Bayesian inference using adaptive sampling

Our paper discusses simulation-based Bayesian inference using information from previous draws to build the proposals. The aim is to produce samplers that are easy to implement, that explore the target distribution effectively, and that are computationally efficient and mix well.

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Year of publication:	2008
Authors:	Giordani, Paolo ; Kohn, Robert
Subject:	Bayes-Statistik \| Bayesian inference \| Stichprobenerhebung \| Sampling \| Induktive Statistik \| Statistical inference \| Schätztheorie \| Estimation theory \| Statistische Methodenlehre \| Statistical theory

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Type of publication:	Article
Language:	English
Other identifiers:	10.1016/S0731-9053(08)23002-1 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015383644