A New Visualization Technique to Study the Time Evolution of Finite and Adaptive Mixture Estimators.

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1994
Accession Number
ADA291147

Entities

People

  • Edward Wegman
  • Jeffrey L. Solka
  • Wendy L. Poston

Organizations

  • George Mason University

Tags

Communities of Interest

  • Air Platforms
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Bandwidth
  • Computational Science
  • Data Analysis
  • Data Science
  • Data Sets
  • Estimators
  • Information Science
  • Maximum Likelihood Estimation
  • Military Research
  • Personal Information Managers
  • Probability
  • Probability Density Functions
  • Standards
  • Statistical Algorithms
  • Statistics
  • Visualizations

Readers

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  • Computational Fluid Dynamics (CFD)
  • Pavement Materials Engineering.