Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-04-30T19:09:50.073Z Has data issue: false hasContentIssue false

Extremes for the inradius in the Poisson line tessellation

Published online by Cambridge University Press:  10 June 2016

Nicolas Chenavier*
Affiliation:
Université du Littoral Côte d'Opale
Ross Hemsley*
Affiliation:
Inria
*
* Postal address: LMPA Joseph Liouville, Université du Littoral Côte d'Opale, 50 rue Ferdinand Buisson, BP 699, F-62228 Calais Cedex, France. Email address: nicolas.chevavier@lmpa.univ-littoral.fr
** Postal address: Inria, BP 93, 06902 Sophia-Antipolis Cedex, France.

Abstract

A Poisson line tessellation is observed in the window Wρ := B(0, π-1/2ρ1/2) for ρ > 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest ball contained in the cell. Using the Poisson approximation, we compute the limit distributions of the largest and smallest order statistics for the inradii of all cells whose nuclei are contained in Wρ as ρ goes to ∞. We additionally prove that the limit shape of the cells minimising the inradius is a triangle.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1]Beermann, M.,Redenbach, C. and Thäle, C. (2014).Asymptotic shape of small cells.Math. Nachr. 287,737747.Google Scholar
[2]Calka, P. (2003).Precise formulae for the distributions of the principal geometric characteristics of the typical cells of a two-dimensional Poisson–Voronoi tessellation and a Poisson line process.Adv. Appl. Prob. 35,551562.CrossRefGoogle Scholar
[3]Calka, P. and Chenavier, N. (2014).Extreme values for characteristic radii of a Poisson–Voronoi tessellation.Extremes 17,359385.CrossRefGoogle Scholar
[4]Charikar, M. S. (2002).Similarity estimation techniques from rounding algorithms. In Proceedings of the Thirty-Fourth Annual ACM Symposium on Theory of Computing,ACM,New York, pp.380388.Google Scholar
[5]Chenavier, N. (2014).A general study of extremes of stationary tessellations with examples.Stoch. Process. Appl. 124,29172953.CrossRefGoogle Scholar
[6]De Haan, L. and Ferreira, A. (2006).Extreme Value Theory: An Introduction.Springer,New York.Google Scholar
[7]Goudsmit, S. (1945).Random distribution of lines in a plane.Rev. Modern Phys. 17,321322.Google Scholar
[8]Heinrich, L. (2009).Central limit theorems for motion-invariant Poisson hyperplanes in expanding convex bodies.Rend. Circ. Mat. Palermo (2) Suppl. 81,187212.Google Scholar
[9]Heinrich, L.,Schmidt, H. and Schmidt, V. (2006).Central limit theorems for Poisson hyperplane tessellations.Ann. Appl. Prob. 16,919950.Google Scholar
[10]Hsing, T. (1988).On the extreme order statistics for a stationary sequence.Stoch. Process. Appl. 29,155169.CrossRefGoogle Scholar
[11]Hug, D. and Schneider, R. (2014).Approximation properties of random polytopes associated with Poisson hyperplane processes.Adv. Appl. Prob. 46,919936.CrossRefGoogle Scholar
[12]Hug, D.,Reitzner, M. and Schneider, R. (2004).The limit shape of the zero cell in a stationary Poisson hyperplane tessellation.Ann. Prob. 32,11401167.Google Scholar
[13]Ju, L.,Gunzburger, M. and Zhao, W. (2006).Adaptive finite element methods for elliptic PDEs based on conforming centroidal Voronoi–Delaunay triangulations.SIAM J. Sci. Comput. 28,20232053.Google Scholar
[14]Leadbetter, M. R. (1974).On extreme values in stationary sequences.Z. Wahrscheinlichkeitsth. 28,289303.Google Scholar
[15]Leadbetter, M. R. and Rootzén, H. (1998).On extreme values in stationary random fields. In Stochastic Processes and Related Topics,Birkhäuser,Boston, MA, pp.275285.CrossRefGoogle Scholar
[16]Miles, R. E. (1964).Random polygons determined by random lines in a plane.Proc. Nat. Acad. Sci. USA 52,901907.Google Scholar
[17]Miles, R. E. (1964).Random polygons determined by random lines in a plane. II.Proc. Nat. Acad. Sci. USA 52,11571160.Google Scholar
[18]Møller, J. and Waagepetersen, R. P. (2004).Statistical Inference and Simulation for Spatial Point Processes (Monogr. Statist. Appl. Prob.100).Chapman & Hall/CRC,Boca Raton, FL.Google Scholar
[19]Penrose, M. (2003).Random Geometric Graphs.Oxford Univeristy Press.Google Scholar
[20]Plan, Y. and Vershynin, R. (2014).Dimension reduction by random hyperplane tessellations.Discrete Comput. Geometry 51,438461.Google Scholar
[21]Resnick, S. I. (1987).Extreme Values, Regular Variation, and Point Processes.Springer,New York.Google Scholar
[22]Santaló, L. A. (2004).Integral Geometry and Geometric Probability,2nd edn.Cambridge University Press.Google Scholar
[23]Schneider, R. and Weil, W. (2008).Stochastic and Integral Geometry.Springer,Berlin.Google Scholar
[24]Schulte, M. and Thäle, C. (2012).The scaling limit of Poisson-driven order statistics with applications in geometric probability.Stoch. Process. Appl. 122,40964120.Google Scholar
[25]Schulte, M. and Thäle, C. (2016).Poisson point process convergence and extreme values in stochastic geometry. In Stochastic Analysis for Poisson Point Processes: Malliavin Calculus, Wiener–Itô Chaos Expansions and Stochastic Geometry,Springer,Cham.Google Scholar