A New Visualization Technique to Study the Time Evolution of Finite and Adaptive Mixture Estimators.
GEORGE MASON UNIV FAIRFAX VA CENTER FOR COMPUTATIONAL STATISTICS
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This paper focuses on recent work which analyzes the expectation maximization EM evolution of mixtures based estimators. The goal of this research is the development of effective visualization techniques to portray the mixture model parameters as they change in time. This is an inherently high dimensional process. Techniques are presented which portray the time evolution of univariate, bivariate, and trivariate finite and adaptive mixtures estimators. Adaptive mixtures is a recently developed variable bandwidth kernel estimator where each of the kernels is not constrained to reside at a sample location. The future role of these techniques in developing new versions of the adaptive mixtures procedure are also discussed.
- Statistics and Probability