High-dimensional asymptotic expansion of LR statistic for testing intraclass correlation structure and its error bound

Naohiro Kato, Takayuki Yamada and Yasunori Fujikoshi

Journal of Multivariate Analysis, 2010, vol. 101, issue 1, 101-112

Abstract: This paper deals with the null distribution of a likelihood ratio (LR) statistic for testing the intraclass correlation structure. We derive an asymptotic expansion of the null distribution of the LR statistic when the number of variable p and the sample size N approach infinity together, while the ratio p/N is converging on a finite nonzero limit c[set membership, variant](0,1). Numerical simulations reveal that our approximation is more accurate than the classical [chi]2-type and F-type approximations as p increases in value. Furthermore, we derive a computable error bound for its asymptotic expansion.

Keywords: Asymptotic; expansion; Error; bound; High-dimensional; approximation; Intraclass; correlation; structure; Likelihood; ratio; statistic (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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