📄 arch.m
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function [archstat,pval] = arch(x,p) % PURPOSE: computes a test for ARCH(p) % -------------------------------------------------------- % USAGE: [archstat,pval] = arch(x,p) % where: x = a vector (usually regression residuals) % p = order(s) of ARCH to be tested (scalar or % row/column vector) % -------------------------------------------------------- % RETURNS: % archstat = ARCH(p) test statistic(s), distributed % Chi-squared(p) under H0 % pval = tail probabilit(ies) % -------------------------------------------------------- % REQUIRES: % cols(), rows(), mlag(), chis_cdf() from LeSage library % -------------------------------------------------------- % REFERENCES: % Engle, Robert (1982), "Autoregressive Conditional Heteroskedasticity with Estimates of % the Variance of United Kingdom Inflation", Econometrica, vol. 50, pp. 987-1007 % Ljung, G.M. & G.E.P. Box (1978), "On a Measure of Lack of Fit in Time Series Models", % Biometrika, vol. 65, no. 2, pp. 297-303 % McLeod, A.I. & W.K. Li (1983), "Diagnostic Checking ARMA Time Series Models Using % Squared-Residual Autocorrelations", Journal of Time Series Analysis, vol. 4, no. 4, % pp. 269-273 %-------------------------------------------------------- % written by: % Kit Baum % Dept of Economics % Boston College % Chestnut Hill MA 02467 USA % baum@bc.edu % 9601 rev 9607 if (nargin ~= 2) error('Wrong number of arguments to arch'); end; [n1 n2] = size(p); if n1 > n2 p = p'; end; c = cols(p); n = rows(x); x2 = x .* x; for i=1:c; lx2 = mlag(x2,p(i)); lx2(1:p(i),:)=[]; lxx = [ones(n-p(i),1) lx2]; olsr = ols(x2(p(i)+1:n),lxx); archstat(i) = (n-p(i))*olsr.rsqr; pval(i) = 1-chis_cdf(archstat(i),p(i)); end; % end of function
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