_parent        0.09906  21.930 1.016e-22  0.090310 1.087e-01
-#> k_m1            0.00524   7.996 8.486e-10  0.004066 6.753e-03
-#> f_parent_to_m1  0.51340  23.000 2.038e-23  0.468100 5.584e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.399       4 15
-#> parent     6.466       2  7
-#> m1         4.679       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5134
-#> parent_sink 0.4866
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.997  23.24
-#> m1     132.282 439.43
-#> 
-#> Data:
-#>  time variable observed predicted   residual err.ini   err
-#>     0   parent    99.46  99.67218 -2.122e-01       1 3.402
-#>     0   parent   102.04  99.67218  2.368e+00       1 3.402
-#>     1   parent    93.50  90.27153  3.228e+00       1 3.402
-#>     1   parent    92.50  90.27153  2.228e+00       1 3.402
-#>     3   parent    63.23  74.04648 -1.082e+01       1 3.402
-#>     3   parent    68.99  74.04648 -5.056e+00       1 3.402
-#>     7   parent    52.32  49.82092  2.499e+00       1 3.402
-#>     7   parent    55.13  49.82092  5.309e+00       1 3.402
-#>    14   parent    27.27  24.90288  2.367e+00       1 3.402
-#>    14   parent    26.64  24.90288  1.737e+00       1 3.402
-#>    21   parent    11.50  12.44765 -9.476e-01       1 3.402
-#>    21   parent    11.64  12.44765 -8.076e-01       1 3.402
-#>    35   parent     2.85   3.11002 -2.600e-01       1 3.402
-#>    35   parent     2.91   3.11002 -2.000e-01       1 3.402
-#>    50   parent     0.69   0.70375 -1.375e-02       1 3.402
-#>    50   parent     0.63   0.70375 -7.375e-02       1 3.402
-#>    75   parent     0.05   0.05913 -9.134e-03       1 3.402
-#>    75   parent     0.06   0.05913  8.662e-04       1 3.402
-#>     0       m1     0.00   0.00000  0.000e+00       2 2.722
-#>     0       m1     0.00   0.00000  0.000e+00       2 2.722
-#>     1       m1     4.84   4.81328  2.672e-02       2 2.722
-#>     1       m1     5.64   4.81328  8.267e-01       2 2.722
-#>     3       m1    12.91  13.04779 -1.378e-01       2 2.722
-#>     3       m1    12.96  13.04779 -8.779e-02       2 2.722
-#>     7       m1    22.97  25.07615 -2.106e+00       2 2.722
-#>     7       m1    24.47  25.07615 -6.062e-01       2 2.722
-#>    14       m1    41.69  36.70729  4.983e+00       2 2.722
-#>    14       m1    33.21  36.70729 -3.497e+00       2 2.722
-#>    21       m1    44.37  41.65050  2.720e+00       2 2.722
-#>    21       m1    46.44  41.65050  4.790e+00       2 2.722
-#>    35       m1    41.22  43.28866 -2.069e+00       2 2.722
-#>    35       m1    37.95  43.28866 -5.339e+00       2 2.722
-#>    50       m1    41.19  41.19339 -3.386e-03       2 2.722
-#>    50       m1    40.01  41.19339 -1.183e+00       2 2.722
-#>    75       m1    40.09  36.43820  3.652e+00       2 2.722
-#>    75       m1    33.85  36.43820 -2.588e+00       2 2.722
-#>   100       m1    31.04  31.98971 -9.497e-01       2 2.722
-#>   100       m1    33.13  31.98971  1.140e+00       2 2.722
-#>   120       m1    25.15  28.80897 -3.659e+00       2 2.722
-#>   120       m1    33.31  28.80897  4.501e+00       2 2.722
    
-
    
+summary(f.w.man.irls)
+# }
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html
index 5703b188..c1287905 100644
--- a/docs/reference/mkinmod.html
+++ b/docs/reference/mkinmod.html
@@ -18,12 +18,24 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -69,6 +81,9 @@
     
  • 
       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
     
    • 
@@ -83,12 +98,7 @@
       
       
       
     
   
@@ -182,7 +192,7 @@
   Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
   Registration” Report of the FOCUS Work Group on Degradation Kinetics,
   EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
+  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
    
 
    NAFTA Technical Working Group on Pesticides (not dated) Guidance for
   Evaluating and Calculating Degradation Kinetics in Environmental 
   Media
    
@@ -196,36 +206,17 @@
 SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
-
+
    # NOT RUN {
 # The above model used to be specified like this, before the advent of mkinsub()
 SFO_SFO <- mkinmod(
   parent = list(type = "SFO", to = "m1"),
-  m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+  m1 = list(type = "SFO"))
+
 # Show details of creating the C function
 SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"), verbose = TRUE)
    #> Compilation argument:
-#>  /usr/lib/R/bin/R CMD SHLIB file519167a14b3a.c 2> file519167a14b3a.c.err.txt 
-#> Program source:
-#>   1: #include <R.h>
-#>   2: 
-#>   3: 
-#>   4: static double parms [3];
-#>   5: #define k_parent_sink parms[0]
-#>   6: #define k_parent_m1 parms[1]
-#>   7: #define k_m1_sink parms[2]
-#>   8: 
-#>   9: void initpar(void (* odeparms)(int *, double *)) {
-#>  10:     int N = 3;
-#>  11:     odeparms(&N, parms);
-#>  12: }
-#>  13: 
-#>  14: 
-#>  15: void func ( int * n, double * t, double * y, double * f, double * rpar, int * ipar ) {
-#>  16: 
-#>  17: f[0] = - k_parent_sink * y[0] - k_parent_m1 * y[0];
-#>  18: f[1] = + k_parent_m1 * y[0] - k_m1_sink * y[1];
-#>  19: }
    #> Successfully compiled differential equation model from auto-generated C code.
    
+  m1 = mkinsub("SFO"), verbose = TRUE)
+
 # If we have several parallel metabolites 
 # (compare tests/testthat/test_synthetic_data_for_UBA_2014.R)
 m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
@@ -235,7 +226,8 @@
 
 fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par,
                           synthetic_data_for_UBA_2014[[12]]$data,
-                          quiet = TRUE)
    
+                          quiet = TRUE)
+# }
    
   
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/mkinparplot-1.png b/docs/reference/mkinparplot-1.png
new file mode 100644
index 00000000..42811535
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diff --git a/docs/reference/mkinparplot-4.png b/docs/reference/mkinparplot-4.png
deleted file mode 100644
index c9f4aadb..00000000
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diff --git a/docs/reference/mkinparplot.html b/docs/reference/mkinparplot.html
index 67ba6052..30954168 100644
--- a/docs/reference/mkinparplot.html
+++ b/docs/reference/mkinparplot.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -86,12 +94,7 @@
       
       
       
     
   
@@ -132,7 +135,7 @@
   T245 = mkinsub("SFO", to = c("phenol"), sink = FALSE),
   phenol = mkinsub("SFO", to = c("anisole")),
   anisole = mkinsub("SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
-mkinparplot(fit)
    
+mkinparplot(fit)
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/mkinplot.html b/docs/reference/mkinplot.html index 7c875ebe..5df3f872 100644 --- a/docs/reference/mkinplot.html +++ b/docs/reference/mkinplot.html @@ -18,12 +18,19 @@ + + + + + + + @@ -86,12 +93,7 @@ @@ -152,7 +154,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html index b3453e6c..df6316e1 100644 --- a/docs/reference/mkinpredict.html +++ b/docs/reference/mkinpredict.html @@ -18,12 +18,21 @@ + + + + + + + @@ -69,6 +78,9 @@
  • 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
    • @@ -83,12 +95,7 @@ @@ -299,17 +306,17 @@ c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "eigen")[201,]))
    #> time parent m1 #> 201 20 4.978707 27.46227
    #> user system elapsed -#> 0.004 0.000 0.003
    system.time( +#> 0.003 0.000 0.003
    system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve")[201,]))
    #> time parent m1 #> 201 20 4.978707 27.46227
    #> user system elapsed -#> 0.000 0.000 0.001
    system.time( +#> 0.002 0.000 0.001
    system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve", use_compiled = FALSE)[201,]))
    #> time parent m1 #> 201 20 4.978707 27.46227
    #> user system elapsed -#> 0.032 0.000 0.032
    +#> 0.031 0.000 0.031
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/mkinresplot-1.png b/docs/reference/mkinresplot-1.png new file mode 100644 index 00000000..8636baf2 Binary files /dev/null and b/docs/reference/mkinresplot-1.png differ diff --git a/docs/reference/mkinresplot-4.png b/docs/reference/mkinresplot-4.png deleted file mode 100644 index 5f3a65e3..00000000 Binary files a/docs/reference/mkinresplot-4.png and /dev/null differ diff --git a/docs/reference/mkinresplot.html b/docs/reference/mkinresplot.html index 5cb9fa96..036917f1 100644 --- a/docs/reference/mkinresplot.html +++ b/docs/reference/mkinresplot.html @@ -18,12 +18,22 @@ + + + + + + + @@ -86,12 +96,7 @@ @@ -175,7 +180,7 @@

