Reduction of Gaussian mixture models by maximum similarity

Jørgen Harmse

Journal of Nonparametric Statistics, 2010, vol. 22, issue 6, 703-709

Abstract: Scott and Szewczyk developed an iterative method to simplify (reduce the order of) a Gaussian mixture model by merging the two most similar components. Since the comparison of all pairs of components may not be feasible, they propose to consider only nearly adjacent components, with no guarantee that they find the most similar. I give a method to find the most similar pair of components without comparing all pairs, and I propose an extension to higher dimensions.

Date: 2010
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DOI: 10.1080/10485250903377293

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