Gaussian Finite Mixture Model

Description

Fits a Gaussian mixture model for any number of classes

Usage

1
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

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