Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
About this item
Full title
Author / Creator
Publisher
Oxford: Oxford University Press
Journal title
Language
English
Formats
Publication information
Publisher
Oxford: Oxford University Press
Subjects
More information
Scope and Contents
Contents
Inference for Dirichlet process hierarchical models is typically performed using Markov chain Monte Carlo methods, which can be roughly categorized into marginal and conditional methods. The former integrate out analytically the infinite-dimensional component of the hierarchical model and sample from the marginal distribution of the remaining varia...
Alternative Titles
Full title
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_201701141
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_201701141
Other Identifiers
ISSN
0006-3444
E-ISSN
1464-3510
DOI
10.1093/biomet/asm086
