Edgeworth expansions for independent bounded integer valued random variables
Edgeworth expansions for independent bounded integer valued random variables
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独立有界整数值随机变量的 Edgeworth 展开
DOI:
10.1016/j.spa.2022.07.001
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发表时间:
2022
影响因子:
1.4
通讯作者:
Hafouta, Yeor
中科院分区:
文献类型:
--
作者:
Dolgopyat, Dmitry;Hafouta, Yeor
We obtain asymptotic expansions for local probabilities of partial sums for uniformly bounded independent but not necessarily identically distributed integer-valued random variables. The expansions involve products of polynomials and trigonometric polynomials. These results also have counterparts for triangular arrays. Our results do not require any additional assumptions. As an application of our expansions we find necessary and sufficient conditions for the classical Edgeworth expansion. It turns out that there are two possible obstructions for the validity of the Edgeworth expansion of order r. First, the distance between the distribution of the underlying partial sums modulo some h∈ N and the uniform distribution could fail to be o (σ N 1− r), where σ N is the standard deviation of the partial sum. Second, this distribution could have the required closeness but this closeness is unstable, in the sense that it could be destroyed by removing finitely many terms. In the first case, the expansion of order r fails. In the second case it may or may not hold depending on the behavior of the derivatives of the characteristic functions of the summands whose removal causes the break-up of the uniform distribution. We also show that a quantitative version of the classical Prokhorov condition (for the strong local central limit theorem) is sufficient for Edgeworth expansions, and moreover this condition is, in some sense, optimal.
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