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#' Permutation test for the area of convex hull or ellipse in ordination
#'
#' Finds if the area covered by a convex hull or fitted ellipse is
#' smaller than expected under null hypothesis using permutation test.
#'
#' @param ord 2-d ordination
#' @param factor defining groups
#' @param are of convex hull of or an ellipse
#' @param permutations: number, permutation matrix or a
#' \code{\link[permute]{how}} definition.
#' @param parallel parallel processing
#' @param \dots other parameters passed to area functions
#'
#' @author Jari Oksanen
`ordiareatest` <-
function(ord, groups, area = c("hull", "ellipse"), permutations = 999,
parallel = getOption("mc.cores"), ...)
{
EPS <- sqrt(.Machine$double.eps)
## Function to find area
area <- match.arg(area)
areafun <- if (area == "hull") ordihull else ordiellipse
areafun <- match.fun(areafun)
## Observed statistics
obs <- summary(areafun(ord, groups, draw = "none", ...))["Area",]
## permutations
pfun <- function(take, ...)
summary(areafun(ord, groups[take], draw = "none", ...))["Area",]
perm <- getPermuteMatrix(permutations, length(groups))
nperm <- nrow(perm)
if (is.null(parallel))
parallel <- 1
hasClus <- inherits(parallel, "cluster")
if (hasClus || parallel > 1) {
if(.Platform$OS.type == "unix" && !hasClus) {
areas <- do.call(cbind,
mclapply(1:nperm,
function(i, ...) pfun(perm[i,],...),
mc.cores = parallel))
} else {
if (!hasClus) {
parallel <- makeCluster(parallel)
}
areas <- parApply(parallel, perm, MARGIN=1, pfun)
if (!hasClus)
stopCluster(parallel)
}
} else {
areas <- sapply(1:nperm, function(i, ...) pfun(perm[i,], ...))
}
signif <- (rowSums(areas <= obs + EPS) + 1)/(nperm + 1)
out <- list("areas" = obs, "pvalues" = signif, "permutations" = areas,
nperm = nperm, control = attr(perm, "control"), "kind" = area)
class(out) <- "ordiareatest"
out
}
### print method
`print.ordiareatest` <-
function(x, ...)
{
qu <- apply(x$permutations, 1, quantile, probs=c(0.05, 0.5))
m <- cbind("Area" = x$areas, t(qu), "Pr(<sim)" = x$pvalues)
cat("\n")
cat(gettextf("Permutation test for the size of ordination %ss\nAlternative hypothesis: observed area is smaller than random %s\n\n", x$kind, x$kind))
cat(howHead(x$control), "\n")
printCoefmat(m, tst.ind=1:3)
invisible(x)
}
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