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Conditional distribution of heavy tailed random variables on large deviations of their sum

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  • Armendáriz, Inés
  • Loulakis, Michail

Abstract

It is known that large deviations of sums of subexponential random variables are most likely realised by deviations of a single random variable. In this article we give a detailed picture of how subexponential random variables are distributed when a large deviation of the sum is observed.

Suggested Citation

  • Armendáriz, Inés & Loulakis, Michail, 2011. "Conditional distribution of heavy tailed random variables on large deviations of their sum," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1138-1147, May.
    • Handle: RePEc:eee:spapps:v:121:y:2011:i:5:p:1138-1147
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    Cited by:

    1. Vogel, Quirin, 2023. "Emergence of interlacements from the finite volume Bose soup," Stochastic Processes and their Applications, Elsevier, vol. 166(C).
    2. Armendáriz, Inés & Grosskinsky, Stefan & Loulakis, Michail, 2013. "Zero-range condensation at criticality," Stochastic Processes and their Applications, Elsevier, vol. 123(9), pages 3466-3496.
    3. Lehtomaa, Jaakko, 2015. "Limiting behaviour of constrained sums of two variables and the principle of a single big jump," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 157-163.
    4. Søren Asmussen & Jaakko Lehtomaa, 2017. "Distinguishing Log-Concavity from Heavy Tails," Risks, MDPI, vol. 5(1), pages 1-14, February.

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