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<h1>Calculate the AIC for a column of an mmkin object</h1>
<small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/AIC.mmkin.R'><code>R/AIC.mmkin.R</code></a></small>
<div class="hidden name"><code>AIC.mmkin.Rd</code></div>
</div>
<div class="ref-description">
<p>Provides a convenient way to compare different kinetic models fitted to the
same dataset.</p>
</div>
<pre class="usage"><span class='co'># S3 method for mmkin</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span>, k <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span>
<span class='co'># S3 method for mmkin</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>BIC</a></span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</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>object</th>
<td><p>An object of class <code><a href='mmkin.html'>mmkin</a></code>, containing only one
column.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>For compatibility with the generic method</p></td>
</tr>
<tr>
<th>k</th>
<td><p>As in the generic method</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>As in the generic method (a numeric value for single fits, or a
dataframe if there are several fits in the column).</p>
<h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
<p>Johannes Ranke</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'>
<span class='co'># skip, as it takes > 10 s on winbuilder</span>
<span class='va'>f</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>,
<span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"FOCUS A"</span> <span class='op'>=</span> <span class='va'>FOCUS_2006_A</span>,
<span class='st'>"FOCUS C"</span> <span class='op'>=</span> <span class='va'>FOCUS_2006_C</span><span class='op'>)</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
</div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span>
#> <span class='warning'>false convergence (8)</span></div><div class='input'> <span class='co'># We get a warning because the FOMC model does not converge for the</span>
<span class='co'># FOCUS A dataset, as it is well described by SFO</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># We get a single number for a single fit</span>
</div><div class='output co'>#> [1] 55.28197</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[[</span><span class='st'>"SFO"</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># or when extracting an mkinfit object</span>
</div><div class='output co'>#> [1] 55.28197</div><div class='input'>
<span class='co'># For FOCUS A, the models fit almost equally well, so the higher the number</span>
<span class='co'># of parameters, the higher (worse) the AIC</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#> df AIC
#> SFO 3 55.28197
#> FOMC 4 57.28211
#> DFOP 5 59.28197</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span>, k <span class='op'>=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='co'># If we do not penalize additional parameters, we get nearly the same</span>
</div><div class='output co'>#> df AIC
#> SFO 3 49.28197
#> FOMC 4 49.28211
#> DFOP 5 49.28197</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>BIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS A"</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># Comparing the BIC gives a very similar picture</span>
</div><div class='output co'>#> df BIC
#> SFO 3 55.52030
#> FOMC 4 57.59987
#> DFOP 5 59.67918</div><div class='input'>
<span class='co'># For FOCUS C, the more complex models fit better</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS C"</span><span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#> df AIC
#> SFO 3 59.29336
#> FOMC 4 44.68652
#> DFOP 5 29.02372</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>BIC</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span>, <span class='st'>"FOCUS C"</span><span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#> df BIC
#> SFO 3 59.88504
#> FOMC 4 45.47542
#> DFOP 5 30.00984</div><div class='input'>
</div></pre>
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