% error: [a, v, k] = aryule (x, p) % % fits an AR (p)-model with Yule-Walker estimates. % x = data vector to estimate % a: AR coefficients % v: variance of white noise % k: reflection coeffients for use in lattice filter % % The power spectrum of the resulting filter can be plotted with % pyulear(x, p), or you can plot it directly with ar_psd(a,v,...). % % See also: % pyulear, power, freqz, impz -- for observing characteristics of the model % arburg -- for alternative spectral estimators % % Example: Use example from arburg, but substitute aryule for arburg. % % Note: Orphanidis '85 claims lattice filters are more tolerant of % truncation errors, which is why you might want to use them. However, % lacking a lattice filter processor, I haven't tested that the lattice % filter coefficients are reasonable.