Nothing
`rarefy` <-
function (x, sample, se = FALSE, MARGIN = 1)
{
x <- as.matrix(x)
## as.matrix changes an n-vector to a n x 1 matrix
if (ncol(x) == 1 && MARGIN == 1)
x <- t(x)
if (!identical(all.equal(x, round(x)), TRUE))
stop("function accepts only integers (counts)")
minobs <- min(x[x > 0])
if (minobs > 1)
warning(gettextf("most observed count data have counts 1, but smallest count is %d", minobs))
minsample <- min(apply(x, MARGIN, sum))
if (missing(sample)) {
stop(
gettextf(
"the size of 'sample' must be given --\nHint: Smallest site maximum %d",
minsample))
}
if (any(sample > minsample))
warning(
gettextf(
"requested 'sample' was larger than smallest site maximum (%d)",
minsample))
rarefun <- function(x, sample) {
x <- x[x > 0]
J <- sum(x)
ldiv <- lchoose(J, sample)
p1 <- ifelse(J - x < sample, 0, exp(lchoose(J - x, sample) -
ldiv))
out <- sum(1 - p1)
if (se) {
V <- sum(p1 * (1 - p1))
Jxx <- J - outer(x, x, "+")
ind <- lower.tri(Jxx)
Jxx <- Jxx[ind]
V <- V + 2 * sum(ifelse(Jxx < sample, 0, exp(lchoose(Jxx,
sample) - ldiv)) - outer(p1, p1)[ind])
## V is >= 0, but numerical zero can be negative (e.g,
## -1e-16), and we avoid taking its square root
out <- cbind(out, sqrt(max(V, 0)))
}
out
}
if (length(sample) > 1) {
S.rare <- sapply(sample, function(n) apply(x, MARGIN, rarefun, sample = n))
S.rare <- matrix(S.rare, ncol=length(sample))
colnames(S.rare) <- paste("N", sample, sep="")
if (se) {
dn <- unlist(dimnames(x)[MARGIN])
rownames(S.rare) <- paste(rep(dn, each=2), c("S","se"), sep=".")
}
} else {
S.rare <- apply(x, MARGIN, rarefun, sample = sample)
if (se)
rownames(S.rare) <- c("S", "se")
}
attr(S.rare, "Subsample") <- sample
S.rare
}
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