    Examples

    model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, FOCUS_2006_D, quiet = TRUE)
-mkinresplot(fit, "m1")
    +mkinresplot(fit, "m1")
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/mkinsub.html b/docs/reference/mkinsub.html index 257d3f89..7724220f 100644 --- a/docs/reference/mkinsub.html +++ b/docs/reference/mkinsub.html @@ -18,12 +18,20 @@ + + + + + + + @@ -86,12 +94,7 @@ @@ -182,7 +185,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/mmkin-12.png b/docs/reference/mmkin-12.png deleted file mode 100644 index 9e40d451..00000000 Binary files a/docs/reference/mmkin-12.png and /dev/null differ diff --git a/docs/reference/mmkin-14.png b/docs/reference/mmkin-14.png deleted file mode 100644 index 72cfc5e7..00000000 Binary files a/docs/reference/mmkin-14.png and /dev/null differ diff --git a/docs/reference/mmkin-15.png b/docs/reference/mmkin-15.png deleted file mode 100644 index e8a23a55..00000000 Binary files a/docs/reference/mmkin-15.png and /dev/null differ diff --git a/docs/reference/mmkin-16.png b/docs/reference/mmkin-16.png deleted file mode 100644 index 0b315b1a..00000000 Binary files a/docs/reference/mmkin-16.png and /dev/null differ diff --git a/docs/reference/mmkin-17.png b/docs/reference/mmkin-17.png deleted file mode 100644 index 01bb3ae3..00000000 Binary files a/docs/reference/mmkin-17.png and /dev/null differ diff --git a/docs/reference/mmkin-18.png b/docs/reference/mmkin-18.png deleted file mode 100644 index b98940ff..00000000 Binary files a/docs/reference/mmkin-18.png and /dev/null differ diff --git a/docs/reference/mmkin-19.png b/docs/reference/mmkin-19.png deleted file mode 100644 index b5ac70f7..00000000 Binary files a/docs/reference/mmkin-19.png and /dev/null differ diff --git a/docs/reference/mmkin-20.png b/docs/reference/mmkin-20.png deleted file mode 100644 index c2e9e5ae..00000000 Binary files a/docs/reference/mmkin-20.png and /dev/null differ diff --git a/docs/reference/mmkin-21.png b/docs/reference/mmkin-21.png deleted file mode 100644 index 7e15e1b3..00000000 Binary files a/docs/reference/mmkin-21.png and /dev/null differ diff --git a/docs/reference/mmkin-23.png b/docs/reference/mmkin-23.png deleted file mode 100644 index 45e8efc1..00000000 Binary files a/docs/reference/mmkin-23.png and /dev/null differ diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html index d649563f..e97e3f81 100644 --- a/docs/reference/mmkin.html +++ b/docs/reference/mmkin.html @@ -18,12 +18,20 @@ + + + + + + + @@ -69,6 +77,9 @@
  • 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
    • @@ -83,12 +94,7 @@ @@ -152,45 +158,39 @@

    Examples

    - 
    
+    
    # NOT RUN {
 m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
                            M1 = mkinsub("SFO", "M2"),
-                           M2 = mkinsub("SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    
+                           M2 = mkinsub("SFO"), use_of_ff = "max")
+
 m_synth_FOMC_lin <- mkinmod(parent = mkinsub("FOMC", "M1"),
                             M1 = mkinsub("SFO", "M2"),
-                            M2 = mkinsub("SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    
+                            M2 = mkinsub("SFO"), use_of_ff = "max")
+
 models <- list(SFO_lin = m_synth_SFO_lin, FOMC_lin = m_synth_FOMC_lin)
 datasets <- lapply(synthetic_data_for_UBA_2014[1:3], function(x) x$data)
 names(datasets) <- paste("Dataset", 1:3)
 
 time_default <- system.time(fits.0 <- mmkin(models, datasets, quiet = TRUE))
-time_1 <- system.time(fits.4 <- mmkin(models, datasets, cores = 1, quiet = TRUE))
    #> Warning: Optimisation by method Port did not converge.
-#> Convergence code is 1
    #> Warning: Optimisation by method Port did not converge.
-#> Convergence code is 1
    
-time_default
    #>    user  system elapsed 
-#>  15.992   0.188  11.440 
    time_1
    #>    user  system elapsed 
-#>  24.576   0.000  24.578 
    
-endpoints(fits.0[["SFO_lin", 2]])
    #> $ff
-#>   parent_M1 parent_sink       M1_M2     M1_sink 
-#>   0.7340479   0.2659521   0.7505687   0.2494313 
-#> 
-#> $SFORB
-#> logical(0)
-#> 
-#> $distimes
-#>              DT50       DT90
-#> parent  0.8777689   2.915885
-#> M1      2.3257456   7.725960
-#> M2     33.7200862 112.015702
-#> 
    
+time_1 <- system.time(fits.4 <- mmkin(models, datasets, cores = 1, quiet = TRUE))
+
+time_default
+time_1
+
+endpoints(fits.0[["SFO_lin", 2]])
+
 # plot.mkinfit handles rows or columns of mmkin result objects
-plot(fits.0[1, ])
    plot(fits.0[1, ], obs_var = c("M1", "M2"))
    plot(fits.0[, 1])
    # Use double brackets to extract a single mkinfit object, which will be plotted
+plot(fits.0[1, ])
+plot(fits.0[1, ], obs_var = c("M1", "M2"))
+plot(fits.0[, 1])
+# Use double brackets to extract a single mkinfit object, which will be plotted
 # by plot.mkinfit and can be plotted using plot_sep
-plot(fits.0[[1, 1]], sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE)
    plot_sep(fits.0[[1, 1]])
+plot(fits.0[[1, 1]], sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE)
+plot_sep(fits.0[[1, 1]])
 # Plotting with mmkin (single brackets, extracting an mmkin object) does not
 # allow to plot the observed variables separately
-plot(fits.0[1, 1])
    
