Shrinkage estimation of high dimensional covariance matrices

2009 IEEE International Conference on Acoustics, Speech and Signal Processing ◽

10.1109/icassp.2009.4960239 ◽

2009 ◽

Author(s):

Yilun Chen ◽

Ami Wiesel ◽

Alfred O. Hero

Keyword(s):

Covariance Matrices ◽

High Dimensional ◽

Shrinkage Estimation

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Robust Shrinkage Estimation of High-Dimensional Covariance Matrices

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2011.2138698 ◽

2011 ◽

Vol 59 (9) ◽

pp. 4097-4107 ◽

Author(s):

Yilun Chen ◽

A. Wiesel ◽

A. O. Hero

Keyword(s):

Covariance Matrices ◽

High Dimensional ◽

Shrinkage Estimation

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Robust shrinkage estimation of high-dimensional covariance matrices

2010 IEEE Sensor Array and Multichannel Signal Processing Workshop ◽

10.1109/sam.2010.5606730 ◽

2010 ◽

Author(s):

Yilun Chen ◽

Ami Wiesel ◽

Alfred O. Hero

Keyword(s):

Covariance Matrices ◽

High Dimensional ◽

Shrinkage Estimation

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Large Sample Covariance Matrices and High-Dimensional Data Analysis

10.1017/cbo9781107588080 ◽

2015 ◽

Author(s):

Jianfeng Yao ◽

Shurong Zheng ◽

Zhidong Bai

Keyword(s):

Data Analysis ◽

High Dimensional Data ◽

Covariance Matrices ◽

High Dimensional ◽

Large Sample ◽

Sample Covariance Matrices ◽

Sample Covariance ◽

High Dimensional Data Analysis

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Dynamic Principal Component CAW Models for High-Dimensional Realized Covariance Matrices

SSRN Electronic Journal ◽

10.2139/ssrn.2888520 ◽

2016 ◽

Author(s):

Bastian Gribisch ◽

Michael Stollenwerk

Keyword(s):

Principal Component ◽

Covariance Matrices ◽

High Dimensional ◽

Realized Covariance

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Sparse Estimation of High-Dimensional Inverse Covariance Matrices with Explicit Eigenvalue Constraints

Journal of the Operations Research Society of China ◽

10.1007/s40305-021-00351-y ◽

2021 ◽

Author(s):

Yun-Hai Xiao ◽

Pei-Li Li ◽

Sha Lu

Keyword(s):

Covariance Matrices ◽

High Dimensional ◽

Sparse Estimation

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Empirical likelihood test for the equality of several high-dimensional covariance matrices

Science China Mathematics ◽

10.1007/s11425-019-1688-1 ◽

2021 ◽

Author(s):

Guili Liao ◽

Liang Peng ◽

Rongmao Zhang

Keyword(s):

Empirical Likelihood ◽

Covariance Matrices ◽

High Dimensional

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Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models

Scandinavian Journal of Statistics ◽

10.1111/sjos.12508 ◽

2020 ◽

Author(s):

Monika Bours ◽

Ansgar Steland

Keyword(s):

Time Series ◽

Linear Time ◽

Factor Models ◽

Covariance Matrices ◽

High Dimensional ◽

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Global one-sample tests for high-dimensional covariance matrices

Journal of Statistical Computation and Simulation ◽

10.1080/00949655.2021.1882459 ◽

2021 ◽

pp. 1-23

Author(s):

Xiaoyi Wang ◽

Baisen Liu ◽

Ning-Zhong Shi ◽

Guo-Liang Tian ◽

Shurong Zheng

Keyword(s):

Covariance Matrices ◽

High Dimensional

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Shrinkage Estimation of Effect Sizes as an Alternative to Hypothesis Testing Followed by Estimation in High-Dimensional Biology: Applications to Differential Gene Expression

Statistical Applications in Genetics and Molecular Biology ◽

10.2202/1544-6115.1504 ◽

2010 ◽

Vol 9 (1) ◽

Author(s):

Zahra Montazeri ◽

Corey M. Yanofsky ◽

David R. Bickel

Keyword(s):

Gene Expression ◽

Hypothesis Testing ◽

Differential Gene Expression ◽

Effect Sizes ◽

High Dimensional ◽

Shrinkage Estimation ◽

Differential Gene

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Ridge estimation of inverse covariance matrices from high-dimensional data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2016.05.012 ◽

2016 ◽

Vol 103 ◽

pp. 284-303 ◽

Author(s):

Wessel N. van Wieringen ◽

Carel F.W. Peeters

Keyword(s):

High Dimensional Data ◽

Covariance Matrices ◽

High Dimensional ◽

Ridge Estimation

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