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authorJohannes Ranke <jranke@uni-bremen.de>2016-10-26 23:18:20 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2016-10-26 23:18:20 +0200
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-<!-- Generated by pkgdown: do not edit by hand --><html><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>mkin - Kinetic evaluation of chemical degradation data. mkin</title><!-- jquery --><script src="https://code.jquery.com/jquery-3.1.0.min.js" integrity="sha384-nrOSfDHtoPMzJHjVTdCopGqIqeYETSXhZDFyniQ8ZHcVy08QesyHcnOUpMpqnmWq" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://maxcdn.bootstrapcdn.com/bootswatch/3.3.7/cerulean/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous"><script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script><!-- Font Awesome icons --><link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-T8Gy5hrqNKT+hzMclPo118YTQO6cYprQmhrYwIiQ/3axmI1hQomh7Ud2hPOy8SP1" crossorigin="anonymous"><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><!-- mathjax --><script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script><!--[if lt IE 9]>
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+ <header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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<h1>mkin - Kinetic evaluation of chemical degradation data</h1>
<h4 class="author">Johannes Ranke</h4>
- <h4 class="date">2016-10-06</h4>
+ <h4 class="date">2016-10-26</h4>
</div>
+<div class="contents">
<p><a href="http://www.jrwb.de">Wissenschaftlicher Berater, Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany</a><br><a href="http://chem.uft.uni-bremen.de/ranke">Privatdozent at the University of Bremen</a></p>
<div id="abstract" class="section level1">
-<h1>Abstract</h1>
+<h1 class="hasAnchor"><html><body><a href="#abstract" class="anchor"> </a></body></html>Abstract</h1>
<p>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 <code>R</code> add-on package <code>mkin</code> <span class="citation">(Ranke 2016)</span> 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.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">require</span>(mkin)
m_SFO_SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mkinmod.html">mkinmod</a></span>(<span class="dt">parent =</span> <span class="kw"><a href="../reference/mkinsub.html">mkinsub</a></span>(<span class="st">"SFO"</span>, <span class="st">"M1"</span>),
@@ -66,10 +68,10 @@ d_SFO_SFO_SFO_err &lt;-<span class="st"> </span><span class="kw"><a href="../ref
f_SFO_SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mkinfit.html">mkinfit</a></span>(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[<span class="dv">1</span>]], <span class="dt">quiet =</span> <span class="ot">TRUE</span>)
<span class="kw"><a href="../reference/plot.mkinfit.html">plot_sep</a></span>(f_SFO_SFO_SFO, <span class="dt">lpos =</span> <span class="kw">c</span>(<span class="st">"topright"</span>, <span class="st">"bottomright"</span>, <span class="st">"bottomright"</span>))</code></pre></div>
-<p><img src="/home/jranke/git/mkin/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png" width="768"></p>
+<p><img src="mkin_files/figure-html/unnamed-chunk-2-1.png" width="768"></p>
</div>
<div id="background" class="section level1">
-<h1>Background</h1>
+<h1 class="hasAnchor"><html><body><a href="#background" class="anchor"> </a></body></html>Background</h1>
<p>Many approaches are possible regarding the evaluation of chemical degradation data.</p>
<p>The now deprecated <code>kinfit</code> package <span class="citation">(Ranke 2015)</span> in <code>R</code> <span class="citation">(R Development Core Team 2016)</span> implements the approach recommended in the kinetics report provided by the FOrum for Co-ordination of pesticide fate models and their USe <span class="citation">(FOCUS Work Group on Degradation Kinetics 2006; 2014)</span> for simple data series for one parent compound in one compartment.</p>
<p>The <code>mkin</code> package <span class="citation">(Ranke 2016)</span> 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.</p>
@@ -79,39 +81,39 @@ f_SFO_SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../referen
<p>Also, <code>mkin</code> introduced using analytical solutions for parent only kinetics for improved optimization speed. Later, Eigenvalue based solutions were introduced to <code>mkin</code> for the case of linear differential equations (<em>i.e.</em> where the FOMC or DFOP models were not used for the parent compound), greatly improving the optimization speed for these cases.</p>
<p>The possibility to specify back-reactions and a biphasic model (SFORB) for metabolites were present in <code>mkin</code> from the very beginning.</p>
<div id="derived-software-tools" class="section level2">
-<h2>Derived software tools</h2>
+<h2 class="hasAnchor"><html><body><a href="#derived-software-tools" class="anchor"> </a></body></html>Derived software tools</h2>
<p>Soon after the publication of <code>mkin</code>, 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.</p>
<p>CAKE focuses on a smooth use experience, sacrificing some flexibility in the model definition, originally allowing only two primary metabolites in parallel. The current version 3.2 of CAKE release in March 2016 uses a basic scheme for up to six metabolites in a flexible arrangement, but does not support back-reactions (non-instantaneous equilibria) or biphasic kinetics for metabolites.</p>