-
    +plot(fits.0[1, 1]) +# }
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/plot.mkinfit-1.png b/docs/reference/plot.mkinfit-1.png new file mode 100644 index 00000000..2bb8f5dd Binary files /dev/null and b/docs/reference/plot.mkinfit-1.png differ diff --git a/docs/reference/plot.mkinfit-10.png b/docs/reference/plot.mkinfit-10.png deleted file mode 100644 index 48ab5271..00000000 Binary files a/docs/reference/plot.mkinfit-10.png and /dev/null differ diff --git a/docs/reference/plot.mkinfit-2.png b/docs/reference/plot.mkinfit-2.png new file mode 100644 index 00000000..22a3f8b0 Binary files /dev/null and b/docs/reference/plot.mkinfit-2.png differ diff --git a/docs/reference/plot.mkinfit-3.png b/docs/reference/plot.mkinfit-3.png new file mode 100644 index 00000000..93e859c7 Binary files /dev/null and b/docs/reference/plot.mkinfit-3.png differ diff --git a/docs/reference/plot.mkinfit-4.png b/docs/reference/plot.mkinfit-4.png index cb52d4ac..27edd6f3 100644 Binary files a/docs/reference/plot.mkinfit-4.png and b/docs/reference/plot.mkinfit-4.png differ diff --git a/docs/reference/plot.mkinfit-6.png b/docs/reference/plot.mkinfit-6.png deleted file mode 100644 index 8e0faa21..00000000 Binary files a/docs/reference/plot.mkinfit-6.png and /dev/null differ diff --git a/docs/reference/plot.mkinfit-8.png b/docs/reference/plot.mkinfit-8.png deleted file mode 100644 index 129f1445..00000000 Binary files a/docs/reference/plot.mkinfit-8.png and /dev/null differ diff --git a/docs/reference/plot.mkinfit.html b/docs/reference/plot.mkinfit.html index 0af2bbf6..4bdad93f 100644 --- a/docs/reference/plot.mkinfit.html +++ b/docs/reference/plot.mkinfit.html @@ -18,12 +18,24 @@ + + + + + + + @@ -86,12 +98,7 @@ @@ -237,12 +244,12 @@ plot_sep(fit, sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE, … # parent to sink included, use Levenberg-Marquardt for speed SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"), m1 = mkinsub("SFO", full = "Metabolite M1" ))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, method.modFit = "Marq") -plot(fit)
    plot(fit, show_residuals = TRUE)
    +plot(fit)
    plot(fit, show_residuals = TRUE)
    # Show the observed variables separately -plot(fit, sep_obs = TRUE, lpos = c("topright", "bottomright"))
    +plot(fit, sep_obs = TRUE, lpos = c("topright", "bottomright"))
    # Show the observed variables separately, with residuals plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"), - show_errmin = TRUE)
    + show_errmin = TRUE)
    # The same can be obtained with less typing, using the convenience function plot_sep plot_sep(fit, lpos = c("topright", "bottomright"))
    @@ -269,7 +276,7 @@ plot_sep(fit, sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE, …
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/plot.mmkin-1.png b/docs/reference/plot.mmkin-1.png new file mode 100644 index 00000000..2554b68b Binary files /dev/null and b/docs/reference/plot.mmkin-1.png differ diff --git a/docs/reference/plot.mmkin-2.png b/docs/reference/plot.mmkin-2.png index 21af1e7b..9a66294f 100644 Binary files a/docs/reference/plot.mmkin-2.png and b/docs/reference/plot.mmkin-2.png differ diff --git a/docs/reference/plot.mmkin-3.png b/docs/reference/plot.mmkin-3.png new file mode 100644 index 00000000..b0f7fa21 Binary files /dev/null and b/docs/reference/plot.mmkin-3.png differ diff --git a/docs/reference/plot.mmkin-4.png b/docs/reference/plot.mmkin-4.png deleted file mode 100644 index 3004f48f..00000000 Binary files a/docs/reference/plot.mmkin-4.png and /dev/null differ diff --git a/docs/reference/plot.mmkin-6.png b/docs/reference/plot.mmkin-6.png deleted file mode 100644 index 02ed2ab1..00000000 Binary files a/docs/reference/plot.mmkin-6.png and /dev/null differ diff --git a/docs/reference/plot.mmkin.html b/docs/reference/plot.mmkin.html index aa3df77a..11da6685 100644 --- a/docs/reference/plot.mmkin.html +++ b/docs/reference/plot.mmkin.html @@ -18,12 +18,23 @@ + + + + + + + @@ -86,12 +97,7 @@ @@ -165,11 +171,11 @@ fits <- mmkin(c("FOMC", "HS"), list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles cores = 1, quiet = TRUE, method.modFit = "Marq") - plot(fits[, "FOCUS C"])
    plot(fits["FOMC", ])
    + plot(fits[, "FOCUS C"])
    plot(fits["FOMC", ])
    # We can also plot a single fit, if we like the way plot.mmkin works, but then the plot # height should be smaller than the plot width (this is not possible for the html pages # generated by pkgdown, as far as I know). - plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
    + plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/print.mkinds.html b/docs/reference/print.mkinds.html index 14342f21..8e0d18b2 100644 --- a/docs/reference/print.mkinds.html +++ b/docs/reference/print.mkinds.html @@ -18,12 +18,19 @@ + + + + + + + @@ -86,12 +93,7 @@ @@ -143,7 +145,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/print.mkinmod.html b/docs/reference/print.mkinmod.html index 33782b7d..db15cc60 100644 --- a/docs/reference/print.mkinmod.html +++ b/docs/reference/print.mkinmod.html @@ -18,12 +18,19 @@ + + + + + + + @@ -86,12 +93,7 @@ @@ -164,7 +166,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/schaefer07_complex_case-4.png b/docs/reference/schaefer07_complex_case-4.png deleted file mode 100644 index b90185a1..00000000 Binary files a/docs/reference/schaefer07_complex_case-4.png and /dev/null differ diff --git a/docs/reference/schaefer07_complex_case.html b/docs/reference/schaefer07_complex_case.html index 605f572e..6c53f805 100644 --- a/docs/reference/schaefer07_complex_case.html +++ b/docs/reference/schaefer07_complex_case.html @@ -18,12 +18,21 @@ + + + + + + + @@ -86,12 +95,7 @@ @@ -140,24 +144,12 @@ A1 = list(type = "SFO", to = "A2"), B1 = list(type = "SFO"), C1 = list(type = "SFO"), - A2 = list(type = "SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    + A2 = list(type = "SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    # NOT RUN { fit <- mkinfit(model, data, quiet = TRUE) - plot(fit)
    endpoints(fit)
    #> $ff -#> parent_A1 parent_B1 parent_C1 parent_sink A1_A2 A1_sink -#> 0.3809618 0.1954667 0.4235715 0.0000000 0.4479596 0.5520404 -#> -#> $SFORB -#> logical(0) -#> -#> $distimes -#> DT50 DT90 -#> parent 13.95078 46.34349 -#> A1 49.75345 165.27739 -#> B1 37.26908 123.80521 -#> C1 11.23130 37.30957 -#> A2 28.50652 94.69662 -#>
    - # Compare with the results obtained in the original publication + plot(fit) + endpoints(fit) + +# }
    # Compare with the results obtained in the original publication print(schaefer07_complex_results)
    #> compound parameter KinGUI ModelMaker deviation #> 1 parent degradation rate 0.0496 0.0506 2.0 #> 2 parent DT50 13.9900 13.6900 2.2 @@ -194,7 +186,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/sigma_rl.html b/docs/reference/sigma_rl.html index b7c93961..868c0d4f 100644 --- a/docs/reference/sigma_rl.html +++ b/docs/reference/sigma_rl.html @@ -18,12 +18,21 @@ + + - + + + + + + @@ -157,7 +166,7 @@
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html index f20e3948..977ff8d8 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -18,12 +18,22 @@ + + + + + + + @@ -69,6 +79,9 @@
  • 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
    • @@ -83,12 +96,7 @@ @@ -177,21 +185,21 @@ Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, - http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    + http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    Examples

    - 
      summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE))
    #> mkin version:    0.9.46 
-#> R version:       3.4.1 
-#> Date of fit:     Sat Jul 29 15:15:30 2017 
-#> Date of summary: Sat Jul 29 15:15:30 2017 
+    
      summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE))
    #> mkin version used for fitting:    0.9.47.1 
+#> R version used for fitting:       3.4.3 
+#> Date of fit:     Thu Mar  1 14:26:27 2018 
+#> Date of summary: Thu Mar  1 14:26:27 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent_sink * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted with method Port using 35 model solutions performed in 0.084 s
+#> Fitted with method Port using 35 model solutions performed in 0.076 s
 #> 
 #> Weighting: none
 #> 
@@ -277,7 +285,7 @@
 
    
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html
index f9603f34..192e8dc2 100644
--- a/docs/reference/synthetic_data_for_UBA.html
+++ b/docs/reference/synthetic_data_for_UBA.html
@@ -18,12 +18,31 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -136,7 +155,7 @@
     
 
     
    Examples
    
-    
    
+    
    # NOT RUN {
 # The data have been generated using the following kinetic models
 m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
                            M1 = list(type = "SFO", to = "M2"),
@@ -235,11 +254,8 @@ fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data,
                quiet = TRUE)
 plot_sep(fit)
 summary(fit)
-
-
    #> Error: <text>:68:43: Unerwartete(s) SPECIAL
-#> 67: 
-#> 68:   d_rep[d_rep$time == 0 & d_rep$name <!-- %in%
-#>                                               ^
    
+# }
+
    
   
    
   
 
 
    
-  
    Site built with pkgdown.
    
+  
    Site built with pkgdown.
    
 
    
 
       
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index 8c65e604..00000000
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diff --git a/docs/reference/test_data_from_UBA_2014.html b/docs/reference/test_data_from_UBA_2014.html
index ed2ccd9c..c4292d9c 100644
--- a/docs/reference/test_data_from_UBA_2014.html
+++ b/docs/reference/test_data_from_UBA_2014.html
@@ -18,12 +18,20 @@
 
 
 
+
+
 
 
 
 
 
+  
+  
+
 
+
+
 
 
 
@@ -123,7 +131,7 @@
     
 
     
    Examples
    
-    
    
+    
      
    # NOT RUN {
   # This is a level P-II evaluation of the dataset according to the FOCUS kinetics
   # guidance. Due to the strong correlation of the parameter estimates, the
   # covariance matrix is not returned. Note that level P-II evaluations are
@@ -131,57 +139,27 @@
   # large parameter correlations, among other reasons (e.g. the adequacy of the
   # model).
   m_ws <- mkinmod(parent_w = mkinsub("SFO", "parent_s"),
-                  parent_s = mkinsub("SFO", "parent_w"))
    #> Successfully compiled differential equation model from auto-generated C code.
      f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data, quiet = TRUE)
-  plot_sep(f_river)
    
-  summary(f_river)$bpar
    #>                         Estimate se_notrans      t value       Pr(>t) Lower
-#> parent_w_0          9.598567e+01 2.33959810 4.102657e+01 9.568973e-19    NA
-#> k_parent_w_sink     3.603743e-01 0.03497716 1.030313e+01 4.988281e-09    NA
-#> k_parent_w_parent_s 6.031370e-02 0.01746026 3.454342e+00 1.514738e-03    NA
-#> k_parent_s_sink     5.099834e-11 0.10381939 4.912217e-10 5.000000e-01    NA
-#> k_parent_s_parent_w 7.419672e-02 0.11338174 6.543974e-01 2.608057e-01    NA
-#>                     Upper
-#> parent_w_0             NA
-#> k_parent_w_sink        NA
-#> k_parent_w_parent_s    NA
-#> k_parent_s_sink        NA
-#> k_parent_s_parent_w    NA
      mkinerrmin(f_river)
    #>             err.min n.optim df
-#> All data 0.09246946       5  6
-#> parent_w 0.06377096       3  3
-#> parent_s 0.20882324       2  3
    
