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- <title>Description of gcv</title>
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- <h1>gcv
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- <h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
- <div class="box"><strong></strong></div>
- <h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
- <div class="box"><strong>function g=gcv(varargin) </strong></div>
- <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
- <div class="fragment"><pre class="comment"></pre></div>
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- <h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
- This function calls:
- <ul style="list-style-image:url(../../../matlabicon.gif)">
- <li><a href="locfit.html" class="code" title="function fit=locfit(varargin)">locfit</a> Smoothing noisy data using Local Regression and Likelihood.</li><li><a href="rsum.html" class="code" title="function z = rsum(fit)">rsum</a> </li></ul>
- This function is called by:
- <ul style="list-style-image:url(../../../matlabicon.gif)">
- <li><a href="gcvplot.html" class="code" title="function g=gcvplot(alpha,varargin)">gcvplot</a> </li></ul>
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- <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
- <div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function g=gcv(varargin)</a>
- 0002
- 0003 fit = <a href="locfit.html" class="code" title="function fit=locfit(varargin)">locfit</a>(varargin{:});
- 0004 rs = <a href="rsum.html" class="code" title="function z = rsum(fit)">rsum</a>(fit);
- 0005
- 0006 df0 = rs(1);
- 0007 df1 = rs(2);
- 0008 llk = rs(3);
- 0009 n = size(fit.data.x,1);
- 0010 gc = -2*n*llk/((n-df0)^2);
- 0011 g = [llk df0 df1 gc];
- 0012
- 0013 <span class="keyword">return</span>;</pre></div>
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