biacovf.m

MATLAB的时间序列分析相关函数,涵盖对时间序列分析所需要所有重要函数

function [BIACF,ACF,M1] = biacovf(Z,N);
% BiAutoCovariance function 
% [BiACF] = biacovf(Z,N);
%
% Input:	Z    Signal
%		N  # of coefficients
% Output:	BIACF bi-autocorrelation function (joint cumulant 3rd order
% Output:	ACF   covariance function (joint cumulant 2nd order)

%       $Id: biacovf.m 5090 2008-06-05 08:12:04Z schloegl $
%	Copyright (C) 1997, 1998, 2008 by Alois Schloegl <[e-mail]>
%
%    This program is free software: you can redistribute it and/or modify
%    it under the terms of the GNU General Public License as published by
%    the Free Software Foundation, either version 3 of the License, or
%    (at your option) any later version.
%
%    This program 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 General Public License for more details.
%
%    You should have received a copy of the GNU General Public License
%    along with this program.  If not, see <http://www.gnu.org/licenses/>.

ACF=zeros(1,N+1);
BIACF=zeros(N+1,N+1);

Z=Z(:);
M=size(Z,1);

M1=sum(Z)/M;
Z=Z-M1*ones(size(Z));

for K=0:N, 
	tmp=Z(1:M-K).*Z(1+K:M);
	ACF(K+1)=sum(tmp)/M;
	for L = K:N,
		BIACF(K+1,L+1) = sum(tmp(1:M-L).*Z(1+L:M))/M;
	end;
end;

BIACF=BIACF+BIACF'-diag(diag(BIACF));