scholarly journals On Testing Homogeneity of Covariance Matrices with Box’s M and the Approximate Tests for Multivariate Data

2021 ◽  
Vol 9 (5) ◽  
Author(s):  
Knavoot Jiamwattanapong ◽  
Nisand Ingadapa
Keyword(s):  
Multivariate Data ◽  
Covariance Matrices ◽  
Testing Homogeneity

Testing homogeneity of high-dimensional covariance matrices

2019 ◽  
Author(s):  
Shurong Zheng ◽  
Ruitao Lin ◽  
Jianhua Guo ◽  
Guosheng Yin
Keyword(s):  
Covariance Matrices ◽  
High Dimensional ◽  
Testing Homogeneity

scholarly journals Testing Hypotheses Of Covariance Structure In Multivariate Data

2018 ◽  
Vol 33 ◽  
pp. 53-62 ◽  
Author(s):  
Miguel Fonseca ◽  
Arkadiusz Koziol ◽  
Roman Zmyslony
Keyword(s):  
Multivariate Data ◽  
Covariance Structure ◽  
Covariance Matrices ◽  
Multivariate Models ◽  
F Test ◽  
New Approach ◽  
Testing Hypotheses ◽  
Unbiased Estimators

In this paper there is given a new approach for testing hypotheses on the structure of covariance matrices in double multivariate data. It is proved that ratio of positive and negative parts of best unbiased estimators (BUE) provide an F-test for independence of blocks variables in double multivariate models.

scholarly journals NONNULL DISTRIBUTION OF LRC FOR TESTING HOMOGENEITY OF COVARIANCE MATRICES OF COMPLETELY SYMMETRIC GAUSSIAN MODELS

1991 ◽  
Vol 22 (1) ◽  
pp. 13-24
Author(s):  
A. K. GUPTA ◽  
D. K. NAGAR ◽  
VIPIN TAYAL
Keyword(s):  
Asymptotic Distribution ◽  
Likelihood Ratio ◽  
Hypergeometric Functions ◽  
Likelihood Ratio Statistic ◽  
Covariance Matrices ◽  
Zonal Polynomials ◽  
Gaussian Models ◽  
Testing Homogeneity ◽  
Nonnull Distribution

The nonnull moments of the likelihood ratio statistic for testing equality of covariance matrices of completely symmetric Gaussian models are obta.ined in terms of the Lauricella's hypergeometric functions and also in terms of zonal polynomials. Then the nonnull asymptotic distribution of the statistic is derived under certain alternatives for unequal samples.

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