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bayesQR (version 2.2)

Bayesian quantile regression

Description

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.

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Version

Install

install.packages('bayesQR')

Monthly Downloads

931

Version

2.2

License

GPL (>= 2)

Maintainer

Dries Benoit

Last Published

April 17th, 2014

Functions in bayesQR (2.2)

Prostate

Prostate Cancer Data
bayesQR

Bayesian quantile regression
predict.bayesQR

Calculate predicted probabilities for binary quantile regression
plot.bayesQR

Produce quantile plots or traceplots with plot.bayesQR
prior

Create prior for Bayesian quantile regression
summary.bayesQR

Summarize the output of the bayesQR function
print.bayesQR.summary

Prints the contents of bayesQR.summary object to the console
Churn

Customer Churn Data