+                  parent_s = mkinsub("SFO", "parent_w"))
+  f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data, quiet = TRUE)
+  plot_sep(f_river)
+
+  summary(f_river)$bpar
+  mkinerrmin(f_river)
+
   # This is the evaluation used for the validation of software packages
   # in the expertise from 2014
   m_soil <- mkinmod(parent = mkinsub("SFO", c("M1", "M2")),
                     M1 = mkinsub("SFO", "M3"),
                     M2 = mkinsub("SFO", "M3"),
                     M3 = mkinsub("SFO"),
-                    use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    
+                    use_of_ff = "max")
+
   f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data, quiet = TRUE)
-  plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
      summary(f_soil)$bpar
    #>                   Estimate  se_notrans    t value       Pr(>t)        Lower
-#> parent_0       76.55425583 0.943443834 81.1434164 4.422340e-30 74.602593306
-#> k_parent        0.12081956 0.004815515 25.0896457 1.639665e-18  0.111257526
-#> k_M1            0.84258650 0.930121206  0.9058889 1.871937e-01  0.085876305
-#> k_M2            0.04210878 0.013729902  3.0669396 2.729137e-03  0.021450631
-#> k_M3            0.01122919 0.008044866  1.3958205 8.804914e-02  0.002550985
-#> f_parent_to_M1  0.32240199 0.278620411  1.1571370 1.295466e-01           NA
-#> f_parent_to_M2  0.16099854 0.030548889  5.2701930 1.196191e-05           NA
-#> f_M1_to_M3      0.27921500 0.314732717  0.8871496 1.920907e-01  0.015016888
-#> f_M2_to_M3      0.55641332 0.650247079  0.8556952 2.004966e-01  0.005360551
-#>                      Upper
-#> parent_0       78.50591836
-#> k_parent        0.13120340
-#> k_M1            8.26714671
-#> k_M2            0.08266187
-#> k_M3            0.04942980
-#> f_parent_to_M1          NA
-#> f_parent_to_M2          NA
-#> f_M1_to_M3      0.90777217
-#> f_M2_to_M3      0.99658634
      mkinerrmin(f_soil)
    #>             err.min n.optim df
-#> All data 0.09649963       9 20
-#> parent   0.04721283       2  6
-#> M1       0.26551209       2  5
-#> M2       0.20327575       2  5
-#> M3       0.05196549       3  4
      
-
    
+  plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
+  summary(f_soil)$bpar
+  mkinerrmin(f_soil)
+
+# }
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/transform_odeparms.html b/docs/reference/transform_odeparms.html index bbf15a41..630a5103 100644 --- a/docs/reference/transform_odeparms.html +++ b/docs/reference/transform_odeparms.html @@ -18,12 +18,27 @@ + + + + + + + @@ -69,6 +84,9 @@
  • 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
    • @@ -83,12 +101,7 @@ @@ -170,10 +183,10 @@ parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) -summary(fit, data=FALSE) # See transformed and backtransformed parameters
    #> mkin version: 0.9.46 -#> R version: 3.4.1 -#> Date of fit: Sat Jul 29 15:15:35 2017 -#> Date of summary: Sat Jul 29 15:15:35 2017 +summary(fit, data=FALSE) # See transformed and backtransformed parameters
    #> mkin version used for fitting: 0.9.47.1 +#> R version used for fitting: 3.4.3 +#> Date of fit: Thu Mar 1 14:26:28 2018 +#> Date of summary: Thu Mar 1 14:26:28 2018 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent @@ -181,7 +194,7 @@ #> #> Model predictions using solution type deSolve #> -#> Fitted with method Port using 153 model solutions performed in 0.608 s +#> Fitted with method Port using 153 model solutions performed in 0.571 s #> #> Weighting: none #> @@ -245,84 +258,10 @@ #> DT50 DT90 #> parent 7.023 23.33 #> m1 131.761 437.70
    - +
    # NOT RUN { fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE, quiet = TRUE) -summary(fit.2, data=FALSE)
    #> mkin version: 0.9.46 -#> R version: 3.4.1 -#> Date of fit: Sat Jul 29 15:15:36 2017 -#> Date of summary: Sat Jul 29 15:15:36 2017 -#> -#> Equations: -#> d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent -#> d_m1/dt = + k_parent_m1 * parent - k_m1_sink * m1 -#> -#> Model predictions using solution type deSolve -#> -#> Fitted with method Port using 352 model solutions performed in 1.401 s -#> -#> Weighting: none -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.7500 state -#> k_parent_sink 0.1000 deparm -#> k_parent_m1 0.1001 deparm -#> k_m1_sink 0.1002 deparm -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 100.7500 -Inf Inf -#> k_parent_sink 0.1000 0 Inf -#> k_parent_m1 0.1001 0 Inf -#> k_m1_sink 0.1002 0 Inf -#> -#> Fixed parameter values: -#> value type -#> m1_0 0 state -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 99.600000 1.6140000 96.330000 1.029e+02 -#> k_parent_sink 0.047920 0.0037500 0.040310 5.553e-02 -#> k_parent_m1 0.050780 0.0020940 0.046530 5.502e-02 -#> k_m1_sink 0.005261 0.0007159 0.003809 6.713e-03 -#> -#> Parameter correlation: -#> parent_0 k_parent_sink k_parent_m1 k_m1_sink -#> parent_0 1.00000 0.6075 -0.06625 -0.1701 -#> k_parent_sink 0.60752 1.0000 -0.08740 -0.6253 -#> k_parent_m1 -0.06625 -0.0874 1.00000 0.4716 -#> k_m1_sink -0.17006 -0.6253 0.47164 1.0000 -#> -#> Residual standard error: 3.211 on 36 degrees of freedom -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 99.600000 61.720 2.024e-38 96.330000 1.029e+02 -#> k_parent_sink 0.047920 12.780 3.050e-15 0.040310 5.553e-02 -#> k_parent_m1 0.050780 24.250 3.407e-24 0.046530 5.502e-02 -#> k_m1_sink 0.005261 7.349 5.758e-09 0.003809 6.713e-03 -#> -#> Chi2 error levels in percent: -#> err.min n.optim df -#> All data 6.398 4 15 -#> parent 6.827 3 6 -#> m1 4.490 1 9 -#> -#> Resulting formation fractions: -#> ff -#> parent_sink 0.4855 -#> parent_m1 0.5145 -#> m1_sink 1.0000 -#> -#> Estimated disappearance times: -#> DT50 DT90 -#> parent 7.023 23.33 -#> m1 131.761 437.70
    - +summary(fit.2, data=FALSE) +# }
    initials <- fit$start$value names(initials) <- rownames(fit$start) transformed <- fit$start_transformed$value @@ -330,162 +269,29 @@ transform_odeparms(initials, SFO_SFO)
    #> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink #> 100.750000 -2.302585 -2.301586 -2.300587
    backtransform_odeparms(transformed, SFO_SFO)
    #> parent_0 k_parent_sink k_parent_m1 k_m1_sink #> 100.7500 0.1000 0.1001 0.1002
    - +
    # NOT RUN { # The case of formation fractions SFO_SFO.ff <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO"), - use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    + use_of_ff = "max") + fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE) -summary(fit.ff, data = FALSE)
    #> mkin version: 0.9.46 -#> R version: 3.4.1 -#> Date of fit: Sat Jul 29 15:15:37 2017 -#> Date of summary: Sat Jul 29 15:15:37 2017 -#> -#> Equations: -#> d_parent/dt = - k_parent * parent -#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 -#> -#> Model predictions using solution type deSolve -#> -#> Fitted with method Port using 185 model solutions performed in 0.772 s -#> -#> Weighting: none -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.7500 state -#> k_parent 0.1000 deparm -#> k_m1 0.1001 deparm -#> f_parent_to_m1 0.5000 deparm -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 100.750000 -Inf Inf -#> log_k_parent -2.302585 -Inf Inf -#> log_k_m1 -2.301586 -Inf Inf -#> f_parent_ilr_1 0.000000 -Inf Inf -#> -#> Fixed parameter values: -#> value type -#> m1_0 0 state -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 99.60000 1.61400 96.3300 102.9000 -#> log_k_parent -2.31600 0.04187 -2.4010 -2.2310 -#> log_k_m1 -5.24800 0.13610 -5.5230 -4.9720 -#> f_parent_ilr_1 0.04096 0.06477 -0.0904 0.1723 -#> -#> Parameter correlation: -#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 -#> parent_0 1.0000 0.5178 -0.1701 -0.5489 -#> log_k_parent 0.5178 1.0000 -0.3285 -0.5451 -#> log_k_m1 -0.1701 -0.3285 1.0000 0.7466 -#> f_parent_ilr_1 -0.5489 -0.5451 0.7466 1.0000 -#> -#> Residual standard error: 3.211 on 36 degrees of freedom -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 99.600000 61.720 2.024e-38 96.330000 1.029e+02 -#> k_parent 0.098700 23.880 5.701e-24 0.090660 1.074e-01 -#> k_m1 0.005261 7.349 5.758e-09 0.003992 6.933e-03 -#> f_parent_to_m1 0.514500 22.490 4.374e-23 0.468100 5.606e-01 -#> -#> Chi2 error levels in percent: -#> err.min n.optim df -#> All data 6.398 4 15 -#> parent 6.459 2 7 -#> m1 4.690 2 8 -#> -#> Resulting formation fractions: -#> ff -#> parent_m1 0.5145 -#> parent_sink 0.4855 -#> -#> Estimated disappearance times: -#> DT50 DT90 -#> parent 7.023 23.33 -#> m1 131.761 437.70
    initials <- c("f_parent_to_m1" = 0.5) +summary(fit.ff, data = FALSE) +initials <- c("f_parent_to_m1" = 0.5) transformed <- transform_odeparms(initials, SFO_SFO.ff) -backtransform_odeparms(transformed, SFO_SFO.ff)
    #> f_parent_to_m1 -#> 0.5
    +backtransform_odeparms(transformed, SFO_SFO.ff) + # And without sink SFO_SFO.ff.2 <- mkinmod( parent = list(type = "SFO", to = "m1", sink = FALSE), m1 = list(type = "SFO"), - use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    + use_of_ff = "max") + fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D, quiet = TRUE) -summary(fit.ff.2, data = FALSE)
    #> mkin version: 0.9.46 -#> R version: 3.4.1 -#> Date of fit: Sat Jul 29 15:15:38 2017 -#> Date of summary: Sat Jul 29 15:15:38 2017 -#> -#> Equations: -#> d_parent/dt = - k_parent * parent -#> d_m1/dt = + k_parent * parent - k_m1 * m1 -#> -#> Model predictions using solution type deSolve -#> -#> Fitted with method Port using 104 model solutions performed in 0.416 s -#> -#> Weighting: none -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.7500 state -#> k_parent 0.1000 deparm -#> k_m1 0.1001 deparm -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 100.750000 -Inf Inf -#> log_k_parent -2.302585 -Inf Inf -#> log_k_m1 -2.301586 -Inf Inf -#> -#> Fixed parameter values: -#> value type -#> m1_0 0 state -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 84.790 2.96500 78.78 90.800 -#> log_k_parent -2.756 0.08088 -2.92 -2.593 -#> log_k_m1 -4.214 0.11150 -4.44 -3.988 -#> -#> Parameter correlation: -#> parent_0 log_k_parent log_k_m1 -#> parent_0 1.0000 0.11059 0.46156 -#> log_k_parent 0.1106 1.00000 0.06274 -#> log_k_m1 0.4616 0.06274 1.00000 -#> -#> Residual standard error: 8.333 on 37 degrees of freedom -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 84.79000 28.600 3.938e-27 78.78000 90.80000 -#> k_parent 0.06352 12.360 5.237e-15 0.05392 0.07483 -#> k_m1 0.01478 8.966 4.114e-11 0.01179 0.01853 -#> -#> Chi2 error levels in percent: -#> err.min n.optim df -#> All data 19.66 3 16 -#> parent 17.56 2 7 -#> m1 18.71 1 9 -#> -#> Estimated disappearance times: -#> DT50 DT90 -#> parent 10.91 36.25 -#> m1 46.89 155.75
    -
    +summary(fit.ff.2, data = FALSE) +# }
    -

