Bayesian auxiliary variable models for binary and multinomial regression

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...

ver descrição completa

Detalhes bibliográficos
Principais autores: Holmes, C, Held, L
Formato: Journal article
Idioma:English
Publicado em: 2006

Registros relacionados