The Poisson regression model for count data belongs to the family of “generalized linear models”, and is available in the R system for statistical computing. In this article, the Bayesian methods are applied to fit the Poisson model using analytic and simulation tools. Laplace Approximation is implemented for approximating posterior densities of the parameters. Moreover, parallel simulation tools are implemented using LaplacesDemon and R2jags packages of R. A data set “DoctorVisits” is used for the purpose of illustrations.
Digital Object Identifier (DOI)
Yousuf, Firdoos and Ali Khan, Athar
"Bayesian Analysis of Count Data with R Using Laplace Approximation and Simulation Tools,"
Journal of Statistics Applications & Probability: Vol. 9:
2, Article 7.
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol9/iss2/7