On splines approximation for sliced average variance estimation

DOI10.1016/j.jspi.2008.07.017zbMath1153.62025OpenAlexW2010025294MaRDI QIDQ999006

Zhou Yu, Li-ping Zhu, Li Xing Zhu

Publication date: 30 January 2009

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.07.017

zbMATH Keywords

asymptotic normalitydimension reductionB-splinesliced average variance estimationBayes information criterionstructural dimension

Mathematics Subject Classification ID

Numerical computation using splines (65D07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

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Cites Work

• Asymptotics for sliced average variance estimation
• On hybrid methods of inverse regression-based algorithms
• Local asymptotics for regression splines and confidence regions
• Asymptotics for kernel estimate of sliced inverse regression
• On kernel method for sliced average variance estimation
• Nonparametric checks for single-index models
• Approximation Theorems of Mathematical Statistics
• Determining the Dimension in Sliced Inverse Regression and Related Methods
• Sliced Inverse Regression for Dimension Reduction
• Graphics for Regressions With a Binary Response
• Extending Sliced Inverse Regression
• Save: a method for dimension reduction and graphics in regression
• On Sliced Inverse Regression With High-Dimensional Covariates
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