Quantile trace regression via nuclear norm regularization

Lei Wang, Jing Zhang, Bo Li and Xiaohui Liu

Statistics & Probability Letters, 2022, vol. 182, issue C

Abstract: Trace regression models are widely used to accommodate matrix-type covariates, such as panel data, images, genomics microarrays, etc. In this paper, we extend the trace regression to the quantile trace regression model. The optimal convergence rate of the estimator is derived under mild conditions. Some simulations are carried out for illustration. Finally, we apply the proposed method to a students’ behavior data set related to personalized education.

Keywords: Quantile trace regression; Nuclear norm regularization; Matrix-type covariates; Optimal convergence rate (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2021.109299

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