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http://dx.doi.org/10.5351/KJAS.2022.35.5.657

Note on the estimation of informative predictor subspace and projective-resampling informative predictor subspace  

Yoo, Jae Keun (Department of Statistics, Ewha Womans University)
Publication Information
The Korean Journal of Applied Statistics / v.35, no.5, 2022 , pp. 657-666 More about this Journal
Abstract
An informative predictor subspace is useful to estimate the central subspace, when conditions required in usual suffcient dimension reduction methods fail. Recently, for multivariate regression, Ko and Yoo (2022) newly defined a projective-resampling informative predictor subspace, instead of the informative predictor subspace, by the adopting projective-resampling method (Li et al. 2008). The new space is contained in the informative predictor subspace but contains the central subspace. In this paper, a method directly to estimate the informative predictor subspace is proposed, and it is compapred with the method by Ko and Yoo (2022) through theoretical aspects and numerical studies. The numerical studies confirm that the Ko-Yoo method is better in the estimation of the central subspace than the proposed method and is more efficient in sense that the former has less variation in the estimation.
Keywords
clustering mean method; informative predictor subspace; multivariate regression; projective-resampling informative predictor subspace; projective-resampling mean method; suffcient dimension reduction;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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