MCLUST Version 3: An R Package for Normal Mixture Modeling and Model-Based Clustering

Abstract

MCLUST is a contributed R package for normal mixture modeling and model-based clustering. It provides functions for parameter estimation via the EM algorithm for normal mixture models with a variety of covariance structures, and functions for simulation from these models. Also included are functions that combine model-based hierarchical clustering, EM for mixture estimation and the Bayesian Information Criterion (BIC) in comprehensive strategies for clustering, density estimation and discriminant analysis. There is additional functionality for displaying and visualizing the models along with clustering and classification results. A number of features of the software have been changed in this version, and the functionality has been expanded to include regularization for normal mixture models via a Bayesian prior. A web page with related links including license information can be found at http://www.stat.washington.edu/mclust.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA456562

Entities

People

  • Adrian Raftery
  • Chris Fraley

Organizations

  • University of Washington

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Clustering
  • Computations
  • Covariance
  • Data Science
  • Data Sets
  • Discriminant Analysis
  • Grids
  • Information Science
  • Language
  • Maximum Likelihood Estimation
  • Normal Distribution
  • Probability
  • Specifications
  • Two Dimensional
  • Variable Coordinates

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Database Systems and Applications
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms