Sampling schemes for generalized linear Dirichlet process random effects models

Minjung Kyung; Jeff Gill; George Casella

doi:10.1007/s10260-011-0168-x

ScienceGate Book Chapters

JOURNAL ARTICLE

Sampling schemes for generalized linear Dirichlet process random effects models

Minjung Kyung Jeff Gill George Casella

Year: 2011 Journal: Statistical Methods & Applications Vol: 20 (3)Pages: 259-290 Publisher: Springer Science+Business Media

DOI: 10.1007/s10260-011-0168-x

Get Full-Text PDF Get Analytical Report

Keywords:

Dirichlet process Markov chain Monte Carlo Dirichlet distribution Generalized Dirichlet distribution Mathematics Hierarchical Dirichlet process Gibbs sampling Sampling (signal processing) Prior probability Nonparametric statistics Representation (politics) Latent Dirichlet allocation Applied mathematics Computer science Mathematical optimization Algorithm Statistics Artificial intelligence Monte Carlo method Topic model Dirichlet's energy Bayesian probability

Metrics

Cited By

2.74

FWCI (Field Weighted Citation Impact)

Refs

0.92

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Sampling schemes for generalized linear Dirichlet process random effects models

Metrics

Citation History

Topics

Related Documents

Rejoinder to the discussion of “Sampling schemes for generalized linear Dirichlet process random effects models”

Discussion of “Sampling schemes for generalized linear Dirichlet process random effects models” by M. Kyung, J. Gill and G. Casella

Discussion of the paper: “Sampling schemes for generalized linear Dirichlet process random effects models” by M. Kyung, J. Gill, and G. Casella

Dirichlet Process Mixed Generalized Linear Models

Dirichlet Process Mixed Generalized Linear Models