This is a pretty vague request ... can we have a little bit more
background? There might be something in a package somewhere, but you will
probably have to "roll your own" (that's quite typical in R). I
would
suggest something like: (1) loading the ts (time series) library, (2)
using spectrum() to compute the power series of your data, (3) some large
number of times, using sample() to permute your data and recomputing the
power series of your data (save the values of spectrum()$spec in a
matrix), (4) using apply and the quantile function to come up with
pointwise 95% confidence limits.
There may well be more expert opinions out there; if you're lucky
someone has already done this for themselves and will contribute code.
(I would have suggested the help.search() command, but I tried
help.search("white") [and help(package=ts)] and didn't see
anything
useful.)
cheers,
Ben Bolker
On Wed, 4 Sep 2002, S. Sijikumar wrote:
> Dear Sir,
>
> Please tell me how to perform monte-carlo white noise test using R.
>
> Thanking you
>
> with regards
>
> S.Sijikumar
>
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318 Carr Hall bolker at zoo.ufl.edu
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