\(L^1\) bounds in normal approximation

DOI10.1214/009117906000001123zbMath1144.60018arXiv0710.3262OpenAlexW3103517063MaRDI QIDQ2456032

Larry Goldstein

Publication date: 17 October 2007

Published in: The Annals of Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0710.3262

zbMATH Keywords

samplingStein's methodcone measureBerry-EsseenWassersteincombinatorial CLTFortet-Mourierzero bias distribution

Mathematics Subject Classification ID

Geometric probability and stochastic geometry (60D05) Central limit and other weak theorems (60F05) Combinatorial probability (60C05) (L^p)-limit theorems (60F25)

Related Items (18)

Convergence in total variation to a mixture of Gaussian laws ⋮ Zero biasing and a discrete central limit theorem ⋮ On the Accuracy in a Combinatorial Central Limit Theorem: The Characteristic Function Method ⋮ The Berry-Esseen bound for identically distributed random variables by Stein method ⋮ Zero bias enhanced Stein couplings ⋮ Optimal bounds in normal approximation for many interacting worlds ⋮ ON THE MAGNITUDE AND INTRINSIC VOLUMES OF A CONVEX BODY IN EUCLIDEAN SPACE ⋮ Zero bias transformation and asymptotic expansions ⋮ New rates for exponential approximation and the theorems of Rényi and Yaglom ⋮ Degree asymptotics with rates for preferential attachment random graphs ⋮ Quenched central limit theorem in a corner growth setting ⋮ Stein's method and zero bias transformation for CDO tranche pricing ⋮ Stein's method via induction ⋮ Bounds on the constant in the mean central limit theorem ⋮ Zero Biasing and Jack Measures ⋮ Unnamed Item ⋮ On the error bound in a combinatorial central limit theorem ⋮ Relaxing the Gaussian assumption in shrinkage and SURE in high dimension

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