Abstract
A new class of probability distributions, the so-called connected double truncated gamma distribution, is introduced. We show that using this class as the error distribution of a linear model leads to a generalized quantile regression model that combines desirable properties of both least-squares and quantile regression methods: robustness to outliers and differentiable loss function.
Acknowledgements
I.L. is a research associate of the F.R.S.-FNRS (Belgium). This research was supported by VUB GOA-062 and by the FWO-Vlaanderen grant G.0564.09N.