Finite Mixture and Markov Switching Models

• Main Author: Frühwirth-Schnatter, Sylvia (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York, 2006.
• Series: Springer Series in Statistics,
• Subjects: Mathematics.; Mathematical statistics.; Bioinformatics.; Probabilities.; Statistics.; Econometrics.; Psychometrics.; Probability Theory and Stochastic Processes.; Statistical Theory and Methods.; Probability and Statistics in Computer Science.

The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way or other. The area of potential applications goes beyond simple data analysis...

Table of Contents:

• Finite Mixture Modeling
• Statistical Inference for a Finite Mixture Model with Known Number of Components
• Practical Bayesian Inference for a Finite Mixture Model with Known Number of Components
• Statistical Inference for Finite Mixture Models Under Model Specification Uncertainty
• Computational Tools for Bayesian Inference for Finite Mixtures Models Under Model Specification Uncertainty
• Finite Mixture Models with Normal Components
• Data Analysis Based on Finite Mixtures
• Finite Mixtures of Regression Models
• Finite Mixture Models with Nonnormal Components
• Finite Markov Mixture Modeling
• Statistical Inference for Markov Switching Models
• Nonlinear Time Series Analysis Based on Markov Switching Models
• Switching State Space Models.