glc: Gaussian Finite Mixture Model

In RPMM: Recursively Partitioned Mixture Model

Description

Fits a Gaussian mixture model for any number of classes

Usage

glc(Y, w, maxiter = 100, tol = 1e-06, weights = NULL, verbose = TRUE)

Arguments

Y	Data matrix (n x j) on which to perform clustering
w	Initial weight matrix (n x k) representing classification
maxiter	Maximum number of EM iterations
tol	Convergence tolerance
weights	Case weights
verbose	Verbose output?

Details

Typically not be called by user.

Value

A list of parameters representing mixture model fit, including posterior weights and log-likelihood

RPMM documentation built on May 2, 2019, 2:52 p.m.