Le vendredi 14 octobre 2011 à 10:49 -0400, [email protected] a écrit : > 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.
About speed comparison between lfilter, convolve, etc... http://www.scipy.org/Cookbook/ApplyFIRFilter -- Fabrice Silva _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
