Sufficient dimension reduction using Hilbert-Schmidt independence criterion

DOI10.1016/j.csda.2017.05.002zbMath1466.62222OpenAlexW2623847832MaRDI QIDQ1658374

Yuan Xue, Xiangrong Yin, Haitao Zheng, Nan Zhang

Publication date: 14 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2017.05.002

zbMATH Keywords

bootstrapsufficient dimension reductioncentral subspaceHilbert-Schmidt independence criterionmultiple-index models

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (2)

A brief review of linear sufficient dimension reduction through optimization ⋮ A new reproducing kernel‐based nonlinear dimension reduction method for survival data

Uses Software

• PLCP
• SQPlab
• bootlib

Cites Work

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• A Cluster Analysis Method for Grouping Means in the Analysis of Variance
• CONTINUOUS INSPECTION SCHEMES
• Comment
• Numerical optimization. Theoretical and practical aspects. Transl. from the French
• Discussion of: Brownian distance covariance

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