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), Benoit & Van den Poel (2012) and Al-Hamzawi, Yu & Benoit (2012). To speed up the calculations, the Markov Chain Monte Carlo core of all algorithms is programmed in Fortran and called from R.

Author | Dries F. Benoit, Rahim Al-Hamzawi, Keming Yu, Dirk Van den Poel |

Date of publication | 2014-04-18 00:35:53 |

Maintainer | Dries F. Benoit <Dries.Benoit@UGent.be> |

License | GPL (>= 2) |

Version | 2.2 |

**bayesQR:** Bayesian quantile regression

**Churn:** Customer Churn Data

**plot.bayesQR:** Produce quantile plots or traceplots with 'plot.bayesQR'

**predict.bayesQR:** Calculate predicted probabilities for binary quantile...

**print.bayesQR:** Prints the contents of 'bayesQR.summary' object to the...

**prior:** Create prior for Bayesian quantile regression

**Prostate:** Prostate Cancer Data

**summary.bayesQR:** Summarize the output of the 'bayesQR' function

bayesQR

bayesQR/src

bayesQR/src/Makevars

bayesQR/src/QRb_AL_mcmc.f95

bayesQR/src/QRc_mcmc.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.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.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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