Campbell equilibrium equation and pseudo-likelihood estimation for non-hereditary Gibbs point processes

DOI10.3150/09-BEJ198zbMath1200.62023arXiv0709.1801MaRDI QIDQ605901

David Dereudre, Frédéric Lavancier

Publication date: 15 November 2010

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0709.1801

zbMATH Keywords

consistencyspatial statisticsCampbell measureGibbs point processpseudo-likelihood estimatornon-hereditary interaction

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (6)

Takacs-Fiksel Method for Stationary Marked Gibbs Point Processes ⋮ Variational estimators for the parameters of Gibbs point process models ⋮ Inference for low‐ and high‐dimensional inhomogeneous Gibbs point processes ⋮ Asymptotic properties of the maximum pseudo-likelihood estimator for stationary Gibbs point processes including the Lennard-Jones model ⋮ Practical simulation and estimation for Gibbs Delaunay-Voronoi tessellations with geometric hardcore interaction ⋮ Existence of Gibbsian point processes with geometry-dependent interactions

Uses Software

• pyuvdata

Cites Work

• Unnamed Item
• Unnamed Item
• Pseudolikelihood for exponential family models of spatial point processes
• Random fields
• Canonical Gibbs measures. Some extensions of de Finetti's representation theorem for interacting particle systems
• On asymptotic normality of pseudo likelihood estimates for pairwise interaction processes
• Consistency of the maximum pseudo-likelihood estimator of continuous state space Gibbsian processes
• Maximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes
• Gibbs Delaunay tessellations with geometric hardcore conditions
• Superstable interactions in classical statistical mechanics
• Integral and Differential Characterizations of the GIBBS Process
• Likelihood and Non‐parametric Bayesian MCMC Inference for Spatial Point Processes Based on Perfect Simulation and Path Sampling
• Exact sampling with coupled Markov chains and applications to statistical mechanics
• Existence of ‘nearest-neighbour’ spatial Gibbs models
• Residual Analysis for Spatial Point Processes (with Discussion)

This page was built for publication: Campbell equilibrium equation and pseudo-likelihood estimation for non-hereditary Gibbs point processes