eBook - ePub
Mixtures
Estimation and Applications
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
About this book
This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete.
The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.
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Table of contents
- Cover
- Table of Contents
- Preface
- Chapter 1: The EM algorithm, variational approximations and expectation propagation for mixtures
- Chapter 2: Online expectation maximisation
- Chapter 3: The Limiting Distribution of the EM Test of the Order of a Finite Mixture
- Chapter 4: Comparing Wald and Likelihood Regions Applied to Locally Identifiable Mixture Models
- Chapter 5: Mixture of experts modelling with social science applications
- Chapter 6: Modelling conditional densities using finite smooth mixtures
- Chapter 7: Nonparametric Mixed Membership Modelling Using the IBP Compound Dirichlet Process
- Chapter 8: Discovering nonbinary hierarchical structures with Bayesian rose trees
- Chapter 9: Mixtures of factor analysers Mixtures of factor analysers for the analysis of high-dimensional data
- Chapter 10: Dealing with label switching under model uncertainty
- Chapter 11: Exact Bayesian Analysis of Mixtures
- Chapter 12: Manifold MCMC for mixtures
- Chapter 13: How many components in a finite mixture?
- Chapter 14: Bayesian mixture models: a blood-free dissection of a sheep
- Index
- End User License Agreement
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Yes, you can access Mixtures by Kerrie L. Mengersen,Christian Robert,Mike Titterington in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.