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BIRS Workshop Lecture Videos

Optimal Estimation for Quantile Regression with Functional Response Wang, Xiao


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.

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