Sufficient dimension reduction using Hilbert-Schmidt independence criterion
type: Item
instance of: scholarly article
title: Sufficient dimension reduction using Hilbert-Schmidt independence criterion
zbMATH Open document ID: 1466.62222
author: Yuan Xue
author: Nan Zhang
author: Xiangrong Yin
author: Haitao Zheng
published in: Computational Statistics and Data Analysis
publication date: 2018-08-14T00:00:00Z
Mathematics Subject Classification ID: 62-08
zbMATH DE Number: 6917776
zbMATH Keywords: bootstrap
zbMATH Keywords: central subspace
zbMATH Keywords: Hilbert-Schmidt independence criterion
zbMATH Keywords: multiple-index models
zbMATH Keywords: sufficient dimension reduction
describes a project that uses: PLCP
describes a project that uses: bootlib
describes a project that uses: SQPlab
MaRDI profile type: Publication
full work available at URL: j.csda.2017.05.002
OpenAlex ID: W2623847832
cites work: Numerical optimization. Theoretical and practical aspects. Transl. from the French
cites work: Graphics for Regressions With a Binary Response
cites work: Q4217298
cites work: Comment
cites work: Theory & Methods: Special Invited Paper: Dimension Reduction and Visualization in Discriminant Analysis (with discussion)
cites work: Q4348180
cites work: Q4370586
cites work: Q4739659
cites work: Discussion of: Brownian distance covariance
cites work: On almost linearity of low dimensional projections from high dimensional data
cites work: Sliced Inverse Regression for Dimension Reduction
cites work: On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
cites work: Contour regression: a general approach to dimension reduction
cites work: CONTINUOUS INSPECTION SCHEMES
cites work: A Cluster Analysis Method for Grouping Means in the Analysis of Variance
cites work: Direction estimation in single-index models via distance covariance
cites work: Sliced Regression for Dimension Reduction
cites work: An Adaptive Estimation of Dimension Reduction Space
cites work: Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
cites work: Successive direction extraction for estimating the central subspace in a multiple-index regres\-sion
cites work: Direction Estimation in Single-Index Regressions via Hilbert-Schmidt Independence Criterion
cites work: Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
DOI: 10.1016/J.CSDA.2017.05.002
Recommended article: 10.1162/153244303322753689
Recommended article: A unified approach to sufficient dimension reduction
Recommended article: A note on sufficient dimension reduction
Recommended article: Dimension estimation in sufficient dimension reduction: a unifying approach
Recommended article: Sufficient dimension reduction through discretization-expectation estimation
Recommended article: Sparse sufficient dimension reduction with heteroscedasticity
Recommended article: Sparse sufficient dimension reduction
Recommended article: Coordinate-independent sparse sufficient dimension reduction and variable selection
Recommended article: Efficient estimation in sufficient dimension reduction
Recommended article: Sufficient dimension reduction based on distance‐weighted discrimination
description: scientific article; zbMATH DE number 6917776