Awesome - thanks!
Paolo
On 17 November 2010 19:44, Ray Brownrigg <ray.brownr...@ecs.vuw.ac.nz>wrote:
> On Thu, 18 Nov 2010, Paolo Rossi wrote:
> > I sent a post to find a clever way to compute a Rolling Average of
> columns
> > in a matrix and I was given the solution below which I am very pleased
> > with.
> >
> >
> > RollingAverage <- function(x, RollingObs) {
> > cx <- cumsum(x);
> > N <- length(x);
> > Temp <- (cx[RollingObs:N] - c(0, cx[1:(N-RollingObs)]))/RollingObs
> > Output <- array(NA, N)
> > Output[RollingObs:N] <- Temp;
> > Output
> > }
> >
> >
> > The only drawback is that in order to use apply to iterate over columns
> one
> > needs to write a fucntion for any RollingObs unless one is able to pass a
> > parameter through an apply call.
> >
> > Example:
> > a= array(1:100, dim = c(17,2))
> > RollingAverage(a[, 1], 7) # works fine
> > apply(a, 2, RollingAverage) # this doesnt work as it doesnt see
> > RollingObs
> >
> > Is there a way to pass an additional parameter to apply?
> >
> RTFM. Thats what the ... option of apply() is for.
>
> apply(a, 2, RollingAverage, RollingObs=7)
>
> Ray
>
> > Thanks
> >
> > Paolo
> >
> > On 16 November 2010 20:05, Ray Brownrigg <ray.brownr...@ecs.vuw.ac.nz
> >wrote:
> > > On Wed, 17 Nov 2010, Paolo Rossi wrote:
> > > > Hi,
> > > > Can anyone suggest a clever way to compute a rolling weekly average
> of
> > >
> > > the
> > >
> > > > columns in a matrix? The column bit is straightforward use apply
> > > > given
> > >
> > > a
> > >
> > > > function which does what you want on a column. With regard to a
> > >
> > > particular
> > >
> > > > column, the obvious way is to run a for loop indexing the last 7 days
> > > > and computing the average . I simply would like to know if there is a
> > > > better
> > >
> > > /
> > >
> > > > quicker way.
> > > >
> > > >
> > > >
> > > > Code:
> > > > Given a,
> > > >
> > > > > a= array(1:100, dim = c(17,2))
> > > > > a
> > > >
> > > > [,1] [,2]
> > > > [1,] 1 18
> > > > [2,] 2 19
> > > > [3,] 3 20
> > > > [4,] 4 21
> > > > [5,] 5 22
> > > > [6,] 6 23
> > > > [7,] 7 24
> > > > [8,] 8 25
> > > > [9,] 9 26
> > > > [10,] 10 27
> > > > [11,] 11 28
> > > > [12,] 12 29
> > > > [13,] 13 30
> > > > [14,] 14 31
> > > > [15,] 15 32
> > > > [16,] 16 33
> > > > [17,] 17 34
> > > > one needs to start computing the average from obs 7 s (at obs 7 you
> > > > have
> > >
> > > a
> > >
> > > > full week to compute the average) and compute the rolling weekly
> > > > average from day 7 onwards
> > > > Results will look like b
> > > > [,1] [,2]
> > > > [1,] 4 14
> > > > [2,] 5 21
> > > > [3,] 6 22
> > > > [4,] 7 23
> > > > [5,] 8 24
> > > > [6,] 9 25
> > > > [7,] 10 26
> > > > [8,] 11 27
> > > > [9,] 12 28
> > > > [10,] 13 29
> > > > Thanks in advance,
> > >
> > > I don't see how an average of 7 numbers all 18 or greater can be 14, as
> > > in your
> > > result[1, 2], unless you have mis-stated the question.
> > >
> > > Anyway, try:
> > > apply(a, 2, function(x) {cx <- cumsum(x); N <- length(x); (cx[7:N] -
> c(0,
> > > cx[1:(N-7)]))/7}
> > >
> > > HTH
> > > Ray Brownrigg
> > >
> > > > Paolo
>
>
>
[[alternative HTML version deleted]]
______________________________________________
R-help@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.
