Nothing
ce.4betaNB.BIC.Init <-
function(N, init.locs, data, h, L0, L, M, Melite, eps, a, r, var.init){
######################### Parameter initialization #####################
new.para <- array(0, dim = c(2, N))
new.para[1, ] <- betaIntEst(init.locs[1:N], var.init, L0, L)$alpha.init
new.para[2, ] <- betaIntEst(init.locs[1:N], var.init, L0, L)$beta.init
########################################################################
# bic <- c()
k <- 0
repeat
{
k <- k + 1
ch <- array(0, dim = c(M, (N + 2)))
ch[, 1] <- c(1)
ch[, (N + 2)] <- c(L + 1)
ch[, (2 : (N + 1))] <- apply(new.para, 2, betarand, L0, L, M)
ch <- t(apply(ch, 1, sort))
loglike <- apply(ch, 1, llhoodnb, data, r, h)
bic.vals <- apply(as.data.frame(loglike), 1, BICnb, N, L)
ch <- cbind(ch, bic.vals, loglike)
ch <- ch[order(ch[, (N + 3)], decreasing = FALSE), ]
melitesmpl <- ch[1:Melite, ]
# bic[k] <- melitesmpl[1, (N + 3)]
newpar.n <- array(0, dim = c(2, N))
newpar.n[1, ] <- apply(as.matrix(melitesmpl[, (2 : (N + 1))]), 2, mean)
newpar.n[2, ] <- apply(as.matrix(melitesmpl[, (2 : (N + 1))]), 2, var)
newpar.new <- array(0, dim = c(2, N))
newpar.new[1, ] <- apply(newpar.n, 2, fun.alpha, L0, L)
newpar.new[2, ] <- apply(newpar.n, 2, fun.beta, L0, L)
new.para <- a * newpar.new + (1 - a) * new.para
mad <- apply(as.matrix(melitesmpl[, (2 : (N + 1))]), 2, mad)
if(max(mad) <= eps){break}
}
# return(list(loci = ch[1, (1 : (N + 2))], BIC = bic[k], LogLike = llVal[k]))
return(list(loci = ch[1, (1 : (N + 2))], BIC = melitesmpl[1, (N + 3)][[1]], LogLike = melitesmpl[1, (N + 4)][[1]]))
}
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