Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach

10.1214/22-BA1326

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Bibliographic Details
Main Authors:	Andrea Cremaschi, Raffaele Argiento, Maria De Iorio, Cai Shirong, Yap Seng Chong, Michael Meaney, Michelle Kee
Other Authors:	DEAN'S OFFICE (MEDICINE)
Format:	Article
Published:	International Society for Bayesian Analysis 2023
Subjects:	Graphical models Markov chain Monte Carlo Mixture models Multi-state models Normalised Point Processes
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/246545
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-246545
record_format	dspace
spelling	sg-nus-scholar.10635-2465452024-11-15T05:38:17Z Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach Andrea Cremaschi Raffaele Argiento Maria De Iorio Cai Shirong Yap Seng Chong Michael Meaney Michelle Kee DEAN'S OFFICE (MEDICINE) DEAN'S OFFICE (YALE-NUS COLLEGE) YALE-NUS COLLEGE DUKE-NUS MEDICAL SCHOOL PAEDIATRICS Graphical models Markov chain Monte Carlo Mixture models Multi-state models Normalised Point Processes 10.1214/22-BA1326 Bayesian Analysis 18 3 753-775 2023-12-23T06:32:07Z 2023-12-23T06:32:07Z 2023-09-23 Article Andrea Cremaschi, Raffaele Argiento, Maria De Iorio, Cai Shirong, Yap Seng Chong, Michael Meaney, Michelle Kee (2023-09-23). Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach. Bayesian Analysis 18 (3) : 753-775. ScholarBank@NUS Repository. https://doi.org/10.1214/22-BA1326 1936-0975 1931-6690 https://scholarbank.nus.edu.sg/handle/10635/246545 International Society for Bayesian Analysis
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Graphical models Markov chain Monte Carlo Mixture models Multi-state models Normalised Point Processes
spellingShingle	Graphical models Markov chain Monte Carlo Mixture models Multi-state models Normalised Point Processes Andrea Cremaschi Raffaele Argiento Maria De Iorio Cai Shirong Yap Seng Chong Michael Meaney Michelle Kee Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
description	10.1214/22-BA1326
author2	DEAN'S OFFICE (MEDICINE)
author_facet	DEAN'S OFFICE (MEDICINE) Andrea Cremaschi Raffaele Argiento Maria De Iorio Cai Shirong Yap Seng Chong Michael Meaney Michelle Kee
format	Article
author	Andrea Cremaschi Raffaele Argiento Maria De Iorio Cai Shirong Yap Seng Chong Michael Meaney Michelle Kee
author_sort	Andrea Cremaschi
title	Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
title_short	Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
title_full	Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
title_fullStr	Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
title_full_unstemmed	Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach
title_sort	seemingly unrelated multi-state processes: a bayesian semiparametric approach
publisher	International Society for Bayesian Analysis
publishDate	2023
url	https://scholarbank.nus.edu.sg/handle/10635/246545
_version_	1821199968653803520

Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach

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