<p>KinGUI offers an even more flexible widget for specifying complex kinetic models. Back-reactions (non-instanteneous equilibria) were supported early on, but until 2014, only simple first-order models could be specified for transformation products. Starting with KinGUII version 2.1, biphasic modelling of metabolites was also available in KinGUII.</p>
<p>A further graphical user interface (GUI) that has recently been brought to a decent degree of maturity is the browser based GUI named <code>gmkin</code>. Please see its <a href="http://kinfit.r-forge.r-project.org/gmkin_static">documentation page</a> and <a href="http://kinfit.r-forge.r-project.org/gmkin_static/vignettes/gmkin_manual.html">manual</a> for further information.</p>
</div>
<div id="recent-developments" class="section level2">
-<h2>Recent developments</h2>
+<h2 class="hasAnchor"><html><body><a href="#recent-developments" class="anchor"> </a></body></html>Recent developments</h2>
<p>Currently (June 2016), the main features available in <code>mkin</code> which are not present in KinGUII or CAKE, are the speed increase by using compiled code when a compiler is present, parallel model fitting on multicore machines using the <code>mmkin</code> function, and the estimation of parameter confidence intervals based on transformed parameters. These are explained in more detail below.</p>
</div>
</div>
<div id="internal-parameter-transformations" class="section level1">
-<h1>Internal parameter transformations</h1>
+<h1 class="hasAnchor"><html><body><a href="#internal-parameter-transformations" class="anchor"> </a></body></html>Internal parameter transformations</h1>
<p>For rate constants, the log transformation is used, as proposed by Bates and Watts <span class="citation">(1988, 77, 149)</span>. Approximate intervals are constructed for the transformed rate constants <span class="citation">(compare Bates and Watts 1988, 135)</span>, <em>i.e.</em> for their logarithms. Confidence intervals for the rate constants are then obtained using the appropriate backtransformation using the exponential function.</p>
<p>In the first version of <code>mkin</code> 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.</p>
<p>This method is still used in the current version of KinGUII (v2.1 from April 2014), 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.</p>
<p>In 2012, an alternative reparameterisation of the formation fractions was proposed together with Ren&eacute; Lehmann <span class="citation">(Ranke and Lehmann 2012)</span>, 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.</p>
<div id="confidence-intervals-based-on-transformed-parameters" class="section level2">
-<h2>Confidence intervals based on transformed parameters</h2>
+<h2 class="hasAnchor"><html><body><a href="#confidence-intervals-based-on-transformed-parameters" class="anchor"> </a></body></html>Confidence intervals based on transformed parameters</h2>
<p>In the first attempt at providing improved parameter confidence intervals introduced to <code>mkin</code> 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.</p>
<p>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.</p>
<p>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.</p>
<p>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.</p>
</div>
<div id="parameter-t-test-based-on-untransformed-parameters" class="section level2">
-<h2>Parameter t-test based on untransformed parameters</h2>
+<h2 class="hasAnchor"><html><body><a href="#parameter-t-test-based-on-untransformed-parameters" class="anchor"> </a></body></html>Parameter t-test based on untransformed parameters</h2>
<p>The standard output of many nonlinear regression software packages includes the results from a test for significant difference from zero for all parameters. Such a test is also recommended to check the validity of rate constants in the FOCUS guidance <span class="citation">(FOCUS Work Group on Degradation Kinetics 2014, 96ff)</span>.</p>
<p>It has been argued that the precondition for this test, <em>i.e.</em> normal distribution of the estimator for the parameters, is not fulfilled in the case of nonlinear regression <span class="citation">(Ranke and Lehmann 2015)</span>. However, this test is commonly used by industry, consultants and national authorities in order to decide on the reliability of parameter estimates, based on the FOCUS guidance mentioned above. Therefore, the results of this one-sided t-test are included in the summary output from <code>mkin</code>.</p>
<p>As it is not reasonable to test for significant difference of the transformed parameters (<em>e.g.</em> <span class="math inline">\(log(k)\)</span>) from zero, the t-test is calculated based on the model definition before parameter transformation, <em>i.e.</em> in a similar way as in packages that do not apply such an internal parameter transformation. A note is included in the <code>mkin</code> output, pointing to the fact that the t-test is based on the unjustified assumption of normal distribution of the parameter estimators.</p>
</div>
</div>
<div id="references" class="section level1">
-<h1>References</h1>
+<h1 class="hasAnchor"><html><body><a href="#references" class="anchor"> </a></body></html>References</h1>
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@@ -146,9 +148,10 @@ f_SFO_SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../referen
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+</div>
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- <div class="col-md-3 hidden-xs">
+ <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked"><li><a href="#abstract">Abstract</a></li>
@@ -165,7 +168,14 @@ f_SFO_SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../referen
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