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On a likelihood ratio test for independence

Author

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  • Allaire, Jérôme
  • Lepage, Yves

Abstract

The likelihood-ratio (LR) statistic is derived for testing the hypothesis of independence between k subvectors of a normally distributed random vector X against the alternative that exactly s, 2 [less-than-or-equals, slant] s [less-than-or-equals, slant] k, subvectors are dependent. A null asymptotic distribution for the LR statistic is also presented.

Suggested Citation

  • Allaire, Jérôme & Lepage, Yves, 1991. "On a likelihood ratio test for independence," Statistics & Probability Letters, Elsevier, vol. 11(5), pages 449-452, May.
    • Handle: RePEc:eee:stapro:v:11:y:1991:i:5:p:449-452
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    Cited by:

    1. Kojadinovic, Ivan & Holmes, Mark, 2009. "Tests of independence among continuous random vectors based on Cramr-von Mises functionals of the empirical copula process," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1137-1154, July.

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