R/ce.simnormal.MeanBIC.R

In breakpoint: An R Package for Multiple Break-Point Detection via the Cross-Entropy Method

ce.simnormal.MeanBIC <-
function(N,data,h,L0,L,M,Melite,eps,a,b){
  
#  v <- var(data[, 1])
#  if (N==0){
#     seql <- c(1, L)
#     LL.full <- loglikMeanNormal(seql, data, h)
#     BIC.value <- -2*LL.full + (N + 2)* log(L)
#     #       #AIC.val <- -2*LL.full + 4* (N + 1)
#     #       return(list(locis = c(1, (L + 1)), BIC.Val = BIC.val, LogLike = LL.full))
#     #       rm(LL.full, BIC.val)
#     
#     #mBic.full <- mBIC(seql, data, 0, L, h)    
#     return(list(loci = c(1, (L + 1)), BIC.Val = BIC.value, LogLike = LL.full))
#     rm(BIC.value, LL.full, seql)    
    v <- var(data[, 1])
    if (N == 0){
    
      LL.full <- loglik.MeanNormal(1, (L + 1), data, h, v)[[1]]
      BIC.full <- BIC.MeanNormal(LL.full, 0, L)
      return(list(loci = c(1, (L + 1)), BIC.Val = BIC.full, LogLike = LL.full))
      
      } else {
    
  ########################Parameter initialization######################################################  
  new_para<-rbind(rep(L0+(L-L0)/2,N),rep(sqrt(L-L0)^2/12,N))    
  ######################################################################################################  
#   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, loglikMeanNormal, data, h)
#     BIC.val <- -2*LL.full + (N + 2)* log(L)
    LL.full <- apply(ch, 1, llhood.MeanNormal, data, v, h)
    BIC.val <- apply(as.data.frame(LL.full), 1, BIC.MeanNormal, N, L) 
    
    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,]
    
    mad<-apply(as.matrix(melitesmpl[,(2:(N+1))]),2,mad)
    
    if(max(mad)<=eps){break}
  }
#  return(list(loci=ch[1,(1:(N+2))], BIC.Val = bic[k], LogLike = llVal[k]))
  return(list(loci=ch[1,(1:(N+2))], BIC.Val = melitesmpl[1, (N + 4)][[1]], LogLike = melitesmpl[1, (N + 3)][[1]]))
      }
}