Stein's method and Poisson process approximation for a class of Wasserstein metrics

D. Schuhmacher

    Research output: Contribution to journalArticle

    5 Citations (Scopus)


    Based on Stein’s method, we derive upper bounds for Poisson process approximation in the L1-Wasserstein metric d2(p), which is based on a slightly adapted Lp-Wasserstein metric between point measures. For the case p=1, this construction yields the metric d2 introduced in [Barbour and Brown Stochastic Process. Appl. 43 (1992) 9–31], for which Poisson process approximation is well studied in the literature. We demonstrate the usefulness of the extension to general p by showing that d2(p)-bounds control differences between expectations of certain pth order average statistics of point processes. To illustrate the bounds obtained for Poisson process approximation, we consider the structure of 2-runs and the hard core model as concrete examples.
    Original languageEnglish
    Pages (from-to)550-568
    Issue number2
    Publication statusPublished - 2009


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