[Numpy-discussion] simulate AR

[Fabrice Silva]

Le vendredi 14 octobre 2011 à 10:49 -0400, josef.pktd at gmail.com a
écrit :
> On Fri, Oct 14, 2011 at 10:24 AM, Alan G Isaac <alan.isaac at gmail.com> 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