Gives a complete account of the mathematical structure, statistical analysis, and applications of finite mixture distributions. Direct applications include economics, medicine, remote sensing, sedimentology, and signal detection (pattern recognition). Also describes indirect applicationsin outlier models, density estimation, Bayesian and empirical Bayes analysis, and robustness studies. Goes on to cover mathematical concepts such as identifiability and information, and the inferential problems associated with data from a mixture. Approximate sequential methods are developed here, in order to deal with estimation difficulties and engineering applications.
|Series:||Wiley Series in Probability and Statistics - Applied Probability and Statistics Section Series , #198|
|Product dimensions:||6.26(w) x 9.29(h) x 0.79(d)|
Table of Contents
Applications of Finite Mixture Models.
Mathematical Aspects of Mixtures.
Learning About the Parameters of a Mixture.
Learning About the Components of a Mixture.
Sequential Problems and Procedures.