Open AccessBackfitting and smooth backfitting in varying coefficient quantile regression
Author(s) -
Lee Young K.,
Mammen Enno,
Park Byeong U.
Publication year - 2014
Publication title -
the econometrics journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.861
H-Index - 36
eISSN - 1368-423X
pISSN - 1368-4221
DOI - 10.1111/ectj.12017
Subject(s) - quantile , quantile regression , estimator , mathematics , additive model , econometrics , mathematical optimization , statistics
Summary In this paper, we study ordinary backfitting and smooth backfitting as methods of fitting varying coefficient quantile models. We do this in a unified framework that accommodates various types of varying coefficient models. Our framework also covers the additive quantile model as a special case. Under a set of weak conditions, we derive the asymptotic distributions of the backfitting estimators. We also briefly report on the results of a simulation study.