本代码计算给定序列的自相关函数ACF。
Computes ACF for a given series.
根据滞后量p返回自相关输出向量。
Returns a vector of autocorrelations through lag p.
还可以生成自相关的条形图,其中拒绝域用于测试(在白噪声假设下)每个自相关等于0。
Also produces bar graph of autocorrelations, with rejection region bands for testing (under white noise assumption) each autocorrelation = 0.
源代码:
function ta = acf(y,p)
% ACF - Compute Autocorrelations Through p Lags
% >> myacf = acf(y,p)
%
% Inputs:
% y - series to compute acf for, nx1 column vector
% p - total number of lags, 1x1 integer
%
% Output:
% myacf - px1 vector containing autocorrelations
% (First lag computed is lag 1. Lag 0 not computed)
%
%
% A bar graph of the autocorrelations is also produced, with
% rejection region bands for testing individual autocorrelations = 0.
%
% Note that lag 0 autocorelation is not computed,
% and is not shown on this graph.
%
% Example:
% >> acf(randn(100,1), 10)
%
% --------------------------
% USER INPUT CHECKS
% --------------------------
[n1, n2] = size(y) ;
if n2 ~=1
error('Input series y must be an nx1 column vector')
end
[a1, a2] = size§ ;
if ~((a11 & a21) & (p end % ------------- % BEGIN CODE % ------------- ta = zeros(p,1) ; global N N = max(size(y)) ; global ybar ybar = mean(y); % Collect ACFs at each lag i for i = 1:p ta(i) = acf_k(y,i) ; end % Plot ACF % Plot rejection region lines for test of individual autocorrelations % H_0: rho(tau) = 0 at alpha=.05 bar(ta) line([0 p+.5], (1.96)*(1/sqrt(N))*ones(1,2)) line([0 p+.5], (-1.96)*(1/sqrt(N))*ones(1,2)) % Some figure properties line_hi = (1.96)*(1/sqrt(N))+.05; line_lo = -(1.96)*(1/sqrt(N))-.05; bar_hi = max(ta)+.05 ; bar_lo = -max(ta)-.05 ; if (abs(line_hi) > abs(bar_hi)) % if rejection lines might not appear on graph else end title({’ ‘,‘Sample Autocorrelations’,’ '}) xlabel(‘Lag Length’) set(gca,‘YTick’,[-1:.20:1]) % set number of lag labels shown if (p<28 & p>4) elseif (p>=28) end set(gca,‘TickLength’,[0 0]) % --------------- % SUB FUNCTION % --------------- function ta2 = acf_k(y,k) % ACF_K - Autocorrelation at Lag k % acf(y,k) % % Inputs: % y - series to compute acf for % k - which lag to compute acf % global ybar global N cross_sum = zeros(N-k,1) ; % Numerator, unscaled covariance for i = (k+1):N end % Denominator, unscaled variance yvar = (y-ybar)’*(y-ybar) ; ta2 = sum(cross_sum) / yvar ; 源码下载地址: http://page2.dfpan.com/fs/8lcje221e291c679df8/error('Input number of lags p must be a 1x1 scalar, and must be less than length of series y')
axis([0 p+.60 line_lo line_hi])
axis([0 p+.60 bar_lo bar_hi])
set(gca,'XTick',floor(linspace(1,p,4)))
set(gca,'XTick',floor(linspace(1,p,8)))
cross_sum(i) = (y(i)-ybar)*(y(i-k)-ybar) ;