The Annals of Statistics
- Ann. Statist.
- Volume 38, Number 5 (2010), 2857-2883.
Backfitting and smooth backfitting for additive quantile models
In this paper, we study the ordinary backfitting and smooth backfitting as methods of fitting additive quantile models. We show that these backfitting quantile estimators are asymptotically equivalent to the corresponding backfitting estimators of the additive components in a specially-designed additive mean regression model. This implies that the theoretical properties of the backfitting quantile estimators are not unlike those of backfitting mean regression estimators. We also assess the finite sample properties of the two backfitting quantile estimators.
Ann. Statist., Volume 38, Number 5 (2010), 2857-2883.
First available in Project Euclid: 20 July 2010
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Lee, Young Kyung; Mammen, Enno; Park, Byeong U. Backfitting and smooth backfitting for additive quantile models. Ann. Statist. 38 (2010), no. 5, 2857--2883. doi:10.1214/10-AOS808. https://projecteuclid.org/euclid.aos/1279638542