Frechet kernel sliced inverse regression

被引：2
|
作者：
Dong, Yushen [1 ]
Wu, Yichao [1 ]
机构：
[1] Univ Illinois, Dept Math,Stat & Comp Sci, 851 S Morgan St, Chicago, IL 60607 USA
来源：
JOURNAL OF MULTIVARIATE ANALYSIS | 2022年 / 191卷
基金：
美国国家科学基金会;
关键词：
Dimension Reduction; Fr?chet regression; Sliced inverse regression;
D O I：
10.1016/j.jmva.2022.105032
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Frechet regression is an extension of classical regression to study the relationship between a metric space-valued response and Euclidean predictors. In this paper, we propose a Frechet kernel sliced inverse regression to perform sufficient dimension reduction for Frechet regression and prove its consistency. Simulation examples and a real data example are used to illustrate its superb finite-sample performance. (C) 2022 Elsevier Inc. All rights reserved.
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页数：14
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