Estimation of error variance via ridge regression

• 成果类型: Article
• 署名作者: Liu, X.; Zheng, S.; Feng, X.
• 署名单位: Shanghai University of Finance & Economics; Northeast Normal University - China
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asz074
• 发表日期: 2020
• 页码: 481488
• 关键词: tests

摘要

We propose a novel estimator of error variance and establish its asymptotic properties based on ridge regression and random matrix theory. The proposed estimator is valid under both low- and high-dimensional models, and performs well not only in nonsparse cases, but also in sparse ones. The finite-sample performance of the proposed method is assessed through an intensive numerical study, which indicates that the method is promising compared with its competitors in many interesting scenarios.