- 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

1 files changed, 0 insertions, 162 deletions

diff --git a/inst/doc/mkin.Rnw b/inst/doc/mkin.Rnw
deleted file mode 100644
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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

-Product Safety \\

-Harlan Laboratories Ltd. \\

-Zelgliweg 1, CH--4452 Itingen, Switzerland}

-\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>>=

-# Do not show significance stars as they interfere with vignette generation

-options(show.signif.stars = FALSE)

-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, plot=TRUE)

-summary(SFORB_SFO.fit, data=FALSE)

-@

-

-\bibliographystyle{plainnat}

-\bibliography{references}

-

-\end{document}

-% vim: set foldmethod=syntax: