MatManly.init: Initialization for the EM algorithm for matrix clustering

In MatManlyMix: Matrix Clustering with Gaussian and Manly Mixture Models

Description

Runs the initialization for the EM algorithm for matrix clustering

Usage

MatManly.init(Y, X = NULL, K, la = NULL, nu = NULL, Mu.type = 0, 
Psi.type = 0, n.start = 10, tol = 1e-05)

Arguments

Y	dataset of random matrices (p x T x n), n random matrices of dimensionality (p x T)
X	dataset of explanatory variables (T x q x n), q explanatory variables for modeling Y
K	number of clusters
la	initial transformation parameters (K x p)
nu	initial transformation parameters (K x T)
Mu.type	mean structure: 0-unrestricted, 1-additive
Psi.type	covariance structure of the Psi matrix: 0-unrestricted, 1-AR1
n.start	initial random starts
tol	tolerance level

Details

Random starts are used to obtain different starting values. The number of clusters, the skewness parameters, and number of random starts need to be specified. In the case when transformation parameters are not provided, the function runs the EM algorithm without any transformations, i.e., it is equivalent to the EM algorithm for a matrix Gaussian mixture. Notation: n - sample size, p x T - dimensionality of the random matrices, K - number of mixture components.

MatManlyMix documentation built on May 2, 2019, 5:58 a.m.