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(The meta learners linearly combines
the coefficients from the base learners.)" />




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    <h1>Extract Coefficients</h1>
    <small class="dont-index">Source: <a href='https://github.com/rauschenberger/joinet/blob/master/R/functions.R'><code>R/functions.R</code></a></small>
    <div class="hidden name"><code>coef.joinet.Rd</code></div>
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    <div class="ref-description">
    <p>Extracts pooled coefficients.
(The meta learners linearly combines
the coefficients from the base learners.)</p>
    </div>

    <pre class="usage"><span class='co'># S3 method for joinet</span>
<span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</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><a href='joinet.html'>joinet</a> object</p></td>
    </tr>
    <tr>
      <th>...</th>
      <td><p>further arguments (not applicable)</p></td>
    </tr>
    </table>

    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>

    <p>This function returns the pooled coefficients.
The slot <code>alpha</code> contains the intercepts
in a vector of length \(q\),
and the slot <code>beta</code> contains the slopes
in a matrix with \(p\) rows (inputs) and \(q\) columns.</p>

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
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    <pre class="examples"><div class='input'><span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<span class='fl'>1</span>+<span class='fl'>1</span>
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
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<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>)
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<span class='no'>coef</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>object</span>)
}</div></pre>
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