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Backfitting and smooth backfitting in varying coefficient quantile regression
- Lee, Young K.;
- Mammen, Enno;
- Park, Byeong U.
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7초록
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.
키워드
Backfitting; Integral equation; Kernel smoothing; Quantile regression; Smooth backfitting; Varying coefficient models
- 제목
- Backfitting and smooth backfitting in varying coefficient quantile regression
- 저자
- Lee, Young K.; Mammen, Enno; Park, Byeong U.
- 발행일
- 2014-06
- 유형
- Article
- 권
- 17
- 호
- 2
- 페이지
- S20 ~ S38