on 12/30/2008 08:33 AM Stephan Kolassa wrote:
> Dear useRs,
>
> I have a list, each entry of which is a matrix of constant dimensions.
> Is there a good way (i.e., not using a for loop) to apply a mean to each
> matrix entry *across list entries*?
>
> Example:
>
> foo <- list(rbind(c(1,2,3),c(4,5,6)),rbind(c(7,8,9),c(10,11,12)))
> some.sort.of.apply(foo,FUN=mean)
>
> I'm looking for a componentwise mean across the two entries of foo,
> i.e., the following output:
>
> [,1] [,2] [,3]
> [1,] 4 5 6
> [2,] 7 8 9
>
> [NB. My "real" application involves trimming and psych::winsor(), so
> anything that generalizes to this would be extra good.]
>
> I've been looking at apply and {s,l,m,t}apply, by, with and aggregate
> and searched the list archives... any ideas?
>
> Thanks a lot,
> Stephan
How about something like this:
> matrix(rowMeans(sapply(foo, c)), dim(foo[[1]]))
[,1] [,2] [,3]
[1,] 4 5 6
[2,] 7 8 9
Essentially, first create matching elementwise rows:
> sapply(foo, c)
[,1] [,2]
[1,] 1 7
[2,] 4 10
[3,] 2 8
[4,] 5 11
[5,] 3 9
[6,] 6 12
Then, get the row means:
> rowMeans(sapply(foo, c))
[1] 4 7 5 8 6 9
Then finally restructure the result to a matrix, using the dimensions of
foo[[1]].
This of course makes the assumption that each matrix is of the same size
and does not otherwise check for that.
HTH,
Marc Schwartz
______________________________________________
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.
