calculate.pcas

A vector, segmentation of variables into clusters.

segmentation

An integer, number of subspaces (clusters).

number.clusters

An integer, upper bound for allowed dimension of subspace.

max.subspace.dim

A boolean, if TRUE subspaces dimensions are estimated using PESEL.

estimate.dimensions

For given segmentation this function estimates dimensionality of each cluster (or chooses fixed dimensionality)
and for each cluster calculates the number of principal components equal to the this dimensionality

internal

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.

calculate.pcas: Calculates principal components for every cluster

Description

Usage

Arguments

Value