The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers advances in the field. This is the first book to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. Focusing mainly on Bayesian inference, the author reviews several frequentist techniques, especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian approach. The book is designed to show how finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, the book will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.
| ISBN: | 9781441921949 |
| Publication date: | 19th November 2010 |
| Author: | Sylvia FrühwirthSchnatter |
| Publisher: | Springer an imprint of Springer New York |
| Format: | Paperback |
| Pagination: | 492 pages |
| Series: | Springer Series in Statistics |
| Genres: |
Probability and statistics Stochastics Computational biology / bioinformatics Maths for computer scientists Psychological testing and measurement Econometrics and economic statistics |
The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers advances in the field. This is the first book to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. Focusing mainly on Bayesian inference, the author reviews several frequentist techniques, especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian approach. The book is designed to show how finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, the book will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.
Finite Mixture and Markov Switching Models features in the following genres: Probability and statistics, Stochastics, Computational biology / bioinformatics, Maths for computer scientists, Psychological testing and measurement, Econometrics and economic statistics
Finite Mixture and Markov Switching Models is available in Paperback, Hardback
Finite Mixture and Markov Switching Models was written by Sylvia FrühwirthSchnatter and published by Springer an imprint of Springer New York
Finite Mixture and Markov Switching Models has 492 pages
Yes it is part of Springer Series in Statistics series