R/ce.sim4beta.MeanVar.BIC.R

Defines functions ce.sim4beta.MeanVar.BIC

ce.sim4beta.MeanVar.BIC <-
function(N, data, h, L0, L, M, Melite, eps, a){
  
  if (N == 0){
#     seql <- c(1, L)
#     LL.full <- loglikMeanVarNormal(seql, data, h)
#     BIC.value <- -2*LL.full + 2*(N + 1)* 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)
    LL.full <- loglik.MeanVarNormal(1, (L + 1), data, h)[[1]]
    BIC.full <- BIC.MeanVarNormal(LL.full, 0, L)
    return(list(loci = c(1, (L + 1)), BIC.Val = BIC.full, LogLike = LL.full))
    
  } else {
    
  ########################Parameter initialization######################################################  
  new.para <- array(1, dim = c(2, 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, betarand, 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) 
    
    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)] 
    
    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.Val = melitesmpl[1, (N + 4)][[1]], LogLike = melitesmpl[1, (N + 3)][[1]]))
  }
}

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breakpoint documentation built on May 29, 2017, 11 a.m.