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diff --git a/vignettes/mkin.Rnw b/vignettes/mkin.Rnw deleted file mode 100644 index 1befe009..00000000 --- a/vignettes/mkin.Rnw +++ /dev/null @@ -1,161 +0,0 @@ -%\VignetteIndexEntry{Routines for fitting kinetic models with one or more state variables to chemical degradation data} -%\VignetteEngine{knitr::knitr} -\documentclass[12pt,a4paper]{article} -\usepackage{a4wide} -\usepackage[utf8]{inputenc} -\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}, - linktocpage = {true}, -} - -\begin{document} - -<<include=FALSE>>= -require(knitr) -opts_chunk$set(engine='R', tidy=FALSE) -@ - -\title{mkin -\\ -Routines for fitting kinetic models with one or more state variables to -chemical degradation data} -\author{\textbf{Johannes Ranke} \\[0.5cm] -%EndAName -Wissenschaftlicher Berater\\ -Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany\\[0.5cm] -and\\[0.5cm] -Privatdozent at the 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{rcore2014} implements the approach recommended in the kinetics report -provided by the FOrum for Co-ordination of pesticide fate models and their -USe \citep{FOCUS2006, FOCUSkinetics2011} 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 transformation products, commonly termed metabolites, and to more than one -compartment. It is also possible to include back reactions, so equilibrium reactions -and equilibrium partitioning can be specified, although this oftentimes leads -to an overparameterisation of the model. - -When mkin was first published in May 2010, the most commonly used tools -for fitting more complex kinetic degradation models to experimental data were KinGUI -\citep{schaefer2007}, a MATLAB$^\circledR$ based tool with a graphical user -interface that was specifically tailored to the task and included some output -as proposed by the FOCUS Kinetics Workgroup, and ModelMaker, a general purpose -compartment based tool providing infrastructure for fitting dynamic simulation -models based on differential equations to data. - -At that time, the R package \Rpackage{FME} (Flexible Modelling Environment) -\citep{soetaert2010} was already available, and provided a good basis for -developing a package specifically tailored to the task. The remaining challenge -was to make it as easy as possible for the users (including the author of this -vignette) to specify the system of differential equations and to include the -output requested by the FOCUS guidance, such as the relative standard deviation -that has to be assumed for the residuals, such that the $\chi^2$ -goodness-of-fit test as defined by the FOCUS kinetics workgroup would pass -using an significance level $\alpha$ of 0.05. - -Also, mkin introduced using analytical solutions for parent only kinetics for -improved optimization speed. Later, Eigenvalue based solutions were -introduced to mkin for the case of linear differential equations (\textit{i.e.} -where the FOMC or DFOP models were not used for the parent compound), greatly -improving the optimization speed for these cases. - -Soon after the publication of mkin, two derived tools were published, namely -KinGUII (available from Bayer Crop Science) and CAKE (commissioned to Tessella -by Syngenta), which added a graphical user interface (GUI), and added fitting by -iteratively reweighted least squares (IRLS) and characterisation of likely -parameter distributions by Markov Chain Monte Carlo (MCMC) sampling. - -CAKE focuses on a smooth use experience, sacrificing some flexibility in the model -definition, allowing only two primary metabolites in parallel. KinGUI offers -quite a flexible widget for specifying complex kinetic models. Back-reactions -(non-instanteneous equilibria) were not present in the first version of -KinGUII, and only simple first-order models could be specified for -transformation products. As of May 2014 (KinGUII version 2.1), back-reactions -and biphasic modelling of metabolites are also available in KinGUII. - -Currently (May 2014), the main feature available in \Rpackage{mkin} which is -not present in KinGUII or CAKE, is the estimation of parameter confidence -intervals based on transformed parameters. For rate constants, the log -transformation is used, as proposed by Bates and Watts \citep[p. 77, p. -149]{bates1988}. Approximate intervals are constructed for the transformed rate -constants \citep[compare][p. 153]{bates1988}, \textit{i.e.} for their logarithms. -Confidence intervals for the rate constants are then obtained using the -appropriate backtransformation using the exponential function. - -In the first version of \Rpackage{mkin} allowing for specifying models using -formation fractions, a home-made reparameterisation was used in order to ensure -that the sum of formation fractions would not exceed unity. - -This method is still used in the current version of KinGUII (v2.1), with a -modification that allows for fixing the pathway to sink to zero. CAKE uses -penalties in the objective function in order to enforce this constraint. - -In 2012, an alternative reparameterisation of the formation fractions was -proposed together with René Lehmann \citep{ranke2012}, based on isometric -logratio transformation (ILR). The aim was to improve the validity of the -linear approximation of the objective function during the parameter -estimation procedure as well as in the subsequent calculation of parameter -confidence intervals. - -In the first attempt at providing improved parameter confidence intervals -introduced to \Rpackage{mkin} in 2013, confidence intervals obtained from -FME on the transformed parameters were simply all backtransformed one by one -to yield asymetric confidence intervals for the backtransformed parameters. - -However, while there is a 1:1 relation between the rate constants in the model -and the transformed parameters fitted in the model, the parameters obtained by the -isometric logratio transformation are calculated from the set of formation -fractions that quantify the paths to each of the compounds formed from a -specific parent compound, and no such 1:1 relation exists. - -Therefore, parameter confidence intervals for formation fractions obtained with -this method only appear valid for the case of a single transformation product, where -only one formation fraction is to be estimated, directly corresponding to one -component of the ilr transformed parameter. - -The confidence intervals obtained by backtransformation for the cases where a -1:1 relation between transformed and original parameter exist are considered by -the author of this vignette to be more accurate than those obtained using a -re-estimation of the Hessian matrix after backtransformation, as implemented -in the FME package. - -\bibliographystyle{plainnat} -\bibliography{references} - -\end{document} -% vim: set foldmethod=syntax: |