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-4.7-arm64)bpr_1.0.8.tar.gz(r-4.7-x86_64)bpr_1.0.8.tar.gz(r-4.6-arm64)bpr_1.0.8.tar.gz(r-4.6-x86_64)
bpr_1.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
bpr/json (API)

# Install 'bpr' in R:
install.packages('bpr', repos = c('https://cran.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 305 downloads 4 exports 6 dependencies

Last updated from:84852e731b. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK155
linux-devel-x86_64OK167
source / vignettesOK196
linux-release-arm64OK169
linux-release-x86_64OK153
wasm-releaseOK166

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo