usage:  [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.