A new approach on recursive and non-recursive SIR methods

DOI10.1016/J.JKSS.2011.05.005zbMath1296.62137OpenAlexW2125834041MaRDI QIDQ744733

Thi Mong Ngoc Nguyen, Jérôme Saracco, Bernard Bercu

Publication date: 26 September 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.2011.05.005

zbMATH Keywords

recursive estimationsemiparametric regression modelsliced inverse regression (SIR)

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Multivariate analysis (62H99)

Related Items (3)

Recursive kernel estimator in a semiparametric regression model ⋮ Variable importance assessment in sliced inverse regression for variable selection ⋮ On the asymptotic behaviour of the recursive Nadaraya–Watson estimator associated with the recursive sliced inverse regression method

Uses Software

• R
• ARC

Cites Work

• On almost linearity of low dimensional projections from high dimensional data
• Slicing regression: A link-free regression method
• An asymptotic theory for sliced inverse regression
• Asymptotics for kernel estimate of sliced inverse regression
• Asymptotics for pooled marginal slicing estimator based on SIR\(_\alpha\) approach
• Some extensions of multivariate sliced inverse regression
• Sliced Inverse Regression for Dimension Reduction
• On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
• An asymptotic theory for sliced inverse regression
• Dimension Reduction for Multivariate Response Data
• Save: a method for dimension reduction and graphics in regression
• Sufficient Dimension Reduction via Inverse Regression
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