Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations

We consider the question of Markov chain Monte Carlo sampling from a general stick-breaking Dirichlet process mixture model, with concentration parameter α . This paper introduces a Gibbs sampling algorithm that combines the slice sampling approach of Walker (Communications in Statistics - Simulatio...

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Vydané v:	Statistics and computing Ročník 25; číslo 5; s. 1023 - 1037
Hlavní autori:	Hastie, David I., Liverani, Silvia, Richardson, Sylvia
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.09.2015
Predmet:	Algorithms Artificial Intelligence Computation Computer simulation Dirichlet problem Mathematical models Mathematics and Statistics Probability and Statistics in Computer Science Sampling Source code Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Mixture model Profile regression Dirichlet process Bayesian clustering
ISSN:	0960-3174, 1573-1375
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