Chong Wang

Works (2)

Updated: July 5th, 2023 15:30

2018 journal article

Functional envelope for model-free sufficient dimension reduction

Journal of Multivariate Analysis, 163, 37–50.

By: X. Zhang, C. Wang & Y. Wu

Source: NC State University Libraries
Added: August 6, 2018

2018 journal article

Principal quantile regression for sufficient dimension reduction with heteroscedasticity

ELECTRONIC JOURNAL OF STATISTICS, 12(2), 2114–2140.

By: C. Wang n, S. Shin* & Y. Wu*

author keywords: Heteroscedasticity; kernel quantile regression; principal quantile regression; sufficient dimension reduction
TL;DR: A new SDR method called principal quantile regression (PQR) is proposed that efficiently and competitively tackles heteroscedasticity and can naturally be extended to a nonlinear version via kernel trick. (via Semantic Scholar)
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Source: Web Of Science
Added: March 25, 2019

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