?? acorf.m
字號:
function [AUTOCOV,stderr,lpq,qpval] = acorf(Z,N);
% 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.
% Version 2.99a Date: 13 Jul 2002
% Copyright (c) 1998-2002 by Alois Schloegl <a.schloegl@ieee.org>
% calculating lpq, stderr, qpval from
% suggested by Philip Gray, University of New South Wales,
% This library is free software; you can redistribute it and/or
% modify it under the terms of the GNU Library General Public
% License as published by the Free Software Foundation; either
% version 2 of the License, or (at your option) any later version.
%
% This library is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
% Library General Public License for more details.
%
% You should have received a copy of the GNU Library General Public
% License along with this library; if not, write to the
% Free Software Foundation, Inc., 59 Temple Place - Suite 330,
% Boston, MA 02111-1307, USA.
[nr,nc] = size(Z);
NC = sum(~isnan(Z),2); % missing values
AUTOCOV = acovf(Z,N);
AUTOCOV = AUTOCOV(:,2:N+1) ./ AUTOCOV(:,ones(1,N));
if nargout > 1
stderr = sqrt(1./NC)*ones(1,N);
lpq = zeros(nr,N);
qpval = zeros(nr,N);
cum=zeros(nr,1);
for k=1:N,
cum = cum+AUTOCOV(:,k).*conj(AUTOCOV(:,k))./(NC-k);
lpq(:,k) = NC.*(NC+2).*cum; % Ljung box Q for k lags
%qpval(:,k) = 1 - chi2cdf(lpq(:,k),k); % p-value of Q stat
qpval(:,k) = 1 - gammainc(lpq(:,k)/2,k/2); % replace chi2cdf by gammainc
end;
end;
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