Pairwise directions estimation for multivariate response regression data

DOI10.1080/00949655.2019.1572145OpenAlexW2914924092WikidataQ128438011 ScholiaQ128438011MaRDI QIDQ5107355

Heng-Hui Lue

Publication date: 27 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2019.1572145

zbMATH Keywords

local linear smoothercanonical correlationeffective dimension reductionsliced inverse regressionprincipal Hessian directionscurve data analysis

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Bayesian joint inference for multivariate quantile regression model with \(L_{1/2}\) penalty ⋮ Interpretable, predictive spatio-temporal models via enhanced pairwise directions estimation

Uses Software

• DAVID

Cites Work

• Sufficient dimension reduction based on an ensemble of minimum average variance estimators
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• Optimal selection of reduced rank estimators of high-dimensional matrices
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• A Semiparametric Approach to Canonical Analysis
• On Directional Regression for Dimension Reduction
• Penalized Normal Likelihood and Ridge Regularization of Correlation and Covariance Matrices
• Sliced Inverse Regression for Dimension Reduction
• On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
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• Theory & Methods: Special Invited Paper: Dimension Reduction and Visualization in Discriminant Analysis (with discussion)
• Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection
• An Adaptive Estimation of Dimension Reduction Space
• Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
• Sufficient Dimension Reduction via Inverse Regression
• RELATIONS BETWEEN TWO SETS OF VARIATES
• Comment
• The dual central subspaces in dimension reduction

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