Independence and equality of covariance matrices of two multivariate normal distributions

The exact percentage points of the likelihood ratio statistic for testing the hypothesis that two p-variate normal distributions are independent and their covariance matrices are equal have been computed for p = 2,3,4 and 5.

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Publication Details

Journal
International journal of mathematics and computer science
Published
2024-11-20
DOI
https://doi.org/10.69793/ijmcs/01.2025/edwin
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Independence and equality of covariance matrices of two multivariate normal distributions

Johanna Marcela Orozco-Castañeda, Edwin Zarrazola, Daya K. Nagar
International journal of mathematics and computer science
Advanced Statistical Methods and Models
article

Independence and equality of covariance matrices of two multivariate normal distributions

Johanna Marcela Orozco-Castañeda, Edwin Zarrazola, Daya K. Nagar
article en

Abstract

The exact percentage points of the likelihood ratio statistic for testing the hypothesis that two p-variate normal distributions are independent and their covariance matrices are equal have been computed for p = 2,3,4 and 5.

International journal of mathematics and computer science
Universidad de Antioquia (CO)
Universidad de Antioquia
Reduced inequalities
Openalex Percentile: Top 79%
Advanced Statistical Methods and Models
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