Symmetric Statistics, Poisson Point Processes, and Multiple Wiener Integrals

  • Dynkin E
  • Mandelbaum A
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Abstract

The asymptotic behaviour of symmetric statistics of arbitrary order is studied. Ail an application we describe all limit distributions of square integrable U-statistics. We use as a tool a randomization of the sample size. A sample of Poisson size N_λ, with EN_λ = λ can be interpreted as a Poisson point process with intensity λ, and randomized symmetric statistics are its functionals. As λ → ∞, the probability distribution of these functionals tend to the distribution of multiple Wiener integrals. This can be considered as a stronger form of the following well-known fact: properly normalized, a Poisson point process with intensity λ approaches a Gaussian random measure, as λ → ∞.

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Dynkin, E. B., & Mandelbaum, A. (2007). Symmetric Statistics, Poisson Point Processes, and Multiple Wiener Integrals. The Annals of Statistics, 11(3). https://doi.org/10.1214/aos/1176346241

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