Abstract
In this work, we propose and investigate a family of non parametric quantile regression estimates. The proposed estimates combine local linear fitting and double kernel approaches. More precisely, we use a Beta kernel when covariate’s support is compact and Gamma kernel for left-bounded supports. Finite sample properties together with asymptotic behavior of the proposed estimators are presented. It is also shown that these estimates enjoy the property of having finite variance and resistance to sparse design.
MATHEMATICS SUBJECT CLASSIFICATION:
Acknowledgments
The authors wish to express their appreciation to the associate editor, the two referees, and Dr. Farid Beninel for their helpful suggestions and comments.