Select the clustering size for three-way clustering. The function searches over a range of clustering sizes and outputs the one that minimizes BIC. The clustering size (\(d_1\), \(d_2\), \(d_3\)) is a length-3 vector consisting of the number of clusters in each mode.
chooseClusteringSize(
x,
k,
r,
l,
lambda = 0,
sim.times = 1,
method = "L0",
n.cores = NULL
)a three-dimensional array
a vector, the possible numbers of clusters at mode 1
a vector, the possible numbers of clusters at mode 2
a vector, the possible numbers of clusters at mode 3
a numeric value, regularization coefficient
the number of simulation replicates when performing clustering
two options: "L0", "L1". "L0" indicates L0 penalty, and "L1" indicates Lasso penalty
the number of cores in parallel implementation
a list
estimated_krl a 1*3 matrix consisting of the estimated clustering size
BIC a vector consisting of the BIC value for all combinations of clustering sizes