calculate.pcas: Calculates principal components for every cluster

In varclust: Variables Clustering

Description

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

Usage

calculate.pcas(X, segmentation, number.clusters, max.subspace.dim,
  estimate.dimensions)

Arguments

X	A data matrix.
segmentation	A vector, segmentation of variables into clusters.
number.clusters	An integer, number of subspaces (clusters).
max.subspace.dim	An integer, upper bound for allowed dimension of subspace.
estimate.dimensions	A boolean, if TRUE subspaces dimensions are estimated using PESEL.

Value

A subset of principal components for every cluster.

varclust documentation built on June 27, 2019, 5:08 p.m.