Nothing
"autoreg" <-
function(x, probs, ejprob, plot=TRUE, nperp=4, species.fixed=TRUE, pdfnb=FALSE){
tjumps <- matrix(nrow=nperp*length(probs),ncol=3)
for (j in 1:length(probs)){
cat(" Estimating disj. parameter: Simulations for p= ",probs[j],"\n")
for (i in 1:nperp){
# print(x$n.species)
# print(x$specperreg)
# print(sum(x$specperreg))
test <- randpop.nb(x$nb,p.nb=probs[j], n.species=x$n.species,
vector.species=x$regperspec,
species.fixed=species.fixed,
pdf.regions=x$specperreg/sum(x$specperreg),
count=FALSE, pdfnb=pdfnb)
# print("Test generated")
# print(test)
# print(dim(test))
# print(x$regperspec)
nst <- apply(test,2,sum)
# print(nst)
# print(apply(test,1,sum) - x$specperreg)
tcn <- con.regmat(test,x$nb,count=FALSE)
# print("tcn computed")
ind <- (j-1)*nperp+i
tjumps[ind,1] <- probs[j]
tjumps[ind,2] <- sum(tcn-1)
# print(tjumps[ind,2])
tjumps[ind,3] <- tjumps[ind,2]/sum(nst-1)
}
}
ejlm <- lm(tjumps[,3]~tjumps[,1])
if (plot){
plot(tjumps[,1],tjumps[,3],xlab="pdisj",
ylab="qdisj")
# print(tjumps[,1])
# print(tjumps[,3])
abline(ejlm$coef)
abline(c(ejprob,0), lty=2)
}
pd <- (ejprob-ejlm$coef[1])/ejlm$coef[2]
cat(" Estimated disjunction parameter =",pd,"\n")
out <- list(pd=pd, coef=ejlm$coef)
out
}
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