Re: [R] Inverse transform after applying function in frequency domain?

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Sat, 19 Apr 2008 14:06:45 +0100 (BST)

spec.pgram() does not just transform to frquency domain: for a single series it then takes the squared amplitude. You cannot undo that. Try applying (the square root of?) your function to the Fourier fransform instead.

Study of the references on ?spec.pgram is recommended, or a discussion with your Statistics supervisor about the underlying theory.

On Sat, 19 Apr 2008, Keith Alan Chamberlain wrote:

> Dear R-Help,
>
> I wish to simulate a process so that it has certain properties in the
> frequency domain. What I attempted was to generate a random time-series
> signal, use spec-pgram(), apply a function in the frequency domain, and then
> inverse transform back to the time-domain. This idea does not seem as
> straight forward in practice as I anticipated.
>
> e.g.
> x<-ts(rnorm(1000, 0,1), frequency=256)
> plot(x) ## looks like noise.
> pgm<-spec.pgram(x, taper=0) ## a flat spectra, white noise
> fx<-pgm$freq^(-1)+pgm$spec ## apply a function
> plot(log(fx)~log(pgm$freq)) ## scaling properties
> x2<-fft(fx, inverse=T)
> plot(Re(x2)) ## not quite what I intended
>
> . Which, although I get some fantastic looking plots, isn't quite what I
> anticipated. How do I apply a function or filter in the frequency domain,
> then inverse transform to the scale of my original time series?
>
> Sincerely,
> KeithC.
> Psych Undergrad, CU Boulder
> RE McNair Scholar [U.S]
>
>
> [[alternative HTML version deleted]]
>
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>

-- 
Brian D. Ripley,                  ripley_at_stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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Received on Sat 19 Apr 2008 - 13:13:19 GMT

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