    Site built with pkgdown.

    +

    Site built with pkgdown.

    diff --git a/docs/reference/twa.html b/docs/reference/twa.html deleted file mode 100644 index be76b439..00000000 --- a/docs/reference/twa.html +++ /dev/null @@ -1,179 +0,0 @@ - - - - - - - - -Function to calculate maximum time weighted average concentrations from kinetic models fitted with mkinfit — twa • mkin - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - -
    - -
    -
    -
    -

    Function to calculate maximum time weighted average concentrations from kinetic models fitted with mkinfit

    -
    - - -

    This function calculates maximum moving window time weighted average concentrations -(TWAs) for kinetic models fitted with mkinfit. Currently, only -calculations for the parent are implemented for the SFO, FOMC and DFOP models, -using the analytical formulas given in the PEC soil section of the FOCUS -guidance.

    - - - 
    twa(fit, windows)
    - -

    Arguments

    - - - - - - - - - - -
    fit

    An object of class mkinfit.

    windows

    The width of the time windows for which the TWAs should be calculated.

    - -

    Value

    - -

    A numeric vector, named using the windows argument.

    - -

    References

    - -

    FOCUS (2006) “Guidance Document on Estimating Persistence and - Degradation Kinetics from Environmental Fate Studies on Pesticides in EU - Registration” Report of the FOCUS Work Group on Degradation Kinetics, - EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, - http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    - - -

    Examples

    - 
      fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-  twa(fit, c(7, 21))
    #>        7       21 
-#> 34.71343 18.22124
    -
    - -
    - -
    -
    -

    Developed by Johannes Ranke.

    -
    - -
    -

    Site built with pkgdown.

    -
    - -
    -
    - - - diff --git a/vignettes/FOCUS_L.html b/vignettes/FOCUS_L.html index ccde0c82..9bdfb5c6 100644 --- a/vignettes/FOCUS_L.html +++ b/vignettes/FOCUS_L.html @@ -1,258 +1,248 @@ - - - + + - - - +Laboratory Data L1 + - + + - + + -Example evaluation of FOCUS Laboratory Data L1 to L3 + + - - - - - - - - - - - - - - +body { + max-width: 800px; + margin: auto; + padding: 1em; + line-height: 20px; +} +tt, code, pre { + font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; +} - - - - - - - - - -
    - - - - - - - - - - - - - -
    -
    -
    -
    -
    - -
    - - - - - + +

    Laboratory Data L1

    +

    The following code defines example dataset L1 from the FOCUS kinetics +report, p. 284:

    -
    -

    Laboratory Data L1

    -

    The following code defines example dataset L1 from the FOCUS kinetics report, p. 284:

    -
    library("mkin", quietly = TRUE)
+
    library("mkin", quietly = TRUE)
 FOCUS_2006_L1 = data.frame(
   t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2),
   parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6,
              72.0, 71.9, 50.3, 59.4, 47.0, 45.1,
              27.7, 27.3, 10.0, 10.4, 2.9, 4.0))
-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
    
-
    Here we use the assumptions of simple first order (SFO), the case of declining rate constant over time (FOMC) and the case of two different phases of the kinetics (DFOP). For a more detailed discussion of the models, please see the FOCUS kinetics report.
    
-
    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:    0.9.47.1 
+FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
+
    
+
+
    Here we use the assumptions of simple first order (SFO), the case of declining
+rate constant over time (FOMC) and the case of two different phases of the
+kinetics (DFOP). For a more detailed discussion of the models, please see the
+FOCUS kinetics report.
    
+
+
    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:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:05 2018 
-## Date of summary: Sun Jan 14 17:50:05 2018 
+## Date of fit:     Thu Mar  1 14:24:54 2018 
+## Date of summary: Thu Mar  1 14:24:54 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 0.242 s
+## Fitted with method Port using 37 model solutions performed in 0.24 s
 ## 
 ## Weighting: none
 ## 
@@ -321,36 +311,46 @@ summary(m.L1.SFO)
    
 ##    21   parent     10.0    12.416  -2.4163
 ##    21   parent     10.4    12.416  -2.0163
 ##    30   parent      2.9     5.251  -2.3513
-##    30   parent      4.0     5.251  -1.2513
    +## 30 parent 4.0 5.251 -1.2513 +     +

    A plot of the fit is obtained with the plot function for mkinfit objects.

    -
    plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
    -

    + +
    plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
+
    + +

    plot of chunk unnamed-chunk-4

    +

    The residual plot can be easily obtained by

    -
    mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
    -

    -

    For comparison, the FOMC model is fitted as well, and the χ2 error level is checked.

    -
    m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
    -
    ## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation by method Port did not converge.
-## Convergence code is 1
    -
    plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
    -

    -
    summary(m.L1.FOMC, data = FALSE)
    -
    ## mkin version:    0.9.47.1 
+
+
    mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
+
    
+
+
    plot of chunk unnamed-chunk-5
    
+
+
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level
+is checked.
    
