Handbook of Mixture Analysis

ISBN-13: 9781498763813 / Angielski / Twarda / 2019 / 498 str.

Sylvia Fruhwirth-Schnatter; Gilles Celeux; Christian P. Robert

Opis

This handbook is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy.

Spis treści

Part I: Methods; 1. Introduction to finite mixtures; 2. ML based inference; 3. Bayesian inference; 4. Posterior sampling; 5. Selecting the number of components; 6. Continuous non-Gaussian mixtures; 7. Mixtures for count data; 8. EM Algorithms for finite mixtures; 9. Infinite mixtures and NP mixtures; 10. Bayesian non-parametric mixture models; 11. Mixtures of experts; 12. Model-based clustering; Part II: Extensions and Applications; 13. Hidden Markov models and time series; 14. Infinite Hidden Markov Models; 15. Spatial mixtures and disease mapping; 16. Image analysis and visualisation; 17. High-dimensional panel data; 18. Applications in Genomics; 19. Applications in Medicine; 20. Applications in Economics; 21. Applications in Finance; 22. Applications in Marketing; 23. Applications in Industry; 24. Applications in Astronomy.