<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> <html> <head> <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>add_err. 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]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> <![endif]--> </head> <body> <div class="container"> <header> <div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar"> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <a class="navbar-brand" href="../index.html">mkin</a> </div> <div id="navbar" class="navbar-collapse collapse"> <ul class="nav navbar-nav"> <li> <a href="../index.html">Home</a> </li> <li> <a href="../reference/index.html">Reference</a> </li> </ul> <ul class="nav navbar-nav navbar-right"> <li> <a href="https://github.com/jranke/mkin"> <span class="fa fa-github fa-lg"></span> </a> </li> </ul> </div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> </header> <div class="page-header"> <h1> </h1> </div> <div class="row"> <div class="col-md-9"> <p>Normally distributed errors are added to data predicted for a specific degradation model using <code>mkinpredict</code>. The variance of the error may depend on the predicted value and is specified as a standard deviation.</p> <pre><span class='fu'>add_err</span>(<span class='no'>prediction</span>, <span class='no'>sdfunc</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>1000</span>, <span class='kw'>LOD</span> <span class='kw'>=</span> <span class='fl'>0.1</span>, <span class='kw'>reps</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>seed</span> <span class='kw'>=</span> <span class='fl'>NA</span>)</pre> <h2>Arguments</h2> <dl class="dl-horizontal"> <dt>prediction</dt> <dd> A prediction from a kinetic model as produced by <code>mkinpredict</code>. </dd> <dt>sdfunc</dt> <dd> A function taking the predicted value as its only argument and returning a standard deviation that should be used for generating the random error terms for this value. </dd> <dt>n</dt> <dd> The number of datasets to be generated. </dd> <dt>LOD</dt> <dd> The limit of detection (LOD). Values that are below the LOD after adding the random error will be set to NA. </dd> <dt>reps</dt> <dd> The number of replicates to be generated within the datasets. </dd> <dt>digits</dt> <dd> The number of digits to which the values will be rounded. </dd> <dt>seed</dt> <dd> The seed used for the generation of random numbers. If NA, the seed is not set. </dd> </dl> <div class="Value"> <h2>Value</h2> <p>A list of datasets compatible with <code>mmkin</code>, i.e. the components of the list are datasets compatible with <code>mkinfit</code>.</p> </div> <div class="References"> <h2>References</h2> <p>Ranke J and Lehmann R (2015) To t-test or not to t-test, that is the question. XV Symposium on Pesticide Chemistry 2-4 September 2015, Piacenza, Italy http://chem.uft.uni-bremen.de/ranke/posters/piacenza_2015.pdf</p> </div> <h2 id="examples">Examples</h2> <pre class="examples"><div class='input'><span class='co'># The kinetic model</span> <span class='no'>m_SFO_SFO</span> <span class='kw'><-</span> <span class='fu'>mkinmod</span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>mkinsub</span>(<span class='st'>"SFO"</span>, <span class='st'>"M1"</span>), <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>mkinsub</span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output'><strong class='text-info'>Successfully compiled differential equation model from auto-generated C code.</strong></div><div class='input'> <span class='co'># Generate a prediction for a specific set of parameters</span> <span class='no'>sampling_times</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span>) <span class='co'># This is the prediction used for the "Type 2 datasets" on the Piacenza poster</span> <span class='co'># from 2015</span> <span class='no'>d_SFO_SFO</span> <span class='kw'><-</span> <span class='fu'>mkinpredict</span>(<span class='no'>m_SFO_SFO</span>, <span class='fu'>c</span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.1</span>, <span class='kw'>f_parent_to_M1</span> <span class='kw'>=</span> <span class='fl'>0.5</span>, <span class='kw'>k_M1</span> <span class='kw'>=</span> <span class='fu'>log</span>(<span class='fl'>2</span>)/<span class='fl'>1000</span>), <span class='fu'>c</span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fl'>0</span>), <span class='no'>sampling_times</span>) <span class='co'># Add an error term with a constant (independent of the value) standard deviation</span> <span class='co'># of 10, and generate three datasets</span> <span class='no'>d_SFO_SFO_err</span> <span class='kw'><-</span> <span class='fu'>add_err</span>(<span class='no'>d_SFO_SFO</span>, <span class='kw'>function</span>(<span class='no'>x</span>) <span class='fl'>10</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>3</span>, <span class='kw'>seed</span> <span class='kw'>=</span> <span class='fl'>123456789</span> ) <span class='co'># Name the datasets for nicer plotting</span> <span class='fu'>names</span>(<span class='no'>d_SFO_SFO_err</span>) <span class='kw'><-</span> <span class='fu'>paste</span>(<span class='st'>"Dataset"</span>, <span class='fl'>1</span>:<span class='fl'>3</span>) <span class='co'># Name the model in the list of models (with only one member in this case)</span> <span class='co'># for nicer plotting later on.</span> <span class='co'># Be quiet and use the faster Levenberg-Marquardt algorithm, as the datasets</span> <span class='co'># are easy and examples are run often. Use only one core not to offend CRAN</span> <span class='co'># checks</span> <span class='no'>f_SFO_SFO</span> <span class='kw'><-</span> <span class='fu'>mmkin</span>(<span class='fu'>list</span>(<span class='st'>"SFO-SFO"</span> <span class='kw'>=</span> <span class='no'>m_SFO_SFO</span>), <span class='no'>d_SFO_SFO_err</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>method.modFit</span> <span class='kw'>=</span> <span class='st'>"Marq"</span>) <span class='fu'>plot</span>(<span class='no'>f_SFO_SFO</span>)</div><img src='unknown-4.png' alt='' width='540' height='400' /><div class='input'> <span class='co'># We would like to inspect the fit for dataset 3 more closely</span> <span class='co'># Using double brackets makes the returned object an mkinfit object</span> <span class='co'># instead of a list of mkinfit objects, so plot.mkinfit is used</span> <span class='fu'>plot</span>(<span class='no'>f_SFO_SFO</span><span class='kw'>[[</span><span class='fl'>3</span>]], <span class='kw'>show_residuals</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><img src='unknown-6.png' alt='' width='540' height='400' /><div class='input'> <span class='co'># If we use single brackets, we should give two indices (model and dataset),</span> <span class='co'># and plot.mmkin is used</span> <span class='fu'>plot</span>(<span class='no'>f_SFO_SFO</span>[<span class='fl'>1</span>, <span class='fl'>3</span>])</div><img src='unknown-8.png' alt='' width='540' height='400' /><div class='input'> </div></pre> </div> <div class="col-md-3"> <h2>Author</h2> Johannes Ranke </div> </div> <footer> <p>Built by <a href="http://hadley.github.io/pkgdown/">pkgdown</a>. 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