Nothing
MVN_BayesianIterator <-
function(data, pri_mean=colMeans(data), Gibbs_nums=5000, pseudo_nums=dim(data)[1], threshold=1e-4, iteration=100, ...){
data_BayesP <- MVN_BayesianPosteriori(data, pri_mean)
for (i in 1:iteration){
data_Gibbs <- MVN_GibbsSampler(Gibbs_nums, data_BayesP, ...)
pseudo_data <- tail(data_Gibbs, pseudo_nums)
data_BayesP <- MVN_BayesianPosteriori(pseudo_data, colMeans(pseudo_data), var(pseudo_data))
p <- as.numeric(data_BayesP$mean)-as.vector(colMeans(pseudo_data))
if(norm(as.matrix(p), type = "2") < threshold){
print(paste("Finish at the", i, "step(s) in iteration.", sep = " "))
break
}
}
return(data_BayesP)
}
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