I recently wrote a function to compute functions over moving windows. (See
below). It varies from your request by using the last N points rather than
the last N/2 and next N/2 points, so you may have to modify it to get what
you want.
It will be in the next gregmisc package, which will go out in a month or so
when the publication review process here finishes. (I hate red tape!)
-Greg
########### CODE #############
# $Id: running.R,v 1.2 2001/09/01 00:01:54 warneg Exp $
#
# $Log: running.R,v $
# Revision 1.2 2001/09/01 00:01:54 warneg
# Release 0.3.0
#
# Revision 1.1 2001/08/25 05:53:37 warneg
# Initial CVS checkin.
#
#
"running" _ function( X, fun=mean, width=min(length(X),20),
allow.fewer=FALSE,...)
{
n _ length(X)
from <- sapply( (1:n) - width + 1, function(x) max(x,1) )
to <- 1:n
elements <- apply(cbind(from,to), 1,function(x) seq(x[1], x[2]) )
if(is.matrix(elements))
elements <- as.data.frame(elements)
funct _ function(which,what,fun,...) fun(what[which],...)
Xvar _ sapply(elements, funct, what=X, fun=fun, ...)
names(Xvar) <- paste(from,to,sep=":")
if(!allow.fewer)
Xvar[1:(width-1)] <- NA
return(Xvar)
}
########## DOCUMENTATION ###############
running package:gregmisc R Documentation
Apply a Function Over Adjacent Subsets of a Vector
Description:
Applies a function over subsets of the vector formed by taking a
fixed number of previous points.
Usage:
running(X, fun=mean, width=min(length(X),20), allow.fewer=FALSE,...)
Arguments:
X: data vector
fun: function to apply. Default is `mean'
width: integer giving the number of vector elements to include in
the subsets. Defaults to the lesser of the length of the
data and 20 elements.
allow.fewer: Boolean indicating whether the function should be computed
for initial subsets with fewer than `width' points
...: parameters to be passed to `fun'
Value:
Vector containg the results of applying the function `fun' to the
subsets.
Author(s):
Gregory R. Warnes Gregory_R_Warnes\@groton.pfizer.com
Examples:
running(1:20,width=5)
plot(1:20, running(1:20,width=5))
plot(1:20, running(1:20,width=5, allow.fewer=T))
# plot running mean and central 2 standard deviation range
# estimated by last 40 observations
dat <- rnorm(500, sd=1 + (1:500)/500 )
plot(dat)
fun <- function(x,sign=1) mean(x) + sign * sqrt(var(x))
lines(running(dat,width=50,fun=mean,allow=T),col="blue")
lines(running(dat,width=50,fun=fun, sign=-1, allow=T),col="red")
lines(running(dat,width=50,fun=fun, sign=1, allow=T),col="red")
> -----Original Message-----
> From: Erin Hodgess [mailto:hodgess at uhddx01.dt.uh.edu]
> Sent: Friday, February 22, 2002 2:10 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Cent. Mov. Ave
>
>
> Dear R People:
>
> Here is an interesting question(I think)
> Suppose I want to calculate Centered Moving Averages; i.e.
> x[1] <- ( sum(y[1:12]) )/12
> x[2] <- ( sum(y[2:13]) )/12
>
> and so on.
>
> Of course, this is easily done through loops. However, I have
> been trying to do this more elegantly, but have failed. I have
> tried things like
> j1 <- 1:109
> j2 <- 12:120
>
> x[1:109] <- ( sum( y[j1:j2]) )/12
>
> but it doesn't work. (Surprise!)
>
>
> R 1.4.0 on windows.
>
>
> Any ideas would be much appreciated!
>
> Thanks!
>
> Sincerely,
> Erin Hodgess
> Associate Professor
> Department of Computer and Mathematical Sciences
> University of Houston - Downtown
> 1 Main Street
> Houston, TX 77002
> mailto: hodgess at uhddx01.dt.uh.edu
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