On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac <alan.isaac@gmail.com> wrote:
On 10/14/2011 1:42 PM, josef.pktd@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity, but handling of the starting values is a bit difficult.
Hmm. Yes. AR(1) is trivial, but how do you handle higher orders?
I would have to look for it. You can invert the stationary part of the AR polynomial with the numpy polynomial classes using division. The main thing is to pad with enough zeros corresponding to the truncation that you want. And in the old classes to watch out because the order is reversed high to low instead of low to high or the other way around. I switched to using mostly lfilter, but I guess the statsmodels sandbox (and the mailing list) still has my "playing with ARMA polynomials" code. (I think it might be pretty useful for teaching. I wished I had the functions to calculate some examples when I learned this.) Josef
Thanks, Alan
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