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
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bpr_1.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
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 411 downloads 4 exports 6 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-arm64OK208
linux-devel-x86_64OK152
source / vignettesOK196
linux-release-arm64OK162
linux-release-x86_64OK153
macos-release-arm64OK120
macos-release-x86_64OK277
macos-oldrel-arm64OK96
macos-oldrel-x86_64OK313
windows-develOK196
windows-releaseOK170
windows-oldrelOK172
wasm-releaseOK190

Exports:mcmc_diagnosticsmerge_simposterior_predictivesample_bpr

Dependencies:BHcodalatticeMASSRcppRcppArmadillo