Bayesian Analysis
- Bayesian Anal.
- Volume 4, Number 4 (2009), 793-816.
Markov switching Dirichlet process mixture regression
Athanasios Kottas and Matthew A. Taddy
Abstract
Markov switching models can be used to study heterogeneous populations that are observed over time. This paper explores modeling the group characteristics nonparametrically, under both homogeneous and nonhomogeneous Markov switching for group probabilities. The model formulation involves a finite mixture of conditionally independent Dirichlet process mixtures, with a Markov chain defining the mixing distribution. The proposed methodology focuses on settings where the number of subpopulations is small and can be assumed to be known, and flexible modeling is required for group regressions. We develop Dirichlet process mixture prior probability models for the joint distribution of individual group responses and covariates. The implied conditional distribution of the response given the covariates is then used for inference. The modeling framework allows for both non-linearities in the resulting regression functions and non-standard shapes in the response distributions. We design a simulation-based model fitting method for full posterior inference. Furthermore, we propose a general approach for inclusion of external covariates dependent on the Markov chain but conditionally independent from the response. The methodology is applied to a problem from fisheries research involving analysis of stock-recruitment data under shifts in the ecosystem state.
Article information
Source
Bayesian Anal. Volume 4, Number 4 (2009), 793-816.
Dates
First available in Project Euclid: 22 June 2012
Permanent link to this document
https://projecteuclid.org/euclid.ba/1340369825
Digital Object Identifier
doi:10.1214/09-BA430
Mathematical Reviews number (MathSciNet)
MR2570089
Zentralblatt MATH identifier
1330.62141
Keywords
Dirichlet process prior hidden Markov model Markov chain Monte Carlo multivariate normal mixture stock-recruitment relationship
Citation
Taddy, Matthew A.; Kottas, Athanasios. Markov switching Dirichlet process mixture regression. Bayesian Anal. 4 (2009), no. 4, 793--816. doi:10.1214/09-BA430. https://projecteuclid.org/euclid.ba/1340369825.
