Nothing
unisegmean <- function(Y,CGHo,Kmax){
n.com = length(Y)
present.data = which(!is.na(Y))
missing.data = which(is.na(Y))
x = Y[present.data]
out = segmeanCO(x,Kmax)
loglik = -(length(x)/2)*(log(2*pi*out$J.est/(length(x)))+1)
if (CGHo["select"]=="none"){
Kselect = Kmax
} else {
mBIC = sapply(1:Kmax,FUN=function(K){
th = out$t.est[K,1:K]
rupt = matrix(ncol=2,c(c(1,th[1:K-1]+1),th))
resmean = meanRuptR_c(Y, rupt[,2], K)
mu = data.frame(begin = rupt[,1],
end = rupt[,2],
mean = resmean)
mu = list(aux=mu)
getmBIC(K,loglik[K],mu,CGHo)
})
Kselect = which.max(mBIC)
}
t.est = bpwmissing(out$t.est,present.data,n.com)
th = t.est[Kselect,1:Kselect]
rupt = matrix(ncol=2,c(c(1,th[1:Kselect-1]+1),th))
resmean = meanRuptR_c(Y, rupt[,2], Kselect)
mu = data.frame(begin = rupt[,1],
end = rupt[,2],
mean = resmean)
invisible(list(mu=mu,loglik=loglik,t.est=t.est))
}
bpwmissing <- function(t.est,present.data,n.com){
for (h in 1:ncol(t.est)){
if (length(which(t.est[,h]==0))!=0){
t.est[,h][-which(t.est[,h]==0)] = present.data[t.est[,h]]
}
else {t.est[,h] = present.data[t.est[,h]]}
}
diag(t.est) = n.com
invisible(t.est)
}
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