Package: bayesQR 2.4

Dries F. Benoit

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-4.7)bayesQR_2.4.zip(r-4.6)bayesQR_2.4.zip(r-4.5)
bayesQR_2.4.tgz(r-4.6-x86_64)bayesQR_2.4.tgz(r-4.6-arm64)bayesQR_2.4.tgz(r-4.5-x86_64)bayesQR_2.4.tgz(r-4.5-arm64)
bayesQR_2.4.tar.gz(r-4.7-arm64)bayesQR_2.4.tar.gz(r-4.7-x86_64)bayesQR_2.4.tar.gz(r-4.6-arm64)bayesQR_2.4.tar.gz(r-4.6-x86_64)
bayesQR_2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bayesQR/json (API)

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

Bug tracker:https://github.com/ugent-cvamo/bayesqr/issues

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

On CRAN:

Conda:

openblasfortran

4.30 score 4 stars 47 scripts 2.1k downloads 1 mentions 2 exports 0 dependencies

Last updated from:4549ee7f90. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK98
linux-devel-x86_64OK100
source / vignettesOK159
linux-release-arm64OK150
linux-release-x86_64OK109
macos-release-arm64OK167
macos-release-x86_64OK233
macos-oldrel-arm64OK226
macos-oldrel-x86_64OK340
windows-develOK91
windows-releaseOK93
windows-oldrelOK87
wasm-releaseOK88

Exports:bayesQRprior

Dependencies: