Parameterising apply To Compute Rolling Average of Columns in a matrix

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?

Thanks

Paolo

On 16 November 2010 20:05, Ray Brownrigg <Ray.Brownrigg at 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