Package: bayesQR 2.4

bayesQR: Bayesian Quantile Regression

Bayesian quantile regression using the asymmetric Laplace distribution, both continuous as well as binary dependent variables are supported. The package consists of implementations of the methods of Yu & Moyeed (2001) <doi:10.1016/S0167-7152(01)00124-9>, Benoit & Van den Poel (2012) <doi:10.1002/jae.1216> and Al-Hamzawi, Yu & Benoit (2012) <doi:10.1177/1471082X1101200304>. To speed up the calculations, the Markov Chain Monte Carlo core of all algorithms is programmed in Fortran and called from R.

Authors:Dries F. Benoit, Rahim Al-Hamzawi, Keming Yu, Dirk Van den Poel

bayesQR_2.4.tar.gz
bayesQR_2.4.zip(r-4.5)bayesQR_2.4.zip(r-4.4)bayesQR_2.4.zip(r-4.3)
bayesQR_2.4.tgz(r-4.5-x86_64)bayesQR_2.4.tgz(r-4.5-arm64)bayesQR_2.4.tgz(r-4.4-x86_64)bayesQR_2.4.tgz(r-4.4-arm64)bayesQR_2.4.tgz(r-4.3-x86_64)bayesQR_2.4.tgz(r-4.3-arm64)
bayesQR_2.4.tar.gz(r-4.5-noble)bayesQR_2.4.tar.gz(r-4.4-noble)
bayesQR_2.4.tgz(r-4.4-emscripten)bayesQR_2.4.tgz(r-4.3-emscripten)
bayesQR.pdf |bayesQR.html✨
bayesQR/json (API)

# Install 'bayesQR' in R:
install.packages('bayesQR', repos = c('https://driesbenoit.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/driesbenoit/bayesqr/issues

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications
Datasets:

On CRAN:

Conda:

fortranopenblas

3.93 score 4 stars 33 scripts 1.3k downloads 1 mentions 2 exports 0 dependencies

Last updated 2 years agofrom:79cbe8758e. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-win-x86_64OKMar 07 2025
R-4.5-mac-x86_64OKMar 07 2025
R-4.5-mac-aarch64OKMar 07 2025
R-4.5-linux-x86_64OKMar 07 2025
R-4.4-win-x86_64OKMar 07 2025
R-4.4-mac-x86_64OKMar 07 2025
R-4.4-mac-aarch64OKMar 07 2025
R-4.4-linux-x86_64OKMar 07 2025
R-4.3-win-x86_64OKMar 07 2025
R-4.3-mac-x86_64OKMar 07 2025
R-4.3-mac-aarch64OKMar 07 2025

Exports:bayesQRprior

Dependencies: