On 26-Feb-09 13:54:51, David Winsemius wrote:
> I saw Gabor's reply but have a clarification to request. You say you
> want to remove low frequency components but then you request smoothing
> functions. The term "smoothing" implies removal of high-frequency
> components of a series.
If you produce a smoothed series, your result of course contains
the low-frequency comsponents, with the high-frequency components
removed.
But if you then subtract that from the original series, your result
contains the high-frequency components, with the low-frequency
compinents removed.
Moving-average is one way of smoothing (but can introduce periodic
components which were not there to start with).
Filtering a time-series is a very open-ended activity! In many
cases a useful start is exploration of the spectral properties
of the series, for which R has several functions. 'spectrum()'
in the stats package (loaded bvy default) is one basic function.
help.search("time series") will throw up a lot of functions.
You might want to look at package 'ltsa' (linear time series
analysis).
Alternatively, if yuou already have good information about the
frequency-structure of the series, or (for instance) know that
it has a will-defined seasonal component, then you could embark
on designing a transfer function specifically tuned to the job.
Have a look at RSiteSearch("{transfer function}")
Hoping this helps,
Ted.
> If smoothing really is your goal then additional R resource would be
> smooth.spline, loess (or lowess), ksmooth, or using smoothing terms in
> regressions. Venables and Ripley have quite a few worked examples of
> such in MASS.
>
> --
> David Winsemius
>
>
> On Feb 26, 2009, at 7:07 AM, <mau...@alice.it> wrote:
>
>> I am looking for some help at removing low-frequency components from
>> a signal, through Moving Average on a sliding window.
>> I understand thiis is a smoothing procedure that I never done in my
>> life before .. sigh.
>>
>> I searched R archives and found "rollmean", "MovingAverages {TTR}",
>> "SymmetricMA".
>> None of the above mantioned functions seems to accept the smoothing
>> polynomial order and the sliding window with as input parameters.
>> Maybe I am missing something.
>>
>> I wonder whether there is some building blocks in R if not even a
>> function which does it all (I do not expect that much,though).
>> Even some literature references and/or tutorials are very welcome.
>>
>> Thank you so much,
>> Maura
>>
>>
>>
>> tutti i telefonini TIM!
>>
>>
>> [[alternative HTML version deleted]]
>>
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>
> ______________________________________________
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Date: 26-Feb-09 Time: 14:54:43
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