genmix

GUI for generating data according to a finite mixture model.

Input Arguments:

None

Output Arguments:

None

Synopsis

This GUI will generate random variables using a finite mixture model. The user can pick between several models:

• SPHERICAL FAMILY (DIAGONAL COVARIANCE, SAME VARIANCES FOR VARIABLES/DIMENSIONS):

1. COV are of form lambda*I (clusters have equal covariances)
2: COV are of form lambda_k*I (clusers have unequal covariances)

• DIAGONAL FAMILY (DIAGONAL COVARIANCE, DIFFERENT VARIANCES FOR VARIABLES/DIMENSIONS):

3. COV are of form lambda*B (clusters have equal covariances)
4. COV are of form lambda*B_k (clusters have same volume, unequal shape)
5. COV are of form lambda_k*B_k (clusters have unequal volume, unequal shape)
where B = diag(b_1,...,b_d); B is a diagonal matrix with different values and det(B) = 1.

• GENERAL FAMILY (FULL COVARIANCE, OFF-DIAGONAL ELEMENTS ARE NON-ZERO)

6. COV are of form lambda*D*A*D' (clusters have equal covariance)
7. COV are of form lambda*D_k*A*(D_k)' (clusters have different orientation)
8. COV are of form lambda*D_k*A_k*(D_k)' (clusters have different orientation and shape)
9. COV are of form SIGMA_k_hat (unconstrained, all aspects vary)
where lambda represents the volume, D governs the orientation, and A is a diagonal matrix
that describes the shape.

The user can save the random variables to a text file (saved in row (observations) and column (variables) format. The data can also be saved to the MATLAB Workspace with a user-assigned variable name.

References:

Model-Based Clustering Toolbox documentation.