Jump to ContentJump to Main Navigation
Bayesian Theory and Applications$
Users without a subscription are not able to see the full content.

Paul Damien, Petros Dellaportas, Nicholas G. Polson, and David A. Stephens

Print publication date: 2013

Print ISBN-13: 9780199695607

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199695607.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 22 April 2021

Bayesian nonparametrics

Bayesian nonparametrics

(p.249) 13 Bayesian nonparametrics
Bayesian Theory and Applications

Stephen G Walker

Oxford University Press

This chapter discusses a certain type of large model for independent and identically distributed (i.i.d.) data, namely the popular mixture model based on stickbreaking processes. It then shows how this structure can be extended to cover non-i.i.d data, such as time series and regression models. These latter extensions require the calculation of a troublesome and unavoidable normalizing constant in order to do full Bayesian inference. Using a novel combination of latent models and Markov chain Monte Carlo (MCMC) techniques, the chapter shows that it is possible to provide satisfactorily complete Bayesian inference even in the non-i.i.d case.

Keywords:   Bayesian inference, i.i.d data, mixtue model, time series, regression, Markov chain Monte Carlo

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .