A Note on the Invariance Law for Surrogate Dimension Reduction

DOI10.1080/03610920903108517zbMath1203.62120OpenAlexW2123114728MaRDI QIDQ2786262

Bing Li, Xiangrong Yin

Publication date: 21 September 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920903108517

zbMATH Keywords

invariancemeasurement errorcentral mean spacecentral spaces

Mathematics Subject Classification ID

General nonlinear regression (62J02) Functional limit theorems; invariance principles (60F17)

Cites Work

• Dimension reduction for conditional mean in regression
• On surrogate dimension reduction for measurement error regression: An invariance law
• Principal Hessian Directions for regression with measurement error
• Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
• Measurement Error Regression with Unknown Link: Dimension Reduction and Data Visualization
• Dimension Reduction for the Conditionalkth Moment in Regression

This page was built for publication: A Note on the Invariance Law for Surrogate Dimension Reduction