An integral transform method for estimating the central mean and central subspaces

DOI10.1016/j.jmva.2009.08.004zbMath1177.62054OpenAlexW1973169242MaRDI QIDQ1041081

Yu Zhu, Peng Zeng

Publication date: 27 November 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2009.08.004

zbMATH Keywords

integral transformkernel density estimationsufficient dimension reductionaverage derivative estimategeneralized multiple index model

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Numerical methods for integral transforms (65R10)

Related Items (17)

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Uses Software

• KernSmooth

Cites Work

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• On almost linearity of low dimensional projections from high dimensional data
• Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations
• Structure adaptive approach for dimension reduction.
• Dimension reduction for conditional mean in regression
• Optimal smoothing in single-index models
• Contour regression: a general approach to dimension reduction
• Exploring Regression Structure Using Nonparametric Functional Estimation
• Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Sliced Inverse Regression for Dimension Reduction
• Bandwidth Choice for Average Derivative Estimation
• On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
• Applications of analysis on nilpotent groups to partial differential equations
• Reweighting to Achieve Elliptically Contoured Covariates in Regression
• Graphics for Regressions With a Binary Response
• Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
• Theory & Methods: Special Invited Paper: Dimension Reduction and Visualization in Discriminant Analysis (with discussion)
• An Adaptive Estimation of Dimension Reduction Space
• Semiparametric Estimation of Index Coefficients
• Comment

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