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R package 'bpr' to perform posterior inference for Bayesian Poisson regression

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bpr package

Posterior sampling and inference for Bayesian Poisson Regression

Efficient C++ based R package to sample from the posterior distribution of Poisson regression models. The model specification makes use of Gaussian (or conditionally Gaussian) prior distributions on the regression coefficients.

A tutorial on how to use the package can be found here.

Installation

The package is available on CRAN. To install it, simply run

install.packages("bpr")

Alternative installation from Github

library(devtools)
install_github("laura-dangelo/bpr/package")

The package requires Rcpp, RcppArmadillo and the C++ library boost.

How to cite

Thank you for your interest in my work! If you use this package in any of your projects, please cite the package and the related paper as:

  • D’Angelo, L. (2024), 'bpr: Bayesian Poisson regression', R package, version 1.0.7, URL: https://CRAN.R-project.org/package=bpr

  • D'Angelo, L. and Canale, A. (2023), 'Efficient posterior sampling for Bayesian Poisson regression', Journal of Computational and Graphical Statistics, 32(3), 917–926. doi:10.1080/10618600.2022.2123337

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R package 'bpr' to perform posterior inference for Bayesian Poisson regression

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