Jinjian Mu, Guanyu Hu, Lynn Kuo, "Bayesian Variable Selection for Poisson Regression with Spatially Varying Coefficients," WSEAS Transactions on Mathematics, vol. 18, pp. 435-438, 2019, DOI:
Jinjian Mu, Guanyu Hu, Lynn Kuo. Bayesian Variable Selection for Poisson Regression with Spatially Varying Coefficients.
WSEAS Transactions on Mathematics. 2019;18:435-438.
WSEAS Transactions on Mathematics
Print ISSN: 1109-2769, E-ISSN: 2224-2880
Volume 18, 2019
Bayesian Variable Selection for Poisson Regression with Spatially Varying Coefficients
Authors: , ,
Abstract: Poisson regression model is commonly used to model count data. In many scenarios, the data are collected from various locations so spatially varying coefficient Poisson regression model is developed to adjust for spatial dependence. We propose a Bayesian variable selection method for Poisson regression model with spatially varying coefficients. Considering computation efficiency we assign a conjugate multivariate log-gamma (MLG) prior to the regression coefficients and further incorporate the spatial information into the covariance matrix. We apply the horseshoe prior to facilitate a robust variable selection method with computational efficiency and build a MCMC algorithm for the posterior inference.
Pages: 435-438 WSEAS Transactions on Mathematics, ISSN / E-ISSN: 1109-2769 / 2224-2880, Volume 18, 2019, Art. #54 DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
×
Citation Tools