BAYESIAN-INFERENCE FOR GENERALIZED LINEAR AND PROPORTIONAL HAZARDS MODELS VIA GIBBS SAMPLING

Authors
DELLAPORTAS P SMITH AFM
Citation
P. Dellaportas et Afm. Smith, BAYESIAN-INFERENCE FOR GENERALIZED LINEAR AND PROPORTIONAL HAZARDS MODELS VIA GIBBS SAMPLING, Applied Statistics, 42(3), 1993, pp. 443-459
Citations number
31
Categorie Soggetti
Statistic & Probability","Statistic & Probability
Journal title
Applied Statistics → ACNP
ISSN journal
00359254
Volume
42
Issue
3
Year of publication
1993
Pages
443 - 459
Database
ISI
SICI code
0035-9254(1993)42:3<443:BFGLAP>2.0.ZU;2-U
Abstract
It is shown that Gibbs sampling, making systematic use of an adaptive rejection algorithm proposed by Gilks and Wild, provides a straightfor ward computational procedure for Bayesian inferences in a wide class o f generalized linear and proportional hazards models.