Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach

Andrea Cremaschi; Raffaele Argiento; Maria De Iorio; Shirong Cai; Yap Seng Chong; Michael J. Meaney; Michelle Z. L. Kee

doi:10.1214/22-ba1326

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Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach

Andrea Cremaschi Raffaele Argiento Maria De Iorio Shirong Cai Yap Seng Chong Michael J. Meaney Michelle Z. L. Kee

Year: 2022 Journal: Bayesian Analysis Vol: 18 (3) Publisher: International Society for Bayesian Analysis

DOI: 10.1214/22-ba1326

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Abstract

10.1214/22-BA1326

Keywords:

Outlier Graphical model Computer science Cluster analysis Inference Posterior probability Dirichlet process Markov chain Monte Carlo Joint probability distribution Bayesian inference Econometrics Overdispersion Bayesian probability Covariate Mathematics Machine learning Artificial intelligence Statistics Poisson distribution Count data

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Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach

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