+
+
    m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
+plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
+
    
+
+
    plot of chunk unnamed-chunk-6
    
+
+
    summary(m.L1.FOMC, data = FALSE)
+
    
+
+
    ## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:06 2018 
-## Date of summary: Sun Jan 14 17:50:06 2018 
-## 
-## 
-## Warning: Optimisation by method Port did not converge.
-## Convergence code is 1 
-## 
+## Date of fit:     Thu Mar  1 14:24:56 2018 
+## Date of summary: Thu Mar  1 14:24:57 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 155 model solutions performed in 0.432 s
+## Fitted with method Port using 611 model solutions performed in 1.376 s
 ## 
 ## Weighting: none
 ## 
@@ -370,16 +370,16 @@ summary(m.L1.SFO)
    
 ## None
 ## 
 ## Optimised, transformed parameters with symmetric confidence intervals:
-##           Estimate Std. Error   Lower  Upper
-## parent_0     92.47      1.449   89.38  95.56
-## log_alpha    11.35    435.800 -917.60 940.30
-## log_beta     13.70    435.800 -915.20 942.60
+##           Estimate Std. Error    Lower   Upper
+## parent_0     92.47      1.482    89.31   95.63
+## log_alpha    11.25    598.200 -1264.00 1286.00
+## log_beta     13.60    598.200 -1261.00 1289.00
 ## 
 ## Parameter correlation:
 ##           parent_0 log_alpha log_beta
-## parent_0    1.0000    0.2209   0.2208
-## log_alpha   0.2209    1.0000   1.0000
-## log_beta    0.2208    1.0000   1.0000
+## parent_0    1.0000   -0.3016  -0.3016
+## log_alpha  -0.3016    1.0000   1.0000
+## log_beta   -0.3016    1.0000   1.0000
 ## 
 ## Residual standard error: 3.045 on 15 degrees of freedom
 ## 
@@ -388,9 +388,9 @@ summary(m.L1.SFO)
    ## t-test (unrealistically) based on the assumption of normal distribution ## for estimators of untransformed parameters. ## Estimate t value Pr(>t) Lower Upper -## parent_0 92.47 63.33000 6.183e-20 89.38 95.56 -## alpha 85190.00 0.03367 4.868e-01 0.00 Inf -## beta 891000.00 0.03367 4.868e-01 0.00 Inf +## parent_0 92.47 64.45000 4.757e-20 89.31 95.63 +## alpha 76830.00 0.02852 4.888e-01 0.00 Inf +## beta 803500.00 0.02852 4.888e-01 0.00 Inf ## ## Chi2 error levels in percent: ## err.min n.optim df @@ -399,50 +399,100 @@ summary(m.L1.SFO)     ## ## Estimated disappearance times: ## DT50 DT90 DT50back -## parent 7.249 24.08 7.249     -

    We get a warning that the default optimisation algorithm Port did not converge, which is an indication that the model is overparameterised, i.e. contains too many parameters that are ill-defined as a consequence.

    -

    And in fact, due to the higher number of parameters, and the lower number of degrees of freedom of the fit, the χ2 error level is actually higher for the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the parameters log_alpha and log_beta internally fitted in the model have excessive confidence intervals, that span more than 25 orders of magnitude (!) when backtransformed to the scale of alpha and beta. Also, the t-test for significant difference from zero does not indicate such a significant difference, with p-values greater than 0.1, and finally, the parameter correlation of log_alpha and log_beta is 1.000, clearly indicating that the model is overparameterised.

    -

    The χ2 error levels reported in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to integer percentages and partly deviate by one percentage point from the results calculated by mkin. The reason for this is not known. However, mkin gives the same χ2 error levels as the kinfit package and the calculation routines of the kinfit package have been extensively compared to the results obtained by the KinGUI software, as documented in the kinfit package vignette. KinGUI was the first widely used standard package in this field. Also, the calculation of χ2 error levels was compared with KinGUII, CAKE and DegKin manager in a project sponsored by the German Umweltbundesamt (Ranke 2014).

    -
    -
    +## parent 7.249 24.08 7.249 + + +

    We get a warning that the default optimisation algorithm Port did not converge, which +is an indication that the model is overparameterised, i.e. contains too many +parameters that are ill-defined as a consequence.

    + +

    And in fact, due to the higher number of parameters, and the lower number of +degrees of freedom of the fit, the \(\chi^2\) error level is actually higher for +the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the +parameters log_alpha and log_beta internally fitted in the model have +excessive confidence intervals, that span more than 25 orders of magnitude (!) +when backtransformed to the scale of alpha and beta. Also, the t-test +for significant difference from zero does not indicate such a significant difference, +with p-values greater than 0.1, and finally, the parameter correlation of log_alpha +and log_beta is 1.000, clearly indicating that the model is overparameterised.

    + +

    The \(\chi^2\) error levels reported in Appendix 3 and Appendix 7 to the FOCUS +kinetics report are rounded to integer percentages and partly deviate by one +percentage point from the results calculated by mkin. The reason for +this is not known. However, mkin gives the same \(\chi^2\) error levels +as the kinfit package and the calculation routines of the kinfit package have +been extensively compared to the results obtained by the KinGUI +software, as documented in the kinfit package vignette. KinGUI was the first +widely used standard package in this field. Also, the calculation of +\(\chi^2\) error levels was compared with KinGUII, CAKE and DegKin manager in +a project sponsored by the German Umweltbundesamt [@ranke2014].

    +

    Laboratory Data L2

    -

    The following code defines example dataset L2 from the FOCUS kinetics report, p. 287:

    -
    FOCUS_2006_L2 = data.frame(
+
+
    The following code defines example dataset L2 from the FOCUS kinetics
+report, p. 287:
    
+
+
    FOCUS_2006_L2 = data.frame(
   t = rep(c(0, 1, 3, 7, 14, 28), each = 2),
   parent = c(96.1, 91.8, 41.4, 38.7,
              19.3, 22.3, 4.6, 4.6,
              2.6, 1.2, 0.3, 0.6))
-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
    
-
    
+FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
+
    +

    SFO fit for L2

    -

    Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument show_residuals to the plot command.

    -
    m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
+
+
    Again, the SFO model is fitted and the result is plotted. The residual plot
+can be obtained simply by adding the argument show_residuals to the plot
+command.
    
+
+
    m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
 plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - SFO")
    
-
    
-
    The χ2 error level of 14% suggests that the model does not fit very well. This is also obvious from the plots of the fit, in which we have included the residual plot.
    
-
    In the FOCUS kinetics report, it is stated that there is no apparent systematic error observed from the residual plot up to the measured DT90 (approximately at day 5), and there is an underestimation beyond that point.
    
-
    We may add that it is difficult to judge the random nature of the residuals just from the three samplings at days 0, 1 and 3. Also, it is not clear a priori why a consistent underestimation after the approximate DT90 should be irrelevant. However, this can be rationalised by the fact that the FOCUS fate models generally only implement SFO kinetics.
    
-
    -
    + main = "FOCUS L2 - SFO") + + +

    plot of chunk unnamed-chunk-8

    + +

    The \(\chi^2\) error level of 14% suggests that the model does not fit very well. +This is also obvious from the plots of the fit, in which we have included +the residual plot.

    + +

    In the FOCUS kinetics report, it is stated that there is no apparent systematic +error observed from the residual plot up to the measured DT90 (approximately at +day 5), and there is an underestimation beyond that point.

    + +

    We may add that it is difficult to judge the random nature of the residuals just +from the three samplings at days 0, 1 and 3. Also, it is not clear a +priori why a consistent underestimation after the approximate DT90 should be +irrelevant. However, this can be rationalised by the fact that the FOCUS fate +models generally only implement SFO kinetics.

    +

    FOMC fit for L2

    -

    For comparison, the FOMC model is fitted as well, and the χ2 error level is checked.

    -
    m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
+
+
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level
+is checked.
    
+
+
    m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.FOMC, show_residuals = TRUE,
-     main = "FOCUS L2 - FOMC")
    
-
    
-
    summary(m.L2.FOMC, data = FALSE)
    
-
    ## mkin version:    0.9.47.1 
+     main = "FOCUS L2 - FOMC")
+
    
+
+
    plot of chunk unnamed-chunk-9
    
+
+
    summary(m.L2.FOMC, data = FALSE)
+
    
+
+
    ## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:07 2018 
-## Date of summary: Sun Jan 14 17:50:07 2018 
+## Date of fit:     Thu Mar  1 14:24:57 2018 
+## Date of summary: Thu Mar  1 14:24:57 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 0.166 s
+## Fitted with method Port using 81 model solutions performed in 0.169 s
 ## 
 ## Weighting: none
 ## 
@@ -491,21 +541,31 @@ plot(m.L2.FOMC, show_residuals = TRUE,
 ## 
 ## Estimated disappearance times:
 ##          DT50  DT90 DT50back
-## parent 0.8092 5.356    1.612
    
-
    The error level at which the χ2 test passes is much lower in this case. Therefore, the FOMC model provides a better description of the data, as less experimental error has to be assumed in order to explain the data.
    
-
    -
    +## parent 0.8092 5.356 1.612 + + +

    The error level at which the \(\chi^2\) test passes is much lower in this case. +Therefore, the FOMC model provides a better description of the data, as less +experimental error has to be assumed in order to explain the data.

    +

    DFOP fit for L2

    -

    Fitting the four parameter DFOP model further reduces the χ2 error level.

    -
    m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
+
+
    Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level.
    
