# demgmm4

## Purpose

Demonstrate density modelling with a Gaussian mixture model.

## Synopsis

    demgmm4

## Description

The problem consists of modelling data generated by a mixture of three Gaussians in 2 dimensions with a mixture model using full covariance matrices. The priors are 0.3, 0.5 and 0.2; the centres are (2, 3.5), (0, 0) and (0,2); the variances are (0.16, 0.64) axis aligned, (0.25, 1) rotated by 30 degrees and the identity matrix. The first figure contains a scatter plot of the data.

A Gaussian mixture model with three components is trained using EM. The parameter vector is printed before training and after training. The user should press any key to continue at these points. The parameter vector consists of priors (the column), and centres (given as (x, y) pairs as the next two columns). The covariance matrices are printed separately.

The second figure is a 3 dimensional view of the density function, while the third shows the axes of the 1-standard deviation ellipses for the three components of the mixture model.

## See Also

`gmm`, `gmminit`, `gmmem`, `gmmprob`, `gmmunpak`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)