Guo, Wenxing and Balakrishnan, Narayanaswamy and Bian, Mengjie (2021) Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model. Electronic Journal of Statistics, 15 (2). pp. 4167-4191. DOI https://doi.org/10.1214/21-ejs1895
Guo, Wenxing and Balakrishnan, Narayanaswamy and Bian, Mengjie (2021) Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model. Electronic Journal of Statistics, 15 (2). pp. 4167-4191. DOI https://doi.org/10.1214/21-ejs1895
Guo, Wenxing and Balakrishnan, Narayanaswamy and Bian, Mengjie (2021) Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model. Electronic Journal of Statistics, 15 (2). pp. 4167-4191. DOI https://doi.org/10.1214/21-ejs1895
Abstract
In this work, we incorporate matrix projections into the reduced rank regression method, and then develop reduced rank regression estimators based on random projection and orthogonal projection in high-dimensional multivariate linear regression model. We propose a consistent estimator of the rank of the coefficient matrix and achieve prediction performance bounds for the proposed estimators based on mean squared errors. Finally, some simulation studies and a real data analysis are carried out to demonstrate that the proposed methods possess good stability, prediction performance and rank consistency compared to some other existing methods.
Item Type: | Article |
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Uncontrolled Keywords: | Matrix projection; reduced rank regression; dimension reduction; high-dimensional data; multivariate linear regression model |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 14 Dec 2022 15:36 |
Last Modified: | 30 Oct 2024 21:28 |
URI: | http://repository.essex.ac.uk/id/eprint/34235 |
Available files
Filename: 21-EJS1895.pdf