+
+
    m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - DFOP")
    
-
    
-
    summary(m.L2.DFOP, data = FALSE)
    
-
    ## mkin version:    0.9.47.1 
+     main = "FOCUS L2 - DFOP")
+
    
+
+
    plot of chunk unnamed-chunk-10
    
+
+
    summary(m.L2.DFOP, data = FALSE)
+
    
+
+
    ## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:08 2018 
-## Date of summary: Sun Jan 14 17:50:08 2018 
+## Date of fit:     Thu Mar  1 14:24:58 2018 
+## Date of summary: Thu Mar  1 14:24:58 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -514,7 +574,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 336 model solutions performed in 0.712 s
+## Fitted with method Port using 336 model solutions performed in 0.721 s
 ## 
 ## Weighting: none
 ## 
@@ -542,8 +602,12 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## log_k2    -1.0880         NA    NA    NA
 ## g_ilr     -0.2821         NA    NA    NA
 ## 
-## Parameter correlation:
    
-
    ## Warning in print.summary.mkinfit(x): Could not estimate covariance matrix; singular system:
    
+## Parameter correlation:
+
    + +
    ## Warning in print.summary.mkinfit(x): Could not estimate covariance matrix; singular system:
+
    + 
    ## Could not estimate covariance matrix; singular system:
 ## 
 ## Residual standard error: 1.732 on 8 degrees of freedom
@@ -565,36 +629,62 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## 
 ## Estimated disappearance times:
 ##          DT50  DT90 DT50_k1 DT50_k2
-## parent 0.5335 5.311 0.03009   2.058
    -

    Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion. However, the failure to calculate the covariance matrix indicates that the parameter estimates correlate excessively. Therefore, the FOMC model may be preferred for this dataset.

    -
    -
    -
    +## parent 0.5335 5.311 0.03009 2.058 + + +

    Here, the DFOP model is clearly the best-fit model for dataset L2 based on the +chi2 error level criterion. However, the failure to calculate the covariance +matrix indicates that the parameter estimates correlate excessively. Therefore, +the FOMC model may be preferred for this dataset.

    +

    Laboratory Data L3

    -

    The following code defines example dataset L3 from the FOCUS kinetics report, p. 290.

    -
    FOCUS_2006_L3 = data.frame(
+
+
    The following code defines example dataset L3 from the FOCUS kinetics report,
+p. 290.
    
+
+
    FOCUS_2006_L3 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(97.8, 60, 51, 43, 35, 22, 15, 12))
-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
    
-
    
+FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
+
    +

    Fit multiple models

    -

    As of mkin version 0.9-39 (June 2015), we can fit several models to one or more datasets in one call to the function mmkin. The datasets have to be passed in a list, in this case a named list holding only the L3 dataset prepared above.

    -
    # Only use one core here, not to offend the CRAN checks
+
+
    As of mkin version 0.9-39 (June 2015), we can fit several models to
+one or more datasets in one call to the function mmkin. The datasets
+have to be passed in a list, in this case a named list holding only
+the L3 dataset prepared above.
    
+
+
    # Only use one core here, not to offend the CRAN checks
 mm.L3 <- mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
                list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
-plot(mm.L3)
    
-
    
-
    The χ2 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 χ2 test passes of 7%. Fitting the four parameter DFOP model further reduces the χ2 error level considerably.
    
-
    -
    +plot(mm.L3) + + +

    plot of chunk unnamed-chunk-12

    + +

    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.

    +

    Accessing mmkin objects

    -

    The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index.

    -

    We can extract the summary and plot for e.g. the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.

    -
    summary(mm.L3[["DFOP", 1]])
    -
    ## mkin version:    0.9.47.1 
+
+
    The objects returned by mmkin are arranged like a matrix, with
+models as a row index and datasets as a column index.
    
+
+
    We can extract the summary and plot for e.g. the DFOP fit,
+using square brackets for indexing which will result in the use of
+the summary and plot functions working on mkinfit objects.
    
+
+
    summary(mm.L3[["DFOP", 1]])
+
    
+
+
    ## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:08 2018 
-## Date of summary: Sun Jan 14 17:50:08 2018 
+## Date of fit:     Thu Mar  1 14:24:59 2018 
+## Date of summary: Thu Mar  1 14:24:59 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -603,7 +693,7 @@ plot(mm.L3)
    
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 137 model solutions performed in 0.291 s
+## Fitted with method Port using 137 model solutions performed in 0.283 s
 ## 
 ## Weighting: none
 ## 
@@ -668,40 +758,64 @@ plot(mm.L3)
    ## 30 parent 35.0 35.15 -0.14707 ## 60 parent 22.0 23.26 -1.25919 ## 91 parent 15.0 15.18 -0.18181 -## 120 parent 12.0 10.19 1.81395 -
    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 χ2 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.

    -
    -
    -
    +## 120 parent 12.0 10.19 1.81395 + + +
    plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
+
    + +

    plot of chunk unnamed-chunk-13

    + +

    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.

    +

    Laboratory Data L4

    -

    The following code defines example dataset L4 from the FOCUS kinetics report, p. 293:

    -
    FOCUS_2006_L4 = data.frame(
+
+
    The following code defines example dataset L4 from the FOCUS kinetics
+report, p. 293:
    
+
+
    FOCUS_2006_L4 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(96.6, 96.3, 94.3, 88.8, 74.9, 59.9, 53.5, 49.0))
-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
    
+FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
+
    +

    Fits of the SFO and FOMC models, plots and summaries are produced below:

    -
    # Only use one core here, not to offend the CRAN checks
+
+
    # Only use one core here, not to offend the CRAN checks
 mm.L4 <- mmkin(c("SFO", "FOMC"), cores = 1,
                list("FOCUS L4" = FOCUS_2006_L4_mkin),
                quiet = TRUE)
-plot(mm.L4)
    
-
    
-
    The χ2 error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the χ2 test passes is slightly lower for the FOMC model. However, the difference appears negligible.
    
-
    summary(mm.L4[["SFO", 1]], data = FALSE)
    
-
    ## mkin version:    0.9.47.1 
+plot(mm.L4)
+
    
+
+
    plot of chunk unnamed-chunk-15
    
+
+
    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:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:09 2018 
-## Date of summary: Sun Jan 14 17:50:09 2018 
+## Date of fit:     Thu Mar  1 14:24:59 2018 
+## Date of summary: Thu Mar  1 14:24:59 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 0.094 s
+## Fitted with method Port using 46 model solutions performed in 0.098 s
 ## 
 ## Weighting: none
 ## 
@@ -749,19 +863,23 @@ plot(mm.L4)
    
 ## 
 ## Estimated disappearance times:
 ##        DT50 DT90
-## parent  106  352
    -
    summary(mm.L4[["FOMC", 1]], data = FALSE)
    -
    ## mkin version:    0.9.47.1 
+## parent  106  352
+
    + +
    summary(mm.L4[["FOMC", 1]], data = FALSE)
+
    + +
    ## mkin version:    0.9.46.3 
 ## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:09 2018 
-## Date of summary: Sun Jan 14 17:50:09 2018 
+## Date of fit:     Thu Mar  1 14:24:59 2018 
+## Date of summary: Thu Mar  1 14:24:59 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 0.139 s
+## Fitted with method Port using 66 model solutions performed in 0.134 s
 ## 
 ## Weighting: none
 ## 
@@ -810,37 +928,11 @@ plot(mm.L4)
    ## ## Estimated disappearance times: ## DT50 DT90 DT50back -## parent 108.9 1644 494.9 -
    -
    -

    References

    -
    -
    -

    Ranke, Johannes. 2014. “Prüfung und Validierung von Modellierungssoftware als Alternative zu ModelMaker 4.0.” Umweltbundesamt Projektnummer 27452.

    -
    -
    -
    - - - -
    - - - - - +## parent 108.9 1644 494.9 +     +

    References

    + diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd index e97876da..b16dfea6 100644 --- a/vignettes/compiled_models.Rmd +++ b/vignettes/compiled_models.Rmd @@ -92,10 +92,10 @@ Here we get a performance benefit of a factor of `r factor_FOMC_SFO` using the version of the differential equation model compiled from C code! -This vignette was built with mkin `r packageVersion("mkin")` on +This vignette was built with mkin `r utils::packageVersion("mkin")` on ```{r sessionInfo, echo = FALSE} -cat(capture.output(sessionInfo())[1:3], sep = "\n") +cat(utils::capture.output(utils::sessionInfo())[1:3], sep = "\n") if(!inherits(try(cpuinfo <- readLines("/proc/cpuinfo")), "try-error")) { cat(gsub("model name\t: ", "CPU model: ", cpuinfo[grep("model name", cpuinfo)[1]])) } -- cgit v1.2.1 From 3512ac1f7c41bbf94edbf73c6464da0f1d0c7160 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 2 Mar 2018 16:42:47 +0100 Subject: Bring back README.html for cgit.jrwb.de --- README.html | 207 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 207 insertions(+) create mode 100644 README.html diff --git a/README.html b/README.html new file mode 100644 index 00000000..57c4d550 --- /dev/null +++ b/README.html @@ -0,0 +1,207 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    + + + + + + + + + + + + + + +
    +

    mkin

    +

    +

    The R package mkin provides calculation routines for the analysis of chemical degradation data, including multicompartment kinetics as needed for modelling the formation and decline of transformation products, or if several compartments are involved.

