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Conditions for equality in Anderson’s theorem

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  • Bočinec, Filip
  • Nagy, Stanislav

Abstract

The classical Anderson theorem is a well-known result relevant to multivariate statistics and probability. It establishes an integral inequality for symmetric quasiconcave functions over a shifted symmetric convex set. The aim of this note is twofold. First, we provide necessary and sufficient conditions for equality in Anderson’s theorem, extending the result of Soms (1991). Second, we propose a set of tractable requirements that guarantee strict inequality in Anderson’s theorem. Our results are used to characterize the independence of Gaussian-distributed random variables.

Suggested Citation

  • Bočinec, Filip & Nagy, Stanislav, 2024. "Conditions for equality in Anderson’s theorem," Statistics & Probability Letters, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:stapro:v:209:y:2024:i:c:s0167715224000634
    DOI: 10.1016/j.spl.2024.110094
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    References listed on IDEAS

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    1. Peter L. Cohen & Colin B. Fogarty, 2022. "Gaussian prepivoting for finite population causal inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 295-320, April.
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