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Journal of Statistical Computation and Simulation Volume 86, 2016 - Issue 3
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Original Articles

Tuning-parameter selection in regularized estimations of large covariance matrices

Yixin FangDivision of Biostatistics, New York University School of Medicine, 650 First Avenue, 5th floor, NY10016, USAView further author information
,
Binhuan WangDivision of Biostatistics, New York University School of Medicine, 650 First Avenue, 5th floor, NY10016, USACorrespondence[email protected]
View further author information
&
Yang FengDepartment of Statistics, Columbia University, 1255 Amsterdam Avenue, 10th Floor, NY10027, USAView further author information
Pages 494-509 | Received 26 Sep 2014, Accepted 07 Feb 2015, Published online: 26 Feb 2015

Citations (15)

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Read on this site (3)

Philippe Boileau, Nima S. Hejazi, Mark J. van der Laan & Sandrine Dudoit. (2023) Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions. Journal of Computational and Graphical Statistics 32:2, pages 601-612.
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Yuan Ke, Heng Lian & Wenyang Zhang. (2022) High-Dimensional Dynamic Covariance Matrices With Homogeneous Structure. Journal of Business & Economic Statistics 40:1, pages 96-110.
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Richard Neuberg & Paul Glasserman. (2019) Estimating a covariance matrix for market risk management and the case of credit default swaps. Quantitative Finance 19:1, pages 77-92.
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Articles from other publishers (12)

K Klockmann & T Krivobokova. (2024) Efficient nonparametric estimation of Toeplitz covariance matrices. Biometrika.
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Jin Yang, Heng Lian & Wenyang Zhang. (2023) A Class of Structured High-Dimensional Dynamic Covariance Matrices. Communications in Mathematics and Statistics.
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Wanfeng Liang, Yue Wu & Hui Chen. (2022) Sparse covariance matrix estimation for ultrahigh dimensional data. Stat 11:1.
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Jason Xu & Kenneth Lange. (2022) A proximal distance algorithm for likelihood-based sparse covariance estimation. Biometrika 109:4, pages 1047-1066.
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Tayler A. Blake & Yoonkyung Lee. (2020) Nonparametric covariance estimation with shrinkage toward stationary models. WIREs Computational Statistics 12:6.
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Yumou Qiu & Janaka S. S. Liyanage. (2019) Threshold Selection for Covariance Estimation. Biometrics 75:3, pages 895-905.
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Hai Shu & Bin Nan. (2019) Estimation of large covariance and precision matrices from temporally dependent observations. The Annals of Statistics 47:3.
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Natalia Bailey, M. Hashem Pesaran & L. Vanessa Smith. (2019) A multiple testing approach to the regularisation of large sample correlation matrices. Journal of Econometrics 208:2, pages 507-534.
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Markku O. Kuismin & Mikko J. Sillanpää. (2017) Estimation of covariance and precision matrix, network structure, and a view toward systems biology. WIREs Computational Statistics 9:6.
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Rong Lu, Ryan M Smith, Michal Seweryn, Danxin Wang, Katherine Hartmann, Amy Webb, Wolfgang Sadee & Grzegorz A Rempala. (2015) Analyzing allele specific RNA expression using mixture models. BMC Genomics 16:1.
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Shu Huang, Russell Golman & Stephen Broomell. (2021) A Regularized Weighting Model of Judgment Aggregation. SSRN Electronic Journal.
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Richard Neuberg & Paul Glasserman. (2017) Estimating a Covariance Matrix for Market Risk Management and the Case of Credit Default Swaps. SSRN Electronic Journal.
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