Testing block‐diagonal covariance structure for high‐dimensional data-Reference-Cited by-同舟云学术

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Testing block‐diagonal covariance structure for high‐dimensional data

Published:2015-05-26 Issue:4 Volume:69 Page:460-482
ISSN:0039-0402
Container-title:Statistica Neerlandica
language:en
Short-container-title:Statistica Neerlandica

Author:

Hyodo Masashi¹,Shutoh Nobumichi²,Nishiyama Takahiro³,Pavlenko Tatjana⁴

Affiliation:

1. Department of Mathematical Sciences, Graduate School of Engineering Osaka Prefecture University

2. Graduate School of Maritime Sciences Kobe University

3. Department of Business Administration Senshu University

4. Department of Mathematics KTH Royal Institute of Technology

Funder

National Research Council of Sweden (VR)

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/stan.12068

Reference9 articles.

1. Effect of high dimension: by an example of a two sample problem;Bai Z.;Statistica Sinica,1996

2. The joint graphical lasso for inverse covariance estimation across multiple classes

3. On testing for an identity covariance matrix when the dimensionality equals or exceeds the sample size

4. Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size

5. Covariance structure approximation via gLasso in high-dimensional supervised classification

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