Package: bpr 1.0.8

Laura DAngelo

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

bpr_1.0.8.tar.gz
bpr_1.0.8.tar.gz(r-4.5-noble)bpr_1.0.8.tar.gz(r-4.4-noble)
bpr_1.0.8.tgz(r-4.4-emscripten)bpr_1.0.8.tgz(r-4.3-emscripten)
bpr.pdf |bpr.html
bpr/json (API)

# Install 'bpr' in R:
install.packages('bpr', repos = c('https://cran.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

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

1.30 score 5 scripts 336 downloads 4 exports 6 dependencies

Last updated 8 months agofrom:84852e731b. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-linux-x86_64OKNov 13 2024

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo