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<title>add_err. mkin 0.9.44.9000</title>
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Johannes Ranke
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<h1>
Add normally distributed errors to simulated kinetic degradation data
</h1>
<div class="row">
<div class="span8">
<h2>Usage</h2>
<pre><span class="functioncall"><a href='add_err.html'>add_err</a></span><span class="keyword">(</span><span class="symbol">prediction</span><span class="keyword">,</span> <span class="symbol">sdfunc</span><span class="keyword">,</span>
<span class="argument">n</span> <span class="argument">=</span> <span class="number">1000</span><span class="keyword">,</span> <span class="argument">LOD</span> <span class="argument">=</span> <span class="number">0.1</span><span class="keyword">,</span> <span class="argument">reps</span> <span class="argument">=</span> <span class="number">2</span><span class="keyword">,</span>
<span class="argument">digits</span> <span class="argument">=</span> <span class="number">1</span><span class="keyword">,</span> <span class="argument">seed</span> <span class="argument">=</span> <span class="number">NA</span><span class="keyword">)</span></pre>
<h2>Arguments</h2>
<dl>
<dt>prediction</dt>
<dd>
A prediction from a kinetic model as produced by <code><a href='mkinpredict.html'>mkinpredict</a></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="Description">
<h2>Description</h2>
<p>Normally distributed errors are added to data predicted for a specific
degradation model using <code><a href='mkinpredict.html'>mkinpredict</a></code>. The variance of the error
may depend on the predicted value and is specified as a standard deviation.</p>
</div>
<div class="Value">
<h2>Value</h2>
<p><dl>
A list of datasets compatible with <code><a href='mmkin.html'>mmkin</a></code>, i.e.
the components of the list are datasets compatible with
<code><a href='mkinfit.html'>mkinfit</a></code>.
</dl></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="comment"># The kinetic model</span>
<span class="symbol">m_SFO_SFO</span> <span class="assignement"><-</span> <span class="functioncall"><a href='mkinmod.html'>mkinmod</a></span><span class="keyword">(</span><span class="argument">parent</span> <span class="argument">=</span> <span class="functioncall"><a href='mkinsub.html'>mkinsub</a></span><span class="keyword">(</span><span class="string">"SFO"</span><span class="keyword">,</span> <span class="string">"M1"</span><span class="keyword">)</span><span class="keyword">,</span>
<span class="argument">M1</span> <span class="argument">=</span> <span class="functioncall"><a href='mkinsub.html'>mkinsub</a></span><span class="keyword">(</span><span class="string">"SFO"</span><span class="keyword">)</span><span class="keyword">,</span> <span class="argument">use_of_ff</span> <span class="argument">=</span> <span class="string">"max"</span><span class="keyword">)</span></div>
<strong class='message'>Successfully compiled differential equation model from auto-generated C code.</strong>
<div class='input'>
<span class="comment"># Generate a prediction for a specific set of parameters</span>
<span class="symbol">sampling_times</span> <span class="assignement">=</span> <span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/c'>c</a></span><span class="keyword">(</span><span class="number">0</span><span class="keyword">,</span> <span class="number">1</span><span class="keyword">,</span> <span class="number">3</span><span class="keyword">,</span> <span class="number">7</span><span class="keyword">,</span> <span class="number">14</span><span class="keyword">,</span> <span class="number">28</span><span class="keyword">,</span> <span class="number">60</span><span class="keyword">,</span> <span class="number">90</span><span class="keyword">,</span> <span class="number">120</span><span class="keyword">)</span>
<span class="comment"># This is the prediction used for the "Type 2 datasets" on the Piacenza poster</span>
<span class="comment"># from 2015</span>
<span class="symbol">d_SFO_SFO</span> <span class="assignement"><-</span> <span class="functioncall"><a href='mkinpredict.html'>mkinpredict</a></span><span class="keyword">(</span><span class="symbol">m_SFO_SFO</span><span class="keyword">,</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/c'>c</a></span><span class="keyword">(</span><span class="argument">k_parent</span> <span class="argument">=</span> <span class="number">0.1</span><span class="keyword">,</span> <span class="argument">f_parent_to_M1</span> <span class="argument">=</span> <span class="number">0.5</span><span class="keyword">,</span>
