Variables Clustering
Calculates principal components for every cluster
Choses a subspace for a variable
mBIC for subspace clustering
Simulates subspace clustering data with shared factors
Simulates subspace clustering data
Computes integration and acontamination of the clustering
Computes misclassification rate
Multiple Latent Components Clustering - Subspace clustering with autom...
Multiple Latent Components Clustering - kmeans algorithm
Multiple Latent Components Clustering - Subspace clustering assuming t...
Plot mlcc.fit class object
Print mlcc.fit class object
Print mlcc.reps.fit class object
Print clusters obtained from MLCC
Variable Clustering with Multiple Latent Components Clustering algorit...
Performs clustering of quantitative variables, assuming that clusters lie in low-dimensional subspaces. Segmentation of variables, number of clusters and their dimensions are selected based on BIC. Candidate models are identified based on many runs of K-means algorithm with different random initializations of cluster centers.