Likelihood inflating sampling algorithm

Markov Chain Monte Carlo (MCMC) sampling from a posterior distribution corresponding to a massive data set can be computationally prohibitive as producing one sample requires a number of operations that is linear in the data size. In this article we introduce a new communication-free parallel method...

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Veröffentlicht in:	Canadian journal of statistics Jg. 46; H. 1; S. 147 - 175
Hauptverfasser:	ENTEZARI, Reihaneh, CRAIU, Radu V., ROSENTHAL, Jeffrey S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Ottawa Wiley 01.03.2018 Wiley Subscription Services, Inc
Schlagworte:	Algorithms Bayesian additive regression trees (BART) Bayesian analysis Bayesian inference big data Communication Computer simulation consensus Monte Carlo Data Inflating Markov analysis Markov Chain Monte Carlo (MCMC) Markov chains Microprocessors Monte Carlo simulation MSC 2010: Primary 62F15 Regression analysis Regression models Sampling secondary 62M20 Socioeconomic factors Statistical analysis Statistical methods Statistics Subsets Trees Canada
ISSN:	0319-5724, 1708-945X
Online-Zugang:	Volltext
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