Backfitting and smooth backfitting in varying coefficient quantile regression. Issue 2 (22nd April 2014) - Lee, Young K.; Mammen, Enno; Park, Byeong U.
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.