function [AR,RC,PE] = durlev(ACF); function [MX,PE] = durlev(ACF); estimates AR(p) model parameter by solving the Yule-Walker with the Durbin-Levinson recursion for multiple channels INPUT: ACF Autocorrelation function from lag=[0:p] OUTPUT AR autoregressive model parameter RC reflection coefficients (= -PARCOR coefficients) PE remaining error variance MX transformation matrix between ARP and RC (Attention: needs O(p^2) memory) AR(:,K) = MX(:,K*(K-1)/2+(1:K)); RC(:,K) = MX(:,(1:K).*(2:K+1)/2); All input and output parameters are organized in rows, one row corresponds to the parameters of one channel see also ACOVF ACORF AR2RC RC2AR LATTICE REFERENCES: Levinson N. (1947) "The Wiener RMS(root-mean-square) error criterion in filter design and prediction." J. Math. Phys., 25, pp.261-278. Durbin J. (1960) "The fitting of time series models." Rev. Int. Stat. Inst. vol 28., pp 233-244. P.J. Brockwell and R. A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991. S. Haykin "Adaptive Filter Theory" 3rd ed. Prentice Hall, 1996. M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981. W.S. Wei "Time Series Analysis" Addison Wesley, 1990.
Package: tsa