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<h1>Calculate Akaike weights for model averaging</h1>
<div class="hidden name"><code>aw.Rd</code></div>
</div>
<div class="ref-description">
<p>Akaike weights are calculated based on the relative
expected Kullback-Leibler information as specified
by Burnham and Anderson (2004).</p>
</div>
<pre class="usage"><span class='fu'>aw</span>(<span class='no'>object</span>, <span class='no'>...</span>)
<span class='co'># S3 method for mkinfit</span>
<span class='fu'>aw</span>(<span class='no'>object</span>, <span class='no'>...</span>)
<span class='co'># S3 method for mmkin</span>
<span class='fu'>aw</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 mmkin column object, containing two or more
<code><a href='mkinfit.html'>mkinfit</a></code> models that have been fitted to the same data,
or an mkinfit object. In the latter case, further mkinfit
objects fitted to the same data should be specified
as dots arguments.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>Not used in the method for mmkin column objects,
further mkinfit objects in the method for mkinfit objects.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
<p>Burnham KP and Anderson DR (2004) Multimodel
Inference: Understanding AIC and BIC in Model Selection
Sociological Methods & Research 33(2) 261-304</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># \dontrun{</span>
<span class='no'>f_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='st'>"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='no'>f_dfop</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='st'>"DFOP"</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>aw_sfo_dfop</span> <span class='kw'><-</span> <span class='fu'>aw</span>(<span class='no'>f_sfo</span>, <span class='no'>f_dfop</span>)
<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>aw_sfo_dfop</span>)</div><div class='output co'>#> [1] 1</div><div class='input'><span class='no'>aw_sfo_dfop</span> <span class='co'># SFO gets more weight as it has less parameters and a similar fit</span></div><div class='output co'>#> [1] 0.5970258 0.4029742</div><div class='input'><span class='no'>f</span> <span class='kw'><-</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 D"</span> <span class='kw'>=</span> <span class='no'>FOCUS_2006_D</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>)
<span class='fu'>aw</span>(<span class='no'>f</span>)</div><div class='output co'>#> [1] 0.4808722 0.1945539 0.3245740</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='fu'>aw</span>(<span class='no'>f</span>))</div><div class='output co'>#> [1] 1</div><div class='input'><span class='fu'>aw</span>(<span class='no'>f</span>[<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"DFOP"</span>)])</div><div class='output co'>#> [1] 0.5970258 0.4029742</div><div class='input'># }
</div></pre>
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