www.gusucode.com > 时间序列分析工具箱 - tsa源码程序 > tsa/pacf.m
function [PARCOR,sig,cil,ciu]= pacf(Z,KMAX); % Partial Autocorrelation function % [parcor,sig,cil,ciu] = pacf(Z,N); % % Input: % Z Signal, each row is analysed % N # of coefficients % Output: % parcor autocorrelation function % sig p-value for significance test % cil lower confidence interval % ciu upper confidence interval % % see also: DURLEV, LATTICE, AC2RC, AR2RC, % FLAG_IMPLICIT_SIGNIFICANCE % Version 2.99b Date: 24Sep 2002 % Copyright (C) 1997-2002 by Alois Schloegl <a.schloegl@ieee.org> % % 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); if nc<KMAX, warning('too less elements.\nmake sure the data is row order\n') end; [s,n] = sumskipnan(Z,2); Z = Z - repmat(s./n,1,nc); % remove mean if (nargin == 1), KMAX = N-1; end; AutoCov = acovf(Z,KMAX); [AR,PARCOR,PE] = durlev(AutoCov); % PARCOR are the reflection coefficients %[AR,PARCOR,PE] = lattice(Z,KMAX); % PARCOR are the reflection coefficients PARCOR = -PARCOR; % the partial correlation coefficients are the negative reflection coefficient. if nargout<2, return, end; % significance test s = 1./sqrt(repmat(n,1,KMAX)-1-ones(nr,1)*(1:KMAX)); sig = normcdf(PARCOR,0,s); sig = min(sig,1-sig); if nargout<3, return, end; % calculate confidence interval if exist('flag_implicit_significance')==2; alpha = flag_implicit_significance; else alpha = 0.05; end; fprintf(1,'PACF: confidence interval for alpha=%f\n', alpha); ciu = norminv(alpha/2).*s; cil = -ciu;