Pivotal variable detection of the covariance matrix and its application to high-dimensional factor models

DOI10.1007/s11222-017-9762-6zbMath1384.62190OpenAlexW2735662577MaRDI QIDQ1704016

Hongyu Zhao, Li Xing Zhu, Jun-Long Zhao

Publication date: 8 March 2018

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-017-9762-6

zbMATH Keywords

principal component analysisfactor modelcovariance matrix estimationultra-high dimensionpivotal variable detectionrow sparsity

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12)

Cites Work

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• Inferential Theory for Factor Models of Large Dimensions
• Determining the Number of Factors in Approximate Factor Models