Likelihood ratio tests for many groups in high dimensions

Holger Dette and Nina Dörnemann

Journal of Multivariate Analysis, 2020, vol. 178, issue C

Abstract: In this paper, we investigate the asymptotic distribution of likelihood ratio tests in models with several groups, when the number of groups converges with the dimension and sample size to infinity. We derive central limit theorems for the logarithm of various test statistics and compare our results with the approximations obtained from a central limit theorem where the number of groups is fixed.

Keywords: High-dimensional inference; Likelihood ratio test (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.jmva.2020.104605

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