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Slow Convergence in Generalized Central Limit Theorems

Probability 2018-04-24 v3 Mathematical Physics math.MP

Abstract

We study the central limit theorem in the non-normal domain of attraction to symmetric α\alpha-stable laws for 0<α20<\alpha\leq2. We show that for i.i.d. random variables XiX_i, the convergence rate in LL^\infty of both the densities and distributions of inXi/(n1/αL(n))\sum_i^n X_i/(n^{1/\alpha}L(n)) is at best logarithmic if LL is a non-trivial slowly varying function. Asymptotic laws for several physical processes have been derived using central limit theorems with nlogn\sqrt{n\log n} scaling and Gaussian limiting distributions. Our result implies that such asymptotic laws are accurate only for exponentially large nn.

Keywords

Cite

@article{arxiv.1711.03456,
  title  = {Slow Convergence in Generalized Central Limit Theorems},
  author = {Christoph Börgers and Claude Greengard},
  journal= {arXiv preprint arXiv:1711.03456},
  year   = {2018}
}

Comments

To appear in Comptes Rendus de l'Acad\'emie des Sciences, Math\'ematiques

R2 v1 2026-06-22T22:41:11.326Z