On Fri, Oct 14, 2011 at 10:24 AM, Alan G Isaac <[email protected]> wrote: > As a simple example, if I have y0 and a white noise series e, > what is the best way to produces a series y such that y[t] = 0.9*y[t-1] + e[t] > for t=1,2,...? > > 1. How can I best simulate an autoregressive process using NumPy? > > 2. With SciPy, it looks like I could do this as > e[0] = y0 > signal.lfilter((1,),(1,-0.9),e) > Am I overlooking similar (or substitute) functionality in NumPy?
I don't think so. At least I didn't find anything in numpy for this. An MA process would be a convolution, but for simulating AR I only found signal.lfilter. (unless numpy has gained extra features that I don't have in 1.5) Except, I think it's possible to do it with fft, if you want to fft-inverse-convolve (?) But simulating an ARMA with fft was much slower than lfilter in my short experimentation with it. Josef > > Thanks, > Alan Isaac > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