    +
    +

    Installation

    +

    You can install the latest released version from CRAN from within R:

    +
    install.packages("mkin")
    +
    +
    +

    Background

    +

    In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance and helpful tools have been developed as detailed in ‘Credits and historical remarks’ below.

    +
    +
    +

    Usage

    +

    For a start, have a look a the code examples provided for plot.mkinfit and plot.mmkin, and at the package vignettes FOCUS L and FOCUS D.

    +
    +
    +

    Documentation

    +

    The HTML documentation is available at jrwb.de, at github and at R-Forge.

    +
    +
    +

    Features

    +
      +
    • Highly flexible model specification using mkinmod, including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two latent state variables for the observed variable.
      • +
    • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
      • +
    • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
      • +
    • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
      • +
    • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric logration transformation that is now used for the formation fractions.
      • +
    • A side effect of this is that when parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which can not occur in a single experiment with a single defined radiolabel position.
      • +
    • The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.
      • +
    • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
      • +
    • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
      • +
    • Iteratively reweighted least squares fitting is implemented in a similar way as in KinGUII and CAKE (see below). Simply add the argument reweight.method = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.
      • +
    • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
      • +
    • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
      • +
    +
    +
    +

    GUI

    +

    There is a graphical user interface that I consider useful for real work. Please refer to its documentation page for installation instructions and a manual.

    +
    +
    +

    News

    +

    There is a ChangeLog, for the latest CRAN release and one for the github master branch.

    +
    +
    +

    Credits and historical remarks

    +

    mkin would not be possible without the underlying software stack consisting of R and the packages deSolve and FME, to say the least.

    +

    It could not have been written without me being introduced to regulatory fate modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories Ltd (formerly RCC Ltd). mkin greatly profits from and largely follows the work done by the FOCUS Degradation Kinetics Workgroup, as detailed in their guidance document from 2006, slightly updated in 2011 and in 2014.

    +

    Also, it was inspired by the first version of KinGUI developed by BayerCropScience, which is based on the MatLab runtime environment.

    +

    The companion package kinfit (now deprecated) was started in 2008 and first published on CRAN on 01 May 2010.

    +

    The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.

    +

    In 2011, Bayer Crop Science started to distribute an R based successor to KinGUI named KinGUII whose R code is based on mkin, but which added, amongst other refinements, a closed source graphical user interface (GUI), iteratively reweighted least squares (IRLS) optimisation of the variance for each of the observed variables, and Markov Chain Monte Carlo (MCMC) simulation functionality, similar to what is available e.g. in the FME package.

    +

    Somewhat in parallel, Syngenta has sponsored the development of an mkin and KinGUII based GUI application called CAKE, which also adds IRLS and MCMC, is more limited in the model formulation, but puts more weight on usability. CAKE is available for download from the CAKE website, where you can also find a zip archive of the R scripts derived from mkin, published under the GPL license.

    +

    Finally, there is KineticEval, which contains a further development of the scripts used for KinGUII, so the different tools will hopefully be able to learn from each other in the future as well.

    +
    +
    +

    Development

    +

    Contributions are welcome! Your mkin fork is just a mouse click away… The master branch on github should always be in good shape, I implement new features in separate branches now. If you prefer subversion, project members for the r-forge project are welcome as well. Generally, the source code of the latest CRAN version should be available there. You can also browse the source code at cgit.jrwb.de/mkin.

    +
    +
    + + + + +
    + + + + + + -- cgit v1.2.1 From 8650f26f63a64ac8b72326e2679719744ac99f07 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 2 Mar 2018 17:23:40 +0100 Subject: Use pkgdown.jrwb.de as canonical doc URL The mkin pkgdown docs have made it to the pkgdown README :) https://github.com/r-lib/pkgdown/commit/f0ef0b58a526add2077e5899f45335a5118091f0 --- README.html | 14 +++++++------- README.md | 22 +++++++++++----------- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/README.html b/README.html index 57c4d550..c9f86c6b 100644 --- a/README.html +++ b/README.html @@ -136,7 +136,7 @@ $(document).ready(function () {

    Usage

    -

    For a start, have a look a the code examples provided for plot.mkinfit and plot.mmkin, and at the package vignettes FOCUS L and FOCUS D.

    +

    For a start, have a look a the code examples provided for plot.mkinfit and plot.mmkin, and at the package vignettes FOCUS L and FOCUS D.

    Documentation

    @@ -145,17 +145,17 @@ $(document).ready(function () {

    Features

      -
    • Highly flexible model specification using mkinmod, including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two latent state variables for the observed variable.
      • -
    • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
      • -
    • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
      • -
    • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
      • -
    • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric logration transformation that is now used for the formation fractions.
      • +
    • Highly flexible model specification using mkinmod, including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two latent state variables for the observed variable.
      • +
    • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
      • +
    • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
      • +
    • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
      • +
    • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric logration transformation that is now used for the formation fractions.
    • A side effect of this is that when parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which can not occur in a single experiment with a single defined radiolabel position.
    • The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.
    • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
    • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
    • Iteratively reweighted least squares fitting is implemented in a similar way as in KinGUII and CAKE (see below). Simply add the argument reweight.method = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.
      • -
    • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
      • +
    • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
    • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
    diff --git a/README.md b/README.md index 4ff631f6..26cdcafb 100644 --- a/README.md +++ b/README.md @@ -27,12 +27,12 @@ detailed guidance and helpful tools have been developed as detailed in ## Usage For a start, have a look a the code examples provided for -[`plot.mkinfit`](http://kinfit.r-forge.r-project.org/mkin_static/reference/plot.mkinfit.html) +[`plot.mkinfit`](https://pkgdown.jrwb.de/mkin/reference/plot.mkinfit.html) and -[`plot.mmkin`](http://kinfit.r-forge.r-project.org/mkin_static/reference/plot.mmkin.html), and +[`plot.mmkin`](https://pkgdown.jrwb.de/mkin/reference/plot.mmkin.html), and at the package vignettes -[`FOCUS L`](http://kinfit.r-forge.r-project.org/mkin_static/articles/FOCUS_L.html) and -[`FOCUS D`](http://kinfit.r-forge.r-project.org/mkin_static/articles/FOCUS_D.html). +[`FOCUS L`](https://pkgdown.jrwb.de/mkin/articles/FOCUS_L.html) and +[`FOCUS D`](https://pkgdown.jrwb.de/mkin/articles/FOCUS_D.html). ## Documentation @@ -44,28 +44,28 @@ and at [R-Forge](http://kinfit.r-forge.r-project.org/mkin_static/index.html). ## Features * Highly flexible model specification using - [`mkinmod`](http://kinfit.r-forge.r-project.org/mkin_static/reference/mkinmod.html), + [`mkinmod`](https://pkgdown.jrwb.de/mkin/reference/mkinmod.html), including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two latent state variables for the observed variable. * As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example - [`plot.mmkin`](http://kinfit.r-forge.r-project.org/mkin_static/reference/plot.mmkin.html). + [`plot.mmkin`](https://pkgdown.jrwb.de/mkin/reference/plot.mmkin.html). * Model solution (forward modelling) in the function - [`mkinpredict`](http://kinfit.r-forge.r-project.org/mkin_static/reference/mkinpredict.html) + [`mkinpredict`](https://pkgdown.jrwb.de/mkin/reference/mkinpredict.html) is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the `deSolve` package (default is `lsoda`). * If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see - [vignette `compiled_models`](http://kinfit.r-forge.r-project.org/mkin_static/articles/compiled_models.html). + [vignette `compiled_models`](https://pkgdown.jrwb.de/mkin/articles/compiled_models.html). The autogeneration of C code was inspired by the [`ccSolve`](https://github.com/karlines/ccSolve) package. Thanks to Karline Soetaert for her work on that. * By default, kinetic rate constants and kinetic formation fractions are transformed internally using - [`transform_odeparms`](http://kinfit.r-forge.r-project.org/mkin_static/reference/transform_odeparms.html) + [`transform_odeparms`](https://pkgdown.jrwb.de/mkin/reference/transform_odeparms.html) so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice @@ -90,8 +90,8 @@ and at [R-Forge](http://kinfit.r-forge.r-project.org/mkin_static/index.html). componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged. * Iterative reweighting is also possible using the two-component error model - for analytical data of - [Rocke and Lorenzato](http://kinfit.r-forge.r-project.org/mkin_static/reference/sigma_rl.html) + for analytical data of + [Rocke and Lorenzato](https://pkgdown.jrwb.de/mkin/reference/sigma_rl.html) using the argument `reweight.method = "tc"`. * When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite. -- cgit v1.2.1