Groupwise Dimension Reduction via Envelope Method

DOI10.1080/01621459.2014.970687zbMath1373.62156OpenAlexW2035558520WikidataQ38925337 ScholiaQ38925337MaRDI QIDQ5367465

Bing Li, Zifang Guo, Lexin Li, Wen-Bin Lu

Publication date: 13 October 2017

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4787236

zbMATH Keywords

dimension reductionsliced inverse regressioncentral subspacemultiple-index modelsdirect sum envelopesufficient dimension reduction (SDR) methods

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) General nonlinear regression (62J02)

Related Items (7)

AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories ⋮ Structured Ordinary Least Squares: A Sufficient Dimension Reduction approach for regressions with partitioned predictors and heterogeneous units ⋮ On expectile-assisted inverse regression estimation for sufficient dimension reduction ⋮ Group-wise sufficient dimension reduction with principal fitted components ⋮ Specification testing of partially linear single-index models: a groupwise dimension reduction-based adaptive-to-model approach ⋮ Specification Testing of Regression Models with Mixed Discrete and Continuous Predictors ⋮ Groupwise sufficient dimension reduction via conditional distance clustering

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