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Activity Number: 381 - High-Dimensional Nonparametric Statistics
Type: Invited
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #326928
Title: MASES: a Nonparametric Dimension Reduction Approach
Author(s): Hui Zou* and Qing Mai and Xin Zhang
Companies: University of Minnesota and Florida State University and Florida State University
Keywords: Categoricaldataanalysis; sliced inverse regression; suf?cient dimension reduction; Hellingerdistance

In this paper we introduce a new concept called Maximum Separation Subspace (MASES) as a natural inferential and estimative object for sufficient dimension reduction with binary or categorical response. This is joint work with Qing Mai and Xin Zhang.

Authors who are presenting talks have a * after their name.

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