From: Anthony Mathelier <anthony.mathelier_at_gmail.com>

Date: Mon, 16 Jun 2008 15:33:18 +0200

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 Mon 16 Jun 2008 - 14:32:48 GMT

Date: Mon, 16 Jun 2008 15:33:18 +0200

On Tue, Jun 10, 2008 at 6:13 PM, stephen sefick <ssefick_at_gmail.com> wrote:

> 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
**>
**> Stephen
**>
**> 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
*

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