From: stephen sefick <ssefick_at_gmail.com>

Date: Tue, 10 Jun 2008 12:13:25 -0400

Date: Tue, 10 Jun 2008 12:13:25 -0400

I from a first thought I would say that you are apply this wrong! The
fourier transform convolves a function (cos(x)+isin(x) (this may not be the
exact formula but I don't have my books near)) to the data and then
integrates over -1/2 to 1/2 takes the modulus and plots this- the
periodogram. The reason you preform a fourier transform is to look at
recurring frequencies in the data, which are in the time domain. The
fourier transform converts the time series into the frequency domain and
viola you have a peak into the hidden/recurring parts of your signal. From
your explaination your are applying this technique wrong- look at schumway,
MASS4, et al. books to get a handle on how this technique is used. If you
are to apply a time series analysis please use it on a time series. Maybe
your logic is not flawed but I don't see how a histogram with its associated
binning is a better candidate for time series analysis than the original
time series if at all.

good luck

On Tue, Jun 10, 2008 at 8:49 AM, Matthieu Stigler < Matthieu.Stigler_at_gmail.com> wrote:

> Hello

*>
**> I don't know exactly what you want to do but:
**>
**> -why do you use in your example h$counts and not h? Furthermore helpl file
**> says it should be a time series, why then rather not your time series?
**>
**> -usually na.action will make the "default" action, which you can see by
**> getOptions("na.action")
**>
**> -here in this function it is provided in the function values na.action =
**> na.fail so it will just remove the NA in the time series
**>
**> -if you want to study a function, I advise you to copy it entirely, rename
**> it and then just insert print(curiousobject...) in the function, this will
**> allow you to let the function run and grasp the interessting objects, like:
**>
**> study<-function (x, spans = NULL, kernel = NULL, taper = 0.1, pad = 0,
**> fast = TRUE, demean = FALSE, detrend = TRUE, plot = TRUE,
**> na.action = na.fail, ...)
**> {
**> series <- deparse(substitute(x))
**> x <- na.action(as.ts(x))
**> print(x)
**> xfreq <- frequency(x)
**> ...}
**> study(sunspots)
**>
**> -when you provide an example, instead of giving an external reference for
**> the data, try to search a convenient internal data (accessed by data() ), so
**> one will be able to reproduce your problems. Here you could use sunspots
**>
**> -to obtain the commented code... I don't know it...
**>
**> -good luck
**>
**> Matthieu
**>
**>
**>
**>
**>
**> Hi everyone,
**>>
**>> first of all, I would like to say that I am a newbie in R, so I apologize
**>> in
**>> advance if my questions seem to be too easy for you.
**>>
**>> Well, I'm looking for periodicity in histograms. I have histograms of
**>> certain phenomenons and I'm asking whether a periodicity exists in these
**>> data. So, I make a periodogram with the function spec.pgram. For instance,
**>> if I have a histogram h, I call spec.pgram by spec.pgram (h, log="no",
**>> taper=0.5). So, I have some peaks that appear and I would like to
**>> interpret
**>> them but I do not know how they are computed and so what a peak with a
**>> value
**>> of 10000 represents in comparison with a peak of value 600 with another
**>> histogram.
**>> I looked at the source code of the function spec.pgram to better
**>> understand
**>> what is behind. But, when I apply the source code line by line, I've got a
**>> problem. For instance, I make:
**>>
**>>
**>>> >data = scan ("file.txt")
**>>> >h = hist (data, breaks=max(data)/5000)
**>>>
**>>>
**>> #then I apply the first two lines of the spec.pgram function
**>>
**>>
**>>> >series <- deparse(substitute(h$counts))
**>>> >x <- na.action(as.ts(h$counts))
**>>> >x
**>>>
**>>>
**>> NULL
**>> I do not understand why when I apply the first two lines of the function I
**>> have x which is equal to NULL (which make a mistake in the following lines
**>> of the code) but if I apply the function directly with h$counts it gives
**>> me
**>> a result.
**>> So, if someone can explain to me what is the problem and/or how spec.pgram
**>> exactly computes the periodogram and how to interpret it with my data, I
**>> would be so grateful.
**>> And subsidiary questions:
**>> - Is it possible to have the commented source code of the function?
**>> - I do not understand what is the function na.action in the second line of
**>> spec.pgram, so if you can explain it to me.
**>>
**>> Thanks in advance for your answers.
**>> Best regards,
**>>
**>> Anthony Mathelier
**>>
**>> [[alternative HTML version deleted]]
**>>
**>
**> ______________________________________________
**> R-help_at_r-project.org mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide
**> http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
**>
*

-- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis [[alternative HTML version deleted]] ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Tue 10 Jun 2008 - 16:26:01 GMT

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