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<title>Calculate the minimum error to assume in order to pass the variance test — mkinerrmin • mkin</title>
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<h1>Calculate the minimum error to assume in order to pass the variance test</h1>
</div>
<p>This function finds the smallest relative error still resulting in passing the
chi-squared test as defined in the FOCUS kinetics report from 2006.</p>
<pre class="usage"><span class='fu'>mkinerrmin</span>(<span class='no'>fit</span>, <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='fl'>0.05</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>fit</th>
<td><p>an object of class <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td>
</tr>
<tr>
<th>alpha</th>
<td><p>The confidence level chosen for the chi-squared test.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A dataframe with the following components:</p>
<dt>err.min</dt><dd><p>The relative error, expressed as a fraction.</p></dd>
<dt>n.optim</dt><dd><p>The number of optimised parameters attributed to the data series.</p></dd>
<dt>df</dt><dd><p>The number of remaining degrees of freedom for the chi2 error level
calculations. Note that mean values are used for the chi2 statistic and
therefore every time point with observed values in the series only counts
one time.</p></dd>
The dataframe has one row for the total dataset and one further row for
each observed state variable in the model.
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>This function is used internally by <code><a href='summary.mkinfit.html'>summary.mkinfit</a></code>.</p>
<h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
<p>FOCUS (2006) “Guidance Document on Estimating Persistence and
Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
Registration” Report of the FOCUS Work Group on Degradation Kinetics,
EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
<a href='http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics'>http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a></p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='no'>SFO_SFO</span> <span class='kw'>=</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"m1"</span>),
<span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></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 co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
<span class='no'>fit_FOCUS_D</span> <span class='kw'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='fu'>round</span>(<span class='fu'>mkinerrmin</span>(<span class='no'>fit_FOCUS_D</span>), <span class='fl'>4</span>)</div><div class='output co'>#> err.min n.optim df
#> All data 0.0640 4 15
#> parent 0.0646 2 7
#> m1 0.0469 2 8</div><div class='input'><span class='no'>fit_FOCUS_E</span> <span class='kw'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_E</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='fu'>round</span>(<span class='fu'>mkinerrmin</span>(<span class='no'>fit_FOCUS_E</span>), <span class='fl'>4</span>)</div><div class='output co'>#> err.min n.optim df
#> All data 0.1544 4 13
#> parent 0.1659 2 7
#> m1 0.1095 2 6</div></pre>
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<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
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<li><a href="#examples">Examples</a></li>
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