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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

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

openblascppopenmp

1.30 score 5 scripts 294 downloads 4 exports 6 dependencies

Last updated 10 months agofrom:84852e731b. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 12 2025
R-4.5-win-x86_64OKJan 12 2025
R-4.5-linux-x86_64OKJan 12 2025
R-4.4-win-x86_64OKJan 12 2025
R-4.4-mac-x86_64OKJan 12 2025
R-4.4-mac-aarch64OKJan 12 2025
R-4.3-win-x86_64OKJan 12 2025
R-4.3-mac-x86_64OKJan 12 2025
R-4.3-mac-aarch64OKJan 12 2025

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo