Abstract
Deviation probabilities of the sum Sn = X1 + ⋯ + Xn of independent and identically distributed real-valued random variables have been extensively investigated, in particular when X1 is Weibull-like distributed, i.e. \(\log \mathbb {P}(X\geqslant x) \sim -qx^{1-\epsilon }\) as x →∞. For instance, A.V. Nagaev formulated exact asymptotic results for \(\mathbb {P}(S_n>x_n)\) when xn > n1∕2 (see, A.V. Nagaev, 1969). In this paper, we derive rough asymptotic results (at logarithmic scale) with shorter proofs relying on classical tools of large deviation theory and giving an explicit formula for the rate function at the transition xn = Θ(n1∕(1+𝜖)).
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We would like to thank the referee for his comments and his suggestions which pushed us to make some proofs clearer and shorter.
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Brosset, F., Klein, T., Lagnoux, A., Petit, P. (2022). Large Deviations at the Transition for Sums of Weibull-Like Random Variables. In: Donati-Martin, C., Lejay, A., Rouault, A. (eds) Séminaire de Probabilités LI. Lecture Notes in Mathematics(), vol 2301. Springer, Cham. https://doi.org/10.1007/978-3-030-96409-2_8
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