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  <title>Description of locfit_all</title>
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  <meta name="description" content="Smoothing noisy data using Local Regression and Likelihood.">
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<!-- ../../menu.html chronux_2_10 --><!-- # locfit --><!-- menu.html m -->
<h1>locfit_all
</h1>

<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
<div class="box"><strong>Smoothing noisy data using Local Regression and Likelihood.</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 out=locfit_all(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"> Smoothing noisy data using Local Regression and Likelihood.

 This is a combination of the locfit and predict functions</pre></div>

<!-- crossreference -->
<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="predict.html" class="code" title="function [y, se] = predict(varargin)">predict</a>	Interpolate a fit produced by locfit().</li></ul>
This function is called by:
<ul style="list-style-image:url(../../../matlabicon.gif)">
</ul>
<!-- crossreference -->


<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 out=locfit_all(varargin)</a>
0002 
0003 <span class="comment">% Smoothing noisy data using Local Regression and Likelihood.</span>
0004 <span class="comment">%</span>
0005 <span class="comment">% This is a combination of the locfit and predict functions</span>
0006 <span class="comment">%</span>
0007 
0008 <span class="comment">% Minimal input validation</span>
0009 <span class="keyword">if</span> nargin &lt; 1
0010    error( <span class="string">'At least one input argument required'</span> );
0011 <span class="keyword">end</span>
0012 
0013 predict_args = {};
0014 
0015 locfit_args = varargin{1};
0016 
0017 <span class="keyword">if</span> nargin==2
0018 predict_args = varargin{2};
0019 <span class="keyword">end</span>;
0020 
0021 fit = <a href="locfit.html" class="code" title="function fit=locfit(varargin)">locfit</a>( locfit_args{:} );
0022 
0023 predict_out = <a href="predict.html" class="code" title="function [y, se] = predict(varargin)">predict</a>( fit, predict_args{:} );
0024 
0025 out = {fit predict_out};</pre></div>
<hr><address>Generated on Fri 12-Aug-2011 11:36:15 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" target="_parent">m2html</a></strong> &copy; 2005</address>
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