Gibbs point process approximation: total variation bounds using Stein's method

DOI10.1214/13-AOP895zbMath1322.60060arXiv1207.3096OpenAlexW1964263897MaRDI QIDQ465467

Kaspar Stucki, Dominic Schuhmacher

Publication date: 31 October 2014

Published in: The Annals of Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1207.3096

zbMATH Keywords

Stein's methodbirth-death processtotal variation distanceconditional intensityGibbs point processespairwise interaction process

Mathematics Subject Classification ID

Random fields (60G60) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Branching processes (Galton-Watson, birth-and-death, etc.) (60J80) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (8)

Multivariate Poisson and Poisson process approximations with applications to Bernoulli sums and -statistics ⋮ Structural properties of Gibbsian point processes in abstract spaces ⋮ On the uniqueness of Gibbs distributions with a non-negative and subcritical pair potential ⋮ Bounds for the Probability Generating Functional of a Gibbs Point Process ⋮ The Stein-Dirichlet-Malliavin method ⋮ Poisson-saddlepoint approximation for Gibbs point processes with infinite-order interaction: in memory of Peter Hall ⋮ Functional Poisson approximation in Kantorovich-Rubinstein distance with applications to \(U\)-statistics and stochastic geometry ⋮ Cluster Expansions for GIBBS Point Processes

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