Nothing
"niche.test" <- function (kasc, points, nrep = 999, o.include = TRUE, ...)
{
## Verifications
if (!inherits(kasc, "kasc"))
stop("should be an object of class \"kasc\"")
if (ncol(points) != 2)
stop("points should have 2 columns")
nrep <- nrep + 1
toto <- join.kasc(points, kasc)
tutu <- apply(toto, 1, function(x) any(is.na(x)))
if (sum(tutu) > 0)
stop("points outside the study area")
## conversion factors -> dummy variables
litab <- kasc2df(kasc)
dude <- dudi.mix(litab$tab, scannf = FALSE)
cw <- dude$cw
kasc <- df2kasc(dude$tab, litab$index, kasc)
## prepare the data for the external call
asc <- getkasc(kasc, names(kasc)[1])
coo <- getXYcoords(kasc)
rc <- lapply(coo, range)
kasc <- as.matrix(kasc)
kasc[is.na(kasc)] <- -9999
asc[is.na(asc)] <- -9999
xp <- as.matrix(points)
## External call to the function randmargtolpts
toto <- .C("randmargtolpts", as.double(t(xp)), as.double(rc$x),
as.double(rc$y), as.double(t(asc)), as.double(cw),
as.double(t(kasc)), as.double(coo$x), as.double(coo$y),
as.double(attr(asc,"cellsize")), double(nrep),
double(nrep), as.integer(nrep),
as.integer(nrow(asc)), as.integer(ncol(asc)),
as.integer(ncol(kasc)), as.integer(nrow(xp)),
PACKAGE = "adehabitat")
## Output
mar <- toto[[10]]
tol <- toto[[11]]
dfxy <- data.frame(marginalite = mar, tolerance = tol)[-1,]
obs <- c(mar[1], tol[1])
biv.test(dfxy, obs, sub = "Tests of\nmarginality\nand tolerance",
o.include = o.include, ...)
return(invisible(list(dfxy = dfxy, obs = obs)))
}
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