<span class="argument">k_M1</span> <span class="argument">=</span> <span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/Log'>log</a></span><span class="keyword">(</span><span class="number">2</span><span class="keyword">)</span><span class="keyword">/</span><span class="number">1000</span><span class="keyword">)</span><span class="keyword">,</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/c'>c</a></span><span class="keyword">(</span><span class="argument">parent</span> <span class="argument">=</span> <span class="number">100</span><span class="keyword">,</span> <span class="argument">M1</span> <span class="argument">=</span> <span class="number">0</span><span class="keyword">)</span><span class="keyword">,</span>
<span class="symbol">sampling_times</span><span class="keyword">)</span>
<span class="comment"># Add an error term with a constant (independent of the value) standard deviation</span>
<span class="comment"># of 10, and generate three datasets</span>
<span class="symbol">d_SFO_SFO_err</span> <span class="assignement"><-</span> <span class="functioncall"><a href='add_err.html'>add_err</a></span><span class="keyword">(</span><span class="symbol">d_SFO_SFO</span><span class="keyword">,</span> <span class="keyword">function</span><span class="keyword">(</span><span class="formalargs">x</span><span class="keyword">)</span> <span class="number">10</span><span class="keyword">,</span> <span class="argument">n</span> <span class="argument">=</span> <span class="number">3</span><span class="keyword">,</span> <span class="argument">seed</span> <span class="argument">=</span> <span class="number">123456789</span> <span class="keyword">)</span>
<span class="comment"># Name the datasets for nicer plotting</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/names'>names</a></span><span class="keyword">(</span><span class="symbol">d_SFO_SFO_err</span><span class="keyword">)</span> <span class="assignement"><-</span> <span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span><span class="keyword">(</span><span class="string">"Dataset"</span><span class="keyword">,</span> <span class="number">1</span><span class="keyword">:</span><span class="number">3</span><span class="keyword">)</span>
<span class="comment"># Name the model in the list of models (with only one member in this case)</span>
<span class="comment"># for nicer plotting later on.</span>
<span class="comment"># Be quiet and use the faster Levenberg-Marquardt algorithm, as the datasets</span>
<span class="comment"># are easy and examples are run often. Use only one core not to offend CRAN</span>
<span class="comment"># checks</span>
<span class="symbol">f_SFO_SFO</span> <span class="assignement"><-</span> <span class="functioncall"><a href='mmkin.html'>mmkin</a></span><span class="keyword">(</span><span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/list'>list</a></span><span class="keyword">(</span><span class="string">"SFO-SFO"</span> <span class="argument">=</span> <span class="symbol">m_SFO_SFO</span><span class="keyword">)</span><span class="keyword">,</span>
<span class="symbol">d_SFO_SFO_err</span><span class="keyword">,</span> <span class="argument">cores</span> <span class="argument">=</span> <span class="number">1</span><span class="keyword">,</span>
<span class="argument">quiet</span> <span class="argument">=</span> <span class="number">TRUE</span><span class="keyword">,</span> <span class="argument">method.modFit</span> <span class="argument">=</span> <span class="string">"Marq"</span><span class="keyword">)</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span><span class="keyword">(</span><span class="symbol">f_SFO_SFO</span><span class="keyword">)</span></div>
<p><img src='add_err-4.png' alt='' width='540' height='400' /></p>
<div class='input'>
<span class="comment"># We would like to inspect the fit for dataset 3 more closely</span>
<span class="comment"># Using double brackets makes the returned object an mkinfit object</span>
<span class="comment"># instead of a list of mkinfit objects, so plot.mkinfit is used</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span><span class="keyword">(</span><span class="symbol">f_SFO_SFO</span><span class="keyword">[[</span><span class="number">3</span><span class="keyword">]</span><span class="keyword">]</span><span class="keyword">,</span> <span class="argument">show_residuals</span> <span class="argument">=</span> <span class="number">TRUE</span><span class="keyword">)</span></div>
<p><img src='add_err-6.png' alt='' width='540' height='400' /></p>
<div class='input'>
<span class="comment"># If we use single brackets, we should give two indices (model and dataset),</span>
<span class="comment"># and plot.mmkin is used</span>
<span class="functioncall"><a href='http://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span><span class="keyword">(</span><span class="symbol">f_SFO_SFO</span><span class="keyword">[</span><span class="number">1</span><span class="keyword">,</span> <span class="number">3</span><span class="keyword">]</span><span class="keyword">)</span></div>
<p><img src='add_err-8.png' alt='' width='540' height='400' /></p>
<div class='input'></div></pre>
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<h2>Author</h2>
Johannes Ranke
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