Mixture-Model Cluster Analysis Using Model Selection Criteria and a New Informational Measure of Complexity
- 1 January 1994
- book chapter
- Published by Springer Nature
Abstract
No abstract availableKeywords
This publication has 43 references indexed in Scilit:
- On the information-based measure of covariance complexity and its application to the evaluation of multivariate linear modelsCommunications in Statistics - Theory and Methods, 1990
- Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensionsPsychometrika, 1987
- DataPublished by Springer Nature ,1985
- A Monte Carlo Investigation Of The Likelihood Ratio Test For The Number Of Components In A Mixture Of Normal DistributionsMultivariate Behavioral Research, 1981
- MODERN DEVELOPMENT OF STATISTICAL METHODSPublished by Elsevier ,1981
- Unresolved Problems in Cluster AnalysisPublished by JSTOR ,1979
- Bayesian cluster analysisBiometrika, 1978
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974
- Information matrix for a mixture of two normal distributionsJournal of Statistical Computation and Simulation, 1972
- On the Distribution of the Likelihood RatioThe Annals of Mathematical Statistics, 1954