Minimax estimation of covariance and precision matrices for high-dimensional time series with long-memory-Reference-Cited by-同舟云学术

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Minimax estimation of covariance and precision matrices for high-dimensional time series with long-memory

Published:2021-10 Issue: Volume:177 Page:109177
ISSN:0167-7152
Container-title:Statistics & Probability Letters
language:en
Short-container-title:Statistics & Probability Letters

Author:

Zhang Qihu,Park Cheolwoo,Chung Jongik^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference21 articles.

1. Measure Theory and Probability Theory;Athreya,2006

2. Optimal approximations of power-laws with exponentials;Bochud,2006

3. Time Series: Theory and Methods;Brockwell,1991

4. Wavelets and statistical analysis of functional magnetic resonance images of the human brain;Bullmore;Stat. Methods Med. Res.,2003

5. A constrained ℓ1 minimization approach to sparse precision matrix estimation;Cai;J. Amer. Statist. Assoc.,2011

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sparse basis covariance matrix estimation for high dimensional compositional data via hard thresholding;Statistics & Probability Letters;2024-06

2. Lower bound estimation for a family of high-dimensional sparse covariance matrices;International Journal of Wavelets, Multiresolution and Information Processing;2023-09-23

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