# Asymptotic Distributions for Likelihood Ratio Tests for the Equality of Covariance Matrices

@inproceedings{Guo2021AsymptoticDF, title={Asymptotic Distributions for Likelihood Ratio Tests for the Equality of Covariance Matrices}, author={Wenchuan Guo and Yongcheng Qi}, year={2021} }

Consider k independent random samples from p-dimensional multivariate normal distributions. We are interested in the limiting distribution of the log-likelihood ratio test statistics for testing for the equality of k covariance matrices. It is well known from classical multivariate statistics that the limit is a chi-square distribution when k and p are fixed integers. Jiang and Yang [12] and Jiang and Qi [11] have obtained the central limit theorem for the log-likelihood ratio test statistics…

## 3 Citations

### Limiting distributions of the likelihood ratio test statistics for independence of normal random vectors

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- 2022

Consider the likelihood ratio test (LRT) statistics for the independence of sub-vectors from a p-variate normal random vector. We are devoted to deriving the limiting distributions of the LRT…

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We investigate the likelihood ratio test for a large block-diagonal covariance matrix with an increasing number of blocks under the null hypothesis. While so far the likelihood ratio statistic has…

### Directional testing for high-dimensional multivariate normal distributions

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Thanks to its favorable properties, the multivariate normal distribution is still largely employed for modeling phenomena in various scientific fields. However, when the number of components p is of…

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