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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"><html><head> <title>Description of covm</title> <meta name="keywords" content="covm"> <meta name="description" content="COVM generates covariance matrix"> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1"> <meta name="generator" content="m2html © 2003 Guillaume Flandin"> <meta name="robots" content="index, follow"> <link type="text/css" rel="stylesheet" href="../m2html.css"></head><body><a name="_top"></a><div><a href="../index.html">Home</a> > <a href="index.html">tsa</a> > covm.m</div><!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png"> Master index</a></td><td align="right"><a href="index.html">Index for tsa <img alt=">" border="0" src="../right.png"></a></td></tr></table>--><h1>covm</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>COVM generates covariance matrix</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 [CC,NN] = covm(X,Y,Mode); </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"> COVM generates covariance matrix X and Y can contain missing values encoded with NaN. NaN's are skipped, NaN do not result in a NaN output. The output gives NaN only if there are insufficient input data COVM(X,Mode); calculates the (auto-)correlation matrix of X COVM(X,Y,Mode); calculates the crosscorrelation between X and Y Mode = 'M' minimum or standard mode [default] C = X'*X; or X'*Y correlation matrix Mode = 'E' extended mode C = [1 X]'*[1 X]; % l is a matching column of 1's C is additive, i.e. it can be applied to subsequent blocks and summed up afterwards the mean (or sum) is stored on the 1st row and column of C Mode = 'D' or 'D0' detrended mode the mean of X (and Y) is removed. If combined with extended mode (Mode='DE'), the mean (or sum) is stored in the 1st row and column of C. The default scaling is factor (N-1). Mode = 'D1' is the same as 'D' but uses N for scaling. C = covm(...); C is the scaled by N in Mode M and by (N-1) in mode D. [C,N] = covm(...); C is not scaled, provides the scaling factor N C./N gives the scaled version.</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="sumskipnan.html" class="code" title="function [o,count,SSQ,S4M] = sumskipnan(i,DIM)">sumskipnan</a> SUMSKIPNAN adds all non-NaN values.</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="mvar.html" class="code" title="function [ARF,RCF,PE,DC,varargout] = mvar(Y, Pmax, Mode);">mvar</a> Estimates Multi-Variate AutoRegressive model parameters</li></ul><!-- crossreference --><hr><address>Generated on Tue 17-Aug-2004 00:13:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/">m2html</a></strong> © 2003</address></body></html>⌨️ 快捷键说明
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