[R-sig-eco] standard variation in dissimilarity matrix

[Gavin Simpson]

On Sun, 2011-07-17 at 15:51 +0200, magali proffit wrote:
> Dear all,
> linked to MRPP in Vegan there is a really nice function (meandist)
> which calculates a matrix of mean of distance, based on a grouping
> factor, from matrices of dissimilarity. I was wondering if there is an
> equivalent function calculating the standard deviation instead of the
> mean distance or if anyone has an idea how to do it.
> thanks a lot!
> Magali

meandist() computes the mean within and between block dissimilarities.
Do you want the within block standard deviation of dissimilarities and
the between block standard deviation of dissimilarities?

If so, you could just grab the sources for meandist and change this
line:

out[take] <- tapply(dist, cl, mean)

to be

out[take] <- tapply(dist, cl, sd)

(or use `var` in place of `sd` if you want the variance instead of the
standard deviation.). Here is a function that does just that, using
`sd`:

sddist <- function (dist, grouping, ...) 
{
    mergenames <- function(X, Y, ...) {
        xy <- cbind(X, Y)
        xy <- apply(xy, 1, sort)
        apply(xy, 2, paste, collapse = " ")
    }
    grouping <- factor(grouping, exclude = NULL)
    cl <- outer(grouping, grouping, mergenames)
    cl <- cl[lower.tri(cl)]
    n <- table(grouping)
    take <- matrix(TRUE, nlevels(grouping), nlevels(grouping))
    diag(take) <- n > 1
    take[upper.tri(take)] <- FALSE
    out <- matrix(NA, nlevels(grouping), nlevels(grouping))
    out[take] <- tapply(dist, cl, sd)
    out[upper.tri(out)] <- t(out)[upper.tri(out)]
    rownames(out) <- colnames(out) <- levels(grouping)
    class(out) <- c("meandist", "matrix")
    attr(out, "n") <- table(grouping)
    out
}

## meandist
require(vegan)
data(dune)
data(dune.env)
dune.md <- with(dune.env, meandist(vegdist(dune), Management))
dune.sd <- with(dune.env, sddist(vegdist(dune), Management))

HTH

G

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