Nothing
fcd.cluster <-
function(obj, K = 2){
### preparation
beta.combind = obj
min.length = length(beta.combind)
n = dim(beta.combind[[1]])[1]
cluster.list = matrix(0, nrow = n, ncol = min.length)
### clustering
for(i in 1: min.length){
temp1 = unique(beta.combind[[i]], margin = 2)
if(dim(temp1)[1] >= K){
k.means = kmeans(beta.combind[[i]], centers = K)
cluster.list[, i] = k.means$cluster
}
}
### return
return(cluster.list)
}
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