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#function to compute distribution on statistics of a box given resampling of dataset
#source("ofun.r")
resampstats <- function(ntimes=100, resampsize=.5,dset, y=NULL, abox, boxtype="OLD"){
statmat <- matrix(nrow=ntimes,ncol=2)
dsetsize <- nrow(dset)
if (resampsize <= 1){
rnum <- resampsize*nrow(dset)
} else{rnum <- resampsize}
if(!is.null(y)){dset <- cbind(dset,y)}
for (i in 1:ntimes){
tempind <- sample(dsetsize,rnum)
tempdset <- dset[tempind,]
if (boxtype=="OLD"){
svect <- beval(tempdset,list(abox))
} else {stop("Currently only set up to use 'old' box formulation")}
statmat[i,1] <- svect[2] #coverage
statmat[i,2] <- svect[1] #density
}
covv <- as.numeric(statmat[,1])
denv <- as.numeric(statmat[,2])
statmat <- cbind(covv,denv)
descrip <- apply(statmat,2,summary)
sdboth <- apply(statmat,2,sd)
descrip <- rbind(descrip,sdboth,(as.numeric(beval(dset,list(abox))[2:1])))
gmean <- mean(dset[,ncol(dset)])
mdiff <- descrip[4,2] - gmean
pseudot <- mdiff/sdboth[2]
rownames(descrip) <- c(rownames(descrip)[1:6],"stdev","full")
colnames(descrip) <- c("coverage","density")
attr(descrip,"globalmean") <- gmean
attr(descrip,"pseudot") <- pseudot
return(descrip)
}
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