Package: bpr 1.0.8

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 (2023) <doi:10.1080/10618600.2022.2123337>.

Authors:Laura D'Angelo

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bpr.pdf |bpr.html
bpr/json (API)

# Install 'bpr' in R:
install.packages('bpr', repos = c('https://laura-dangelo.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.00 score 5 scripts 409 downloads 4 exports 6 dependencies

Last updated 11 months agofrom:84852e731b. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-win-x86_64OKMar 13 2025
R-4.5-mac-x86_64OKMar 13 2025
R-4.5-mac-aarch64OKMar 13 2025
R-4.5-linux-x86_64OKMar 13 2025
R-4.4-win-x86_64OKMar 13 2025
R-4.4-mac-x86_64OKMar 13 2025
R-4.4-mac-aarch64OKMar 13 2025
R-4.4-linux-x86_64OKMar 13 2025
R-4.3-win-x86_64OKMar 13 2025
R-4.3-mac-x86_64OKMar 13 2025
R-4.3-mac-aarch64OKMar 13 2025

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo