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.

AuthorDries F. Benoit, Rahim Al-Hamzawi, Keming Yu, Dirk Van den Poel
Date of publication2017-01-27 10:38:21
MaintainerDries F. Benoit <Dries.Benoit@UGent.be>
LicenseGPL (>= 2)
Version2.3

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Files

bayesQR
bayesQR/inst
bayesQR/inst/CITATION
bayesQR/src
bayesQR/src/Makevars
bayesQR/src/QRb_AL_mcmc.f95
bayesQR/src/QRc_mcmc.f95
bayesQR/src/setseed.f95
bayesQR/src/QRb_mcmc.f95
bayesQR/src/QRc_AL_mcmc.f95
bayesQR/NAMESPACE
bayesQR/data
bayesQR/data/Prostate.rda
bayesQR/data/Churn.rda
bayesQR/R
bayesQR/R/plot.bayesQR.r
bayesQR/R/prior.r
bayesQR/R/summary.bayesQR.single.r
bayesQR/R/bayesQR.single.r
bayesQR/R/print.bayesQR.r
bayesQR/R/print.bayesQR.summary.r
bayesQR/R/summary.bayesQR.r
bayesQR/R/predict.bayesQR.r
bayesQR/R/bayesQR.r
bayesQR/MD5
bayesQR/DESCRIPTION
bayesQR/man
bayesQR/man/print.bayesQR.summary.Rd bayesQR/man/print.bayesQR.Rd bayesQR/man/Churn.Rd bayesQR/man/Prostate.Rd bayesQR/man/summary.bayesQR.Rd bayesQR/man/bayesQR.Rd bayesQR/man/prior.Rd bayesQR/man/predict.bayesQR.Rd bayesQR/man/plot.bayesQR.Rd

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