Bayesian auxiliary variable models for binary and multinomial regression

Bayesian auxiliary variable models for binary and multinomial regression

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In this paper we discuss auxiliary variable approaches to Bayesian binary and multinomial regression. These approaches are ideally suited to automated Markov chain Monte Carlo simulation. In the first part we describe a simple technique using joint updating that improves the performance of the conve...

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Dettagli Bibliografici
Autori principali:	Holmes, C, Held, L
Natura:	Journal article
Lingua:	English
Pubblicazione:	2006

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