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Intensive numerical studies of optimal sufficient dimension reduction with singularity

Title
Intensive numerical studies of optimal sufficient dimension reduction with singularity
Authors
Yoo J.K.Gwak D.-H.Kim M.-S.
Ewha Authors
유재근
SCOPUS Author ID
유재근scopus
Issue Date
2017
Journal Title
Communications for Statistical Applications and Methods
ISSN
2287-7843JCR Link
Citation
Communications for Statistical Applications and Methods vol. 24, no. 3, pp. 303 - 315
Keywords
Chi-square testOptimalitySingularitySufficient dimension reduction
Publisher
Korean Statistical Society
Indexed
SCOPUS; KCI scopus
Document Type
Article
Abstract
Yoo (2015, Statistics and Probability Letters, 99, 109-113) derives theoretical results in an optimal sufficient dimension reduction with singular inner-product matrix. The results are promising, but Yoo (2015) only presents one simulation study. So, an evaluation of its practical usefulness is necessary based on numerical studies. This paper studies the asymptotic behaviors of Yoo (2015) through various simulation models and presents a real data example that focuses on ordinary least squares. Intensive numerical studies show that the X2 test by Yoo (2015) outperforms the existing optimal sufficient dimension reduction method. The basis estimation by the former can be theoretically sub-optimal; however, there are no notable differences from that by the latter. This investigation confirms the practical usefulness of Yoo (2015). © 2017 The Korean Statistical Society, and Korean International Statistical Society. All rights reserved.
DOI
10.5351/CSAM.2017.24.3.303
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자연과학대학 > 통계학전공 > Journal papers
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