This function implements the idea of Bayesian Binary quantile regression employing a likelihood function that is based on the asymmetric Laplace distribution.
BBqr(x,y, tau =0.5, runs =11000, burn =1000, thin=1)Matrix of predictors.
Vector of dependent variable.
The quantile of interest. Must be between 0 and 1.
Length of desired Gibbs sampler output.
Number of Gibbs sampler iterations before output is saved.
thinning parameter of MCMC draws.