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
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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'))

Peer review:

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

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

On CRAN:

2 exports 3 stars 1.33 score 0 dependencies 1 mentions 32 scripts 1.2k downloads

Last updated 1 years agofrom:79cbe8758e. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 08 2024
R-4.5-win-x86_64OKSep 08 2024
R-4.5-linux-x86_64OKSep 08 2024
R-4.4-win-x86_64OKSep 08 2024
R-4.4-mac-x86_64OKSep 08 2024
R-4.4-mac-aarch64OKSep 08 2024
R-4.3-win-x86_64OKSep 08 2024
R-4.3-mac-x86_64OKSep 08 2024
R-4.3-mac-aarch64OKSep 08 2024

Exports:bayesQRprior

Dependencies: