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<p>This function uses <code>optimize</code> in order to iteratively find the
smallest relative error still resulting in passing the chi-squared test
as defined in the FOCUS kinetics report from 2006.</p>
<pre><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>Arguments</h2>
<dl class="dl-horizontal">
<dt>fit</dt>
<dd>
an object of class <code>mkinfit</code>.
</dd>
<dt>alpha</dt>
<dd>
The confidence level chosen for the chi-squared test.
</dd>
</dl>
<div class="Value">
<h2>Value</h2>
<p>A dataframe with the following components:</p>
<p>The dataframe has one row for the total dataset and one further row for
each observed state variable in the model.</p>
</div>
<div class="Details">
<h2>Details</h2>
<p>This function is used internally by <code>summary.mkinfit</code>.</p>
</div>
<div class="References">
<h2>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://focus.jrc.ec.europa.eu/dk'>http://focus.jrc.ec.europa.eu/dk</a></p>
</div>
<h2 id="examples">Examples</h2>
<pre class="examples"><div class='input'><span class='no'>SFO_SFO</span> <span class='kw'>=</span> <span class='fu'>mkinmod</span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</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'>list</span>(<span class='kw'>type</span> <span class='kw'>=</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='no'>fit_FOCUS_D</span> <span class='kw'>=</span> <span class='fu'>mkinfit</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'>mkinfit</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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