A data-adaptive hybrid method for dimension reduction

DOI10.1080/10485250902980568zbMath1172.62012OpenAlexW2046230121MaRDI QIDQ3182738

Li Xing Zhu, Li-ping Zhu

Publication date: 16 October 2009

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250902980568

zbMATH Keywords

asymptotic normalitydimension reductioninverse regressioncentral subspace

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) General nonlinear regression (62J02)

Cites Work

• Unnamed Item
• Sliced Regression for Dimension Reduction
• Asymptotics for sliced average variance estimation
• On hybrid methods of inverse regression-based algorithms
• An asymptotic theory for sliced inverse regression
• Asymptotics for kernel estimate of sliced inverse regression
• On kernel method for sliced average variance estimation
• Approximation Theorems of Mathematical Statistics
• On Directional Regression for Dimension Reduction
• Determining the Dimension in Sliced Inverse Regression and Related Methods
• Sliced Inverse Regression for Dimension Reduction
• Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
• Save: a method for dimension reduction and graphics in regression