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authorjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2012-04-10 21:50:22 +0000
committerjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2012-04-10 21:50:22 +0000
commitc1144753adfa0809003085009ebd85f8af9beda8 (patch)
treec07afafb9e6a3ffd1248167f4e40983bb3ef85fc /vignettes/mkin.Rnw
parentd3df16102c5ed4bf9182b4f1893561e99eaed166 (diff)
- Fitting and summaries now work with the new parameter transformations.
- The SFORB models with metabolites is broken (see TODO) - Moved the vignette to the location recommended since R 2.14 - Added the missing documentation - Commented out the schaefer_complex_case test, as this version of mkin is not able to fit a model without sink and therefore mkin estimated parameters are quite different git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@22 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
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+% $Id: mkin.Rnw 66 2010-09-03 08:50:26Z jranke $
+%%\VignetteIndexEntry{Routines for fitting kinetic models with one or more state variables to chemical degradation data}
+%%VignetteDepends{FME}
+%%\usepackage{Sweave}
+\documentclass[12pt,a4paper]{article}
+\usepackage{a4wide}
+%%\usepackage[lists,heads]{endfloat}
+\input{header}
+\hypersetup{
+ pdftitle = {mkin - Routines for fitting kinetic models with one or more state variables to chemical degradation data},
+ pdfsubject = {Manuscript},
+ pdfauthor = {Johannes Ranke},
+ colorlinks = {true},
+ linkcolor = {blue},
+ citecolor = {blue},
+ urlcolor = {red},
+ hyperindex = {true},
+ linktocpage = {true},
+}
+\SweaveOpts{engine=R, eps=FALSE, keep.source = TRUE}
+<<setup, echo = FALSE, results = hide>>=
+options(prompt = "R> ")
+options(SweaveHooks = list(
+ cex = function() par(cex.lab = 1.3, cex.axis = 1.3)))
+@
+\begin{document}
+\title{mkin -\\
+Routines for fitting kinetic models with one or more state variables to chemical degradation data}
+\author{\textbf{Johannes Ranke} \\
+%EndAName
+Eurofins Regulatory AG\\
+Weidenweg 15, CH--4310 Rheinfelden, Switzerland\\{1cm}
+and\\
+University of Bremen\\
+}
+\maketitle
+
+\begin{abstract}
+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 has been developed, based on nonlinear optimisation.
+The \RR{} add-on package \Rpackage{mkin} implements fitting some of the models
+recommended in this guidance from within R and calculates some statistical
+measures for data series within one or more compartments, for parent and
+metabolites.
+\end{abstract}
+
+
+\thispagestyle{empty} \setcounter{page}{0}
+
+\clearpage
+
+\tableofcontents
+
+\textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation
+
+\section{Introduction}
+\label{intro}
+
+Many approaches are possible regarding the evaluation of chemical degradation
+data. The \Rpackage{kinfit} package \citep{pkg:kinfit} in \RR{}
+\citep{rcore2010} implements the approach recommended in the kinetics report
+provided by the FOrum for Co-ordination of pesticide fate models and their
+USe \citep{FOCUS2006} for simple data series for one parent compound in one
+compartment.
+
+The \Rpackage{mkin} package \citep{pkg:mkin} extends this approach to data series
+with metabolites and more than one compartment and includes the possibility
+for back reactions.
+
+\section{Example}
+\label{exam}
+
+In the following, requirements for data formatting are explained. Then the
+procedure for fitting the four kinetic models recommended by the FOCUS group
+to an example dataset for parent only given in the FOCUS kinetics report is
+illustrated. The explanations are kept rather verbose in order to lower the
+barrier for \RR{} newcomers.
+
+\subsection{Data format}
+
+The following listing shows example dataset C from the FOCUS kinetics
+report as distributed with the \Rpackage{mkin} package
+
+<<FOCUS_2006_C_data, echo=TRUE, eval=TRUE>>=
+library("mkin")
+FOCUS_2006_C
+@
+
+Note that the data needs to be in the format of a data frame containing a
+variable \Robject{name} specifying the observed variable, indicating the
+compound name and, if applicable, the compartment, a variable \Robject{time}
+containing sampling times, and a numeric variable \Robject{value} specifying
+the observed value of the variable. If a further variable \Robject{error}
+is present, this will be used to give different weights to the data points
+(the higher the error, the lower the weight, see the help page of the
+\Robject{modCost} function of the \Rpackage{FME} package \citep{soetaert10}).
+Replicate measurements are not recorded in extra columns but simply appended,
+leading to multiple occurrences of the sampling times \Robject{time}.
+
+Small to medium size dataset can be conveniently entered directly as \RR{} code
+as shown in the following listing
+
+<<data_format, echo=TRUE>>=
+example_data <- data.frame(
+ name = rep("parent", 9),
+ time = c(0, 1, 3, 7, 14, 28, 63, 91, 119),
+ value = c(85.1, 57.9, 29.9, 14.6, 9.7, 6.6, 4, 3.9, 0.6)
+)
+@
+
+\subsection{Model definition}
+
+The next task is to define the model to be fitted to the data. In order to
+facilitate this task, a convenience function \Robject{mkinmod} is available.
+
+<<model_definition, echo=TRUE>>=
+SFO <- mkinmod(parent = list(type = "SFO"))
+SFORB <- mkinmod(parent = list(type = "SFORB"))
+SFO_SFO <- mkinmod(
+ parent = list(type = "SFO", to = "m1", sink = TRUE),
+ m1 = list(type = "SFO"))
+SFORB_SFO <- mkinmod(
+ parent = list(type = "SFORB", to = "m1", sink = TRUE),
+ m1 = list(type = "SFO"))
+@
+
+The model definitions given above define sets of linear first-order ordinary
+differential equations. In these cases, a coefficient matrix is also returned.
+
+Other models that include time on the right-hand side of the differential
+equation are the first-order multi-compartment (FOMC) model and the
+Hockey-Stick (HS) model. At present, only the FOMC model can only be used, and
+only for the parent compound.
+
+\subsection{Fitting the model}
+
+Then the model parameters should be fitted to the data. The function
+\Robject{mkinfit} internally creates a cost function using \Robject{modCost}
+from the \Rpackage{FME} package and the produces a fit using \Robject{modFit}
+from the same package. In cases of linear first-order differential
+equations, the solution used for calculating the cost function is based
+on the fundamental system of the coefficient matrix, as proposed by
+\citet{bates88}.
+
+<<model_fitting, echo=TRUE>>=
+SFO.fit <- mkinfit(SFO, FOCUS_2006_C)
+summary(SFO.fit)
+SFORB.fit <- mkinfit(SFORB, FOCUS_2006_C)
+summary(SFORB.fit)
+SFO_SFO.fit <- mkinfit(SFO_SFO, FOCUS_2006_D, plot=TRUE)
+summary(SFO_SFO.fit, data=FALSE)
+#SFORB_SFO.fit <- mkinfit(SFORB_SFO, FOCUS_2006_D,
+# parms.ini = c(f_parent_to_m1 = 0.5, k_m1 = 0.2),
+# plot=TRUE)
+#summary(SFORB_SFO.fit, data=FALSE)
+@
+
+\bibliographystyle{plainnat}
+\bibliography{references}
+
+\end{document}
+% vim: set foldmethod=syntax:

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