Variable selection using axis-aligned random projections for partial least-squares regression-Reference-Cited by-同舟云学术

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Variable selection using axis-aligned random projections for partial least-squares regression

Published:2024-03-23 Issue:3 Volume:34 Page:
ISSN:0960-3174
Container-title:Statistics and Computing
language:en
Short-container-title:Stat Comput

Author:

Lin Youwu,Zeng Xin,Wang Pei,Huang Shuai,Teo Kok Lay

Funder

National Natural Science Foundation Committee of PR China

Guangxi Science and Technology Project

Guangdong Basic and Applied Basic Research Foundation

Fundamental Research Grant Scheme of Malaysia

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11222-024-10417-5.pdf

Reference33 articles.

1. Ahn, S.C., Bae, J.: Forecasting with Partial Least Squares When a Large Number of Predictors are Available. Available at SSRN 4248450 (2022)

2. Anderlucci, L., Fortunato, F., Montanari, A.: High-dimensional clustering via Random Projections. J. Classif. 39, 1–26 (2022)

3. Brown, P.J., Fearn, T., Vannucci, M.: Bayesian wavelet regression on curves with application to a spectroscopic calibration problem. J. Am. Stat. Assoc. 96(454), 398–408 (2001)

4. Cannings, T.I., Samworth, R.J.: Random-projection ensemble classification. J. R. Stat. Soc. Ser. B Stat. Methodol. 79(4), 959–1035 (2017)

5. Chun, H., Keleş, S.: Sparse partial least squares regression for simultaneous dimension reduction and variable selection. J. R. Stat. Soc. Ser. B Stat. Methodol. 72(1), 3–25 (2010)

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1. Random projection ensemble conformal prediction for high-dimensional classification;Chemometrics and Intelligent Laboratory Systems;2024-10

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