bpr: Fitting Bayesian Poisson Regression

Posterior sampling and inference for Bayesian Poisson regression models. The model specification makes use of Gaussian (or conditionally Gaussian) prior distributions on the regression coefficients. Details on the algorithm are found in D'Angelo and Canale (2021) <arXiv:2109.09520>.

Version: 1.0.4
Imports: Rcpp (≥ 1.0.7), RcppArmadillo, coda, MASS
LinkingTo: Rcpp, RcppArmadillo, BH
Published: 2021-09-22
Author: Laura D'Angelo
Maintainer: Laura D'Angelo <laura.dangelo at live.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: bpr results

Documentation:

Reference manual: bpr.pdf

Downloads:

Package source: bpr_1.0.4.tar.gz
Windows binaries: r-devel: bpr_1.0.4.zip, r-devel-UCRT: bpr_1.0.4.zip, r-release: bpr_1.0.4.zip, r-oldrel: bpr_1.0.4.zip
macOS binaries: r-release (arm64): bpr_1.0.4.tgz, r-release (x86_64): bpr_1.0.4.tgz, r-oldrel: bpr_1.0.4.tgz

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