A theoretical view of the envelope model for multivariate linear regression as response dimension reduction

DOI10.1016/J.JKSS.2012.03.004zbMath1294.62089OpenAlexW1972785568MaRDI QIDQ2512574

Jae Keun Yoo

Publication date: 7 August 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2012.03.004

zbMATH Keywords

reducing subspacesmultivariate linear regressionenvelope modelresponse dimension reduction

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (1)

Response dimension reduction: model-based approach

Cites Work

• Response dimension reduction for the conditional mean in multivariate regression
• On almost linearity of low dimensional projections from high dimensional data
• The Geometry of Algorithms with Orthogonality Constraints
• Dimension Reduction for Multivariate Response Data
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