Stein's method for the half-normal distribution with applications to limit theorems related to the simple symmetric random walk

preprint2015arXivOpen access

Abstract

We develop Stein's method for the half-normal distribution and apply it to derive rates of convergence in distributional limit theorems for three statistics of the simple symmetric random walk: the maximum value, the number of returns to the origin and the number of sign changes up to a given time nn. We obtain explicit error bounds with the optimal rate n−1/2n^{-1/2} for both the Kolmogorov and the Wasserstein metric. In order to apply Stein's method, we compare the characterizing operator of the limiting half-normal distribution with suitable characterizations of the discrete approximating distributions, exploiting a recent technique by Goldstein and Reinert \cite{GolRei13}.

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