Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A note on the test for the covariance matrix under normality

  • Received : 2017.10.11
  • Accepted : 2017.12.05
  • Published : 2018.01.31
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Abstract

In this study, we consider the likelihood ratio test for the covariance matrix of the multivariate normal data. For this, we propose a method for obtaining null distributions of the likelihood ratio statistics by the Monte-Carlo approach when it is difficult to derive the exact null distributions theoretically. Then we compare the performance and precision of distributions obtained by the asymptotic normality and the Monte-Carlo method for the likelihood ratio test through a simulation study. Finally we discuss some interesting features related to the likelihood ratio test for the covariance matrix and the Monte-Carlo method for obtaining null distributions for the likelihood ratio statistics.

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References

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