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#'
#' segtest.R
#'
#' Monte Carlo test of segregation for multitype patterns
#'
#' $Revision: 1.6 $ $Date: 2022/04/06 07:35:46 $
#'
segregation.test <- function(X, ...) {
UseMethod("segregation.test")
}
segregation.test.ppp <- function(X, ..., nsim=19, permute=TRUE,
verbose=TRUE, Xname) {
if(missing(Xname))
Xname <- short.deparse(substitute(X))
stopifnot(is.ppp(X))
stopifnot(is.multitype(X))
check.1.integer(nsim)
stopifnot(nsim > 1)
verboten <- c("at", "relative", "se", "leaveoneout",
"casecontrol", "case", "control")
if(any(nyet <- (verboten %in% names(list(...)))))
stop(paste(ngettext(sum(nyet), "Argument", "Arguments"),
commasep(sQuote(verboten[nyet])),
"cannot be used"))
lam <- intensity(X)
pbar <- lam/sum(lam)
np <- npoints(X)
nt <- length(pbar)
pbar <- matrix(pbar, byrow=TRUE, nrow=np, ncol=nt)
if(verbose) cat("Computing observed value... ")
phat <- relrisk(X, at="points", ..., casecontrol=FALSE)
obs <- sum((phat-pbar)^2)
if(verbose) {
cat(paste("Done.\nComputing", nsim, "simulated values... "))
pstate <- list()
}
sim <- numeric(nsim)
for(i in 1:nsim) {
Xsim <- rlabel(X, permute=permute)
phatsim <- relrisk(Xsim, at="points", ..., casecontrol=FALSE)
if(permute) pbarsim <- pbar else {
lamsim <- intensity(Xsim)
pbarsim <- lamsim/sum(lamsim)
pbarsim <- matrix(pbarsim, byrow=TRUE, nrow=np, ncol=nt)
}
sim[i] <- sum((phatsim - pbarsim)^2)
if(verbose) pstate <- progressreport(i, nsim, state=pstate)
}
if(verbose) cat("Done.\n")
p.value <- (1+sum(sim >= obs))/(1+nsim)
names(obs) <- "T"
out <- list(statistic=obs,
p.value=p.value,
method="Monte Carlo test of spatial segregation of types",
data.name=Xname)
class(out) <- "htest"
return(out)
}
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