VBmix (version 0.2.8)

classicEM: classicEM

Description

estimates a GMM on data using EM algorithm. A lower bound is calculated and monitored at each iteration.

Usage

classicEM(data, k, thres = 0.1, maxit = NULL)

Arguments

data

matrix of row-elements.

k

maximal number of components in the GMM. In case of degeneracies, the final model size may be less than 0.

thres

threshold for lower bound variations between 2 iterations. Convergence is decided if this variation is below thres.

maxit

if NULL, the stopping criterion is related to thres. If not NULL, maxit iterations are performed.

Value

• estimated GMM with at most k components, with labels containing associated labels for data in addition.

References

Bishop, C. M. (2006) _Pattern Recognition and Machine Learning_, Chapter 9, Springer.

See Also

newGmm varbayes

Examples

temp <- classicEM(irisdata, 4)