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<title>Calculate the AIC for a column of an mmkin object — AIC.mmkin • mkin</title>


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    <h1>Calculate the AIC for a column of an mmkin object</h1>
    
    <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='no'>object</span>, <span class='no'>...</span>, <span class='kw'>k</span> <span class='kw'>=</span> <span class='fl'>2</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='no'>object</span>, <span class='no'>...</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="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'>
   <span class='co'># skip, as it takes &gt; 10 s on winbuilder</span>
  <span class='no'>f</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span>),
    <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='st'>"FOCUS A"</span> <span class='kw'>=</span> <span class='no'>FOCUS_2006_A</span>,
         <span class='st'>"FOCUS C"</span> <span class='kw'>=</span> <span class='no'>FOCUS_2006_C</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>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Optimisation did not converge:</span>
#&gt; <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='no'>f</span>[<span class='st'>"SFO"</span>, <span class='st'>"FOCUS A"</span>]) <span class='co'># We get a single number for a single fit</span></div><div class='output co'>#&gt; [1] 55.28197</div><div class='input'>  <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span>(<span class='no'>f</span><span class='kw'>[[</span><span class='st'>"SFO"</span>, <span class='st'>"FOCUS A"</span>]]) <span class='co'># or when extracting an mkinfit object</span></div><div class='output co'>#&gt; [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='no'>f</span>[, <span class='st'>"FOCUS A"</span>])</div><div class='output co'>#&gt;      df      AIC
#&gt; SFO   3 55.28197
#&gt; FOMC  4 57.28202
#&gt; 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='no'>f</span>[, <span class='st'>"FOCUS A"</span>], <span class='kw'>k</span> <span class='kw'>=</span> <span class='fl'>0</span>) <span class='co'># If we do not penalize additional parameters, we get nearly the same</span></div><div class='output co'>#&gt;      df      AIC
#&gt; SFO   3 49.28197
#&gt; FOMC  4 49.28202
#&gt; 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='no'>f</span>[, <span class='st'>"FOCUS A"</span>])        <span class='co'># Comparing the BIC gives a very similar picture</span></div><div class='output co'>#&gt;      df      BIC
#&gt; SFO   3 55.52030
#&gt; FOMC  4 57.59979
#&gt; 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='no'>f</span>[, <span class='st'>"FOCUS C"</span>])</div><div class='output co'>#&gt;      df      AIC
#&gt; SFO   3 59.29336
#&gt; FOMC  4 44.68652
#&gt; 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='no'>f</span>[, <span class='st'>"FOCUS C"</span>])</div><div class='output co'>#&gt;      df      BIC
#&gt; SFO   3 59.88504
#&gt; FOMC  4 45.47542
#&gt; DFOP  5 30.00984</div><div class='input'>  

</div></pre>
  </div>
  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
    <h2>Contents</h2>
    <ul class="nav nav-pills nav-stacked">
      <li><a href="#arguments">Arguments</a></li>
      <li><a href="#value">Value</a></li>
      <li><a href="#examples">Examples</a></li>
    </ul>

    <h2>Author</h2>
    <p>Johannes Ranke</p>
  </div>
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