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A general study of extremes of stationary tessellations with examples

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  • Chenavier, Nicolas

Abstract

Let m be a random tessellation in Rd, d≥1, observed in a bounded Borel subset W and f(⋅) be a measurable function defined on the set of convex bodies. A point z(C), called the nucleus of C, is associated with each cell C of m. Applying f(⋅) to all the cells of m, we investigate the order statistics of f(C) over all cells C∈m with nucleus in Wρ=ρ1/dW when ρ goes to infinity. Under a strong mixing property and a local condition on m and f(⋅), we show a general theorem which reduces the study of the order statistics to the random variable f(C), where C is the typical cell of m. The proof is deduced from a Poisson approximation on a dependency graph via the Chen–Stein method. We obtain that the point process {(ρ−1/dz(C),aρ−1(f(C)−bρ)),C∈m,z(C)∈Wρ}, where aρ>0 and bρ are two suitable functions depending on ρ, converges to a non-homogeneous Poisson point process. Several applications of the general theorem are derived in the particular setting of Poisson–Voronoi and Poisson–Delaunay tessellations and for different functions f(⋅) such as the inradius, the circumradius, the area, the volume of the Voronoi flower and the distance to the farthest neighbor.

Suggested Citation

  • Chenavier, Nicolas, 2014. "A general study of extremes of stationary tessellations with examples," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 2917-2953.
  • Handle: RePEc:eee:spapps:v:124:y:2014:i:9:p:2917-2953
    DOI: 10.1016/j.spa.2014.04.009
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    References listed on IDEAS

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    1. Schulte, Matthias & Thäle, Christoph, 2012. "The scaling limit of Poisson-driven order statistics with applications in geometric probability," Stochastic Processes and their Applications, Elsevier, vol. 122(12), pages 4096-4120.
    2. Hsing, Tailen, 1988. "On the extreme order statistics for a stationary sequence," Stochastic Processes and their Applications, Elsevier, vol. 29(1), pages 155-169.
    3. Smith, Richard L., 1988. "Extreme value theory for dependent sequences via the stein-chen method of poisson approximation," Stochastic Processes and their Applications, Elsevier, vol. 30(2), pages 317-327, December.
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    1. Pianoforte, Federico & Schulte, Matthias, 2022. "Criteria for Poisson process convergence with applications to inhomogeneous Poisson–Voronoi tessellations," Stochastic Processes and their Applications, Elsevier, vol. 147(C), pages 388-422.

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