Test for equality of generalized variance in high-dimensional and large sample settings-Reference-Cited by-同舟云学术

Test for equality of generalized variance in high-dimensional and large sample settings

Published:2019-12-01 Issue:2 Volume:55 Page:
ISSN:0916-5746
Container-title:SUT Journal of Mathematics
language:
Short-container-title:SUT J. Math.

Author:

Sugiyama Takatoshi¹,Hyodo Masashi²,Watanabe Hiroki³,Tsukada Shin-ichi⁴,Seo Takashi¹

Affiliation:

1. Department of Applied Mathematics, Tokyo University of Science 1-3, Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan

2. Department of Mathematical Sciences, Graduate School of Science, Osaka Prefecture University 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan hyodo_h@yahoo.co.jp

3. Department of Health Sciences, Oita University of Nursing and Health Sciences 2944-9, Megusuno, Oita City, Oita 870-1201, Japan

4. School of Education, Meisei University 2-1-1, Hodokubo, Hino, Tokyo 191-8506 Japan

Publisher

SUT Journal of Mathematics - Tokyo University of Science

Subject

General Mathematics

Reference8 articles.

1. [1] Cai, T. T., Liang, T. and Zhou, H. H. (2015). Law of log determinant of sample covariance matrix and optimal estimation of differential entropy for high-dimensional Gaussian distributions, J. Multivariate Anal. 137, 161–172.

2. [2] Fujikoshi, Y. (1968). Asymptotic expansion of the distribution of the generalized variance in the non-central case, Journal of Science of the Hiroshima University, Series A-I (Mathematics) 32, 293–299.

3. [3] Nagao, H. (1973). Asymptotic expansions of the distributions of Bartlett’s test and sphericity test under the local alternatives, Ann. Inst. Statist. Math. 25, 407–422.

4. [4] Najarzadeh, D. (2017). Testing equality of generalized variances of $k$ multivariate normal populations, Comm. Statist. Simulation Comput. 46, 6414–6423.

5. [5] Sugiura, N. (1969). Asymptotic expansions of the distributions of the likelihood ratio criteria for covariance matrix, Ann. Math. Statist. 40, 2051–2063.

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