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In this paper, we study the ordinary backfitting and smooth backfitting asmethods of fitting additive quantile models. We show that these backfittingquantile estimators are asymptotically equivalent to the correspondingbackfitting estimators of the additive components in a specially-designedadditive mean regression model. This implies that the theoretical properties ofthe backfitting quantile estimators are not unlike those of backfitting meanregression estimators. We also assess the finite sample properties of the twobackfitting quantile estimators.

Backfitting and smooth backfitting for additive quantile models