On Parameter Estimation for Pairwise Interaction Point Processes

DOI10.2307/1403548zbMath0829.62093OpenAlexW1965718516MaRDI QIDQ4850141

Masaharu Tanemura, Thomas Fiksel, Dietrich Stoyan, P. Grabarnik, Yosihiko Ogata, Peter J. Diggle

Publication date: 14 November 1995

Published in: International Statistical Review / Revue Internationale de Statistique (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/1403548

zbMATH Keywords

boundary conditionsmaximum likelihoodGibbs distributionreviewpseudo-likelihoodpotential functionspatial point patternsinteraction functionTakacs-Fiksel methodpairwise interaction point processMarkov point processcomparative simulation study

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Markov processes: estimation; hidden Markov models (62M05) Statistical tables (62Q05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (10)

Takacs-Fiksel Method for Stationary Marked Gibbs Point Processes ⋮ Area-interaction point processes ⋮ Bayesian modeling on continuously marked spatial point patterns ⋮ Fast approximation of the intensity of Gibbs point processes ⋮ Sample-based Maximum Likelihood Estimation of the Autologistic Model ⋮ Bayesian inference for spatially inhomogeneous pairwise interacting point processes ⋮ A method for approximate fully bayesian analysis of parameters ⋮ Adjusted composite likelihood ratio test for spatial Gibbs point processes ⋮ Asymptotic Properties of Takacs-Fiksel Estimation Method for GIBBS Point Processes ⋮ Pseudo-likelihood approach for gibbs point processes in connection with field observations

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