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Central limit theorem for quadratic forms for sparse tables

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  • Burman, Prabir

Abstract

Sufficient conditions for asymptotic normality for quadratic forms in {nt - npt} are given, where {nt} are the observed counts with expected cell means {npt}. The main result is used to derive asymptotic distributions of many statistics including the Pearson's chi-square.

Suggested Citation

  • Burman, Prabir, 1987. "Central limit theorem for quadratic forms for sparse tables," Journal of Multivariate Analysis, Elsevier, vol. 22(2), pages 258-277, August.
    • Handle: RePEc:eee:jmvana:v:22:y:1987:i:2:p:258-277
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    Cited by:

    1. Liero, Hannelore, 2001. "L2-tests for sparse multinomials," Statistics & Probability Letters, Elsevier, vol. 55(2), pages 147-158, November.
    2. Burman, Prabir, 2004. "On some testing problems for sparse contingency tables," Journal of Multivariate Analysis, Elsevier, vol. 88(1), pages 1-18, January.

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