Title	Optimal Estimation for Quantile Regression with Functional Response
Creator	Wang, Xiao
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2016-02-04T10:46
Description	Quantile regression with functional response and scalar covariates has become an important statistical tool for many neuroimaging studies. In this paper, we study optimal estimation of varying coefficient functions in the framework of reproducing kernel Hilbert space. Minimax rates of convergence under both fixed and random designs are established. We have developed easily implementable estimators which are shown to be rate-optimal. Simulations and real data analysis are conducted to examine the finite-sample performance. This is a joint work with Linglong Kong, Zhengwu Zhang, and Hongtu Zhu.
Extent	38 minutes
Subject	Mathematics; Statistics; Game theory, economics, social and behavioral sciences
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Purdue University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2016-08-05
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0307385
URI	http://hdl.handle.net/2429/58686
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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