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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 acorf</title> <meta name="keywords" content="acorf"> <meta name="description" content="Calculates autocorrelations for multiple data series."> <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> > acorf.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>acorf</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>Calculates autocorrelations for multiple data series.</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 [AUTOCOV,stderr,lpq,qpval] = acorf(Z,N); </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"> Calculates autocorrelations for multiple data series.
Missing values in Z (NaN) are considered.
Also calculates Ljung-Box Q stats and p-values.
[AutoCorr,stderr,lpq,qpval] = acorf(Z,N);
If mean should be removed use
[AutoCorr,stderr,lpq,qpval] = acorf(detrend(Z',0)',N);
If trend should be removed use
[AutoCorr,stderr,lpq,qpval] = acorf(detrend(Z')',N);
INPUT
Z is data series for which autocorrelations are required
each in a row
N maximum lag
OUTPUT
AutoCorr nr x N matrix of autocorrelations
stderr nr x N matrix of (approx) std errors
lpq nr x M matrix of Ljung-Box Q stats
qpval nr x N matrix of p-values on Q stats
All input and output parameters are organized in rows, one row
corresponds to one series
REFERENCES:
S. Haykin "Adaptive Filter Theory" 3ed. Prentice Hall, 1996.
M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981.
W.S. Wei "Time Series Analysis" Addison Wesley, 1990.
J.S. Bendat and A.G.Persol "Random Data: Analysis and Measurement procedures", Wiley, 1986.</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="acovf.html" class="code" title="function [ACF,NN] = acovf(Z,KMAX,Mode,Mode2);">acovf</a> ACOVF estimates autocovariance function (not normalized)</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"></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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