A general theory for nonlinear sufficient dimension reduction: formulation and estimation

DOI10.1214/12-AOS1071zbMath1347.62018arXiv1304.0580MaRDI QIDQ1952450

Kuang-Yao Lee, Bing Li, Francesca Chiaromonte

Publication date: 30 May 2013

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.0580

zbMATH Keywords

unbiasednessdimension reduction \(\sigma\)-fieldexhaustivenesgeneralized sliced average variance estimatorgeneralized sliced inverse regression estimatorheteroscedastic conditional covariance operatorsufficient and complete dimension reduction classes

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Sufficient statistics and fields (62B05)

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