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]
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