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Kolmogorov bounds for decomposable random variables and subgraph counting by the Stein-Tikhomirov method

2021/07/08 by Peter Eichelsbacher, Eichelsbacher, Peter, Benedikt Rednoß +1
Computer Science · Mathematics · #05C80 #60E10 #60F05 #FOS: Mathematics #Probability (math.PR) #Random Matrices and Applications #Stochastic processes and statistical mechanics #Topological and Geometric Data Analysis

paper · pdf · doi:10.48550/arxiv.2107.03775

openalex publication_date 2021/07/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In his work \citeTi80, Tikhomirov combined elements of Stein's method with the theory of characteristic functions to derive Kolmogorov bounds for the convergence rate in the central limit theorem for a normalized sum of a stationary sequence of random variables satisfying one of several weak dependency conditions. The combination of elements of Stein's method with the theory of characteristic functions is sometimes called Stein-Tikhomirov method. \citet*AMPS17 successfully used the Stein-Tikhomirov method to bound the convergence rate in contexts with non-Gaussian targets. \citet*Ro17 used the Stein-Tikhomirov method to bound the convergence rate in the Kolmogorov distance for normal approximation of normalized triangle counts in the Erdös-Rényi random graph.

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