R help - Feb 2009 - Moving Average

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]]

See rollapply in zoo or filter or embed in the core of R.

On Thu, Feb 26, 2009 at 7:07 AM,  <mauede at 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]]
>
> ______________________________________________
> 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.
>

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 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, <mauede at 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]]
>
> ______________________________________________
> 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.

Along similar lines, I wrote a toy script to apply any function you want 
  in a windowed sense.  Be warned that it's about 10000 times slower 
than loess().


# my  own boxcar tool, just because.
# use bfunc to specify what function to apply to the windowed
# region.
# basically must be valid function name and must accept
# single value or vector of values
# "pad" generates partial-width values at ends of x so output is
# same length as input.
# and make it optional for picky people
boxcar<-function(x, width=5, bfunc='mean', pad=TRUE){
	goodfunc<-try(bfunc<-get(bfunc),silent=TRUE)
	if (inherits (goodfunc,"try-error")) {
		stop ('"', bfunc,'"', ' is not a known
function', call.=FALSE)
		}
	# paranoid, force width to be integer
	width<-floor(width)
	# fix width given definition of window() inputs
	width<-max(0,(width-1))
	if (width%%2 == 1) cat('Warning: window is even length, hence 
asymmetric\n')
	#adjust start, end points to half-window width; keep output length right
	seqstart<- 1 -pad*((width+1)%/%2)
	seqend<- length(x)- width + pad*(width%/%2)
	boxout<-mapply(function(shiftx) {
		bfunc(window(x,max(shiftx,1), min(shiftx+width,length(x)) ) )
		} ,seq(seqstart, seqend) )
		return(invisible(boxout))
	}