Quantile regression for additive coefficient models in high dimensions
In this paper, we consider quantile regression in additive coefficient models (ACM) with high dimensionality under a sparsity assumption and approximate the additive coefficient functions by B-spline expansion. First, we consider the oracle estimator for quantile ACM when the number of additive coef...
Main Authors: | Fan, Zengyan, Lian, Heng |
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Other Authors: | School of Physical and Mathematical Sciences |
Format: | Journal Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/140938 |
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