首页|Covariate-Assisted Matrix Completion with Multiple Structural Breaks

Covariate-Assisted Matrix Completion with Multiple Structural Breaks

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In matrix completion,additional covariates often provide valuable information for com-pleting the unobserved entries of a high-dimensional low-rank matrix A.In this paper,the authors consider the matrix recovery problem when there are multiple structural breaks in the coefficient matrix β under the column-space-decomposition model A=Xβ+B.A cumulative sum(CUSUM)statistic is constructed based on the penalized estimation of β.Then the CUSUM is incorporated into the Wild Binary Segmentation(WBS)algorithm to consistently estimate the location of breaks.Consequently,a nearly-optimal recovery of A is fulfilled.Theoretical findings are further corroborated via numerical experiments and a real-data application.

Additional covariatesmatrix completionmultiple structural breakswild Binary Seg-mentation

MENG Jing、FENG Long、ZOU Changliang、WANG Zhaojun

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School of Statistics and Data Science,KLMDASR,LEBPS,and LPMC,Nankai University,Tianjin 300071,China

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金中央高校基本科研业务费专项China National Key Research and Development ProgramChina National Key Research and Development ProgramChina National Key Research and Development Program

122260071227127111925106122310111193100111971247ZB220001052022YFA10037032022YFA10038002019YFC1908502

2024

10.1007/s11424-023-2342-2

系统科学与复杂性学报(英文版)
中国科学院系统科学研究所

系统科学与复杂性学报(英文版)

EI
影响因子：0.181
ISSN：1009-6124
年,卷(期)：2024.37(2)
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