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bpr  

Fitting Bayesian Poisson Regression
View on CRAN: Click here


Download and install bpr package within the R console
Install from CRAN:
install.packages("bpr")

Install from Github:
library("remotes")
install_github("cran/bpr")

Install by package version:
library("remotes")
install_version("bpr", "1.0.8")



Attach the package and use:
library("bpr")
Maintained by
Laura D'Angelo
[Scholar Profile | Author Map]
First Published: 2021-09-22
Latest Update: 2022-10-22
Description:
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 (2023) .
How to cite:
Laura D'Angelo (2021). bpr: Fitting Bayesian Poisson Regression. R package version 1.0.8, https://cran.r-project.org/web/packages/bpr. Accessed 01 May. 2025.
Previous versions and publish date:
1.0.4 (2021-09-22 10:20), 1.0.5 (2022-05-25 17:30), 1.0.6 (2022-10-22 14:45), 1.0.7 (2024-01-18 17:30)
Other packages that cited bpr R package
View bpr citation profile
Other R packages that bpr depends, imports, suggests or enhances
Complete documentation for bpr
Functions, R codes and Examples using the bpr R package
Some associated functions: bpr-package . mcmc_diagnostics . merge_sim . plot.poisreg . plot.posterior_check . posterior_predictive . sample_bpr . summary.poisreg . 
Some associated R codes: RcppExports.R . bpr-package.R . emphpd.R . main.R . mcmc_diagnostics.R . merge.R . plot.R . plot_ppc.R . posterior_predictive.R . sampling.R . summary.R .  Full bpr package functions and examples
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