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

bpr_1.0.8.tar.gz
bpr_1.0.8.zip(r-4.7)bpr_1.0.8.zip(r-4.6)bpr_1.0.8.zip(r-4.5)
bpr_1.0.8.tgz(r-4.6-x86_64)bpr_1.0.8.tgz(r-4.6-arm64)bpr_1.0.8.tgz(r-4.5-x86_64)bpr_1.0.8.tgz(r-4.5-arm64)
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://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 322 downloads 4 exports 6 dependencies

Last updated from:84852e731b. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK161
linux-devel-x86_64OK165
source / vignettesOK174
linux-release-arm64OK164
linux-release-x86_64OK154
macos-release-arm64OK133
macos-release-x86_64OK289
macos-oldrel-arm64OK95
macos-oldrel-x86_64OK224
windows-develOK190
windows-releaseOK179
windows-oldrelOK166
wasm-releaseOK133

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo