# R/ce.simnormal.Init.MeanVar.BIC.R In breakpoint: An R Package for Multiple Break-Point Detection via the Cross-Entropy Method

#### Defines functions ce.simnormal.Init.MeanVar.BIC

ce.simnormal.Init.MeanVar.BIC <-
function(N, init.locs, data, h, L0, L, M, Melite, eps, a, b, var.init){

#   if (N==0){
#     seql<-c(1,L)
#     mBic.full<-mBIC(seql,data,0,L,h)
#
#     return(list(locis=c(1,L+1),mBIC=mBic.full))
#     rm(mBic.full,seql)
#
#   } else {

########################Parameter initialization######################################################
#new_para<-rbind(rep(L0+(L-L0)/2,N),rep(sqrt(L-L0)^2/12,N))
new_para <- rbind(init.locs, rep(var.init, N))

#  n_par_m <- array(init.locs, dim=c(1,N))
#  n_par_sd<-array(std,dim=c(1,N))
#  new_para<-rbind(n_par_m,n_par_sd)
######################################################################################################
#   llVal <- c()
#   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,normrand,L0,L,M)
ch<-t(apply(ch,1,sort))

#     LL.full <- apply(ch, 1, loglikMeanVarNormal, data, h)
#     BIC.val <- -2*LL.full + 2*(N + 1)* log(L)
LL.full <- apply(ch, 1, llhood.MeanVarNormal, data, h)
BIC.val <- apply(as.data.frame(LL.full), 1, BIC.MeanVarNormal, N, L)

#mod_bic<-apply(ch,1,mBIC,data,N,L,h)
#ch<-cbind(ch,mod_bic)
ch <- cbind(ch, LL.full, BIC.val)
ch <- ch[order(ch[, (N + 4)], decreasing = FALSE), ]

melitesmpl<-ch[1:Melite,]
#     llVal[k] <- melitesmpl[1, (N + 3)]
#     bic[k] <- melitesmpl[1, (N + 4)]

new_par_n<-array(0,dim=c(2,N))
new_par_n[1,]<-apply(as.matrix(melitesmpl[,(2:(N+1))]),2,mean)
new_par_n[2,]<-apply(as.matrix(melitesmpl[,(2:(N+1))]),2,sd)

new_para[1,] <- a*new_par_n[1,] + (1-a)*new_para[1,]
new_para[2,] <- b*new_par_n[2,] + (1-b)*new_para[2,]