Flexible Bayesian quantile regression for independent and clustered data
Flexible Bayesian quantile regression for independent and clustered data
Quantile regression has emerged as a useful supplement to ordinary mean regression. Traditional frequentist quantile regression makes very minimal assumptions on the form of the error distribution and thus is able to accommodate nonnormal errors, which are common in many applications. However, inference for these models is challenging, particularly for …