NON-PARAMETRIC BAYESIAN INFERENCE FOR INHOMOGENEOUS MARKOV POINT PROCESSES

DOI10.1111/j.1467-842X.2008.00516.xzbMath1337.62298MaRDI QIDQ2810356

Kasper K. Berthelsen, Jesper Møller

Publication date: 1 June 2016

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

zbMATH Keywords

Markov chain Monte Carlohard coreperfect simulationshot noise processpairwise interaction point processauxiliary variable methodpartially ordered Markov point process

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Order statistics; empirical distribution functions (62G30)

Related Items (4)

Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range ⋮ Pairwise interaction function estimation of stationary Gibbs point processes using basis expansion ⋮ Rejection- and importance-sampling-based perfect simulation for Gibbs hard-sphere models ⋮ Modelling Aggregation on the Large Scale and Regularity on the Small Scale in Spatial Point Pattern Datasets

Uses Software

• spatial

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Inhomogeneous Markov point processes by transformation
• MODELLING THE POSITION OF CELL PROFILES ALLOWING FOR BOTH INHOMOGENEITY AND INTERACTION
• A Kernel Method for Smoothing Point Process Data
• Non-parametric Bayesian Estimation of a Spatial Poisson Intensity
• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• Inhomogeneous spatial point processes by location-dependent scaling
• Likelihood and Non‐parametric Bayesian MCMC Inference for Spatial Point Processes Based on Perfect Simulation and Path Sampling
• Shot noise Cox processes
• Hidden Markov Models and Disease Mapping
• Perfect simulation using dominating processes on ordered spaces, with application to locally stable point processes
• Statistics for Spatial Data
• An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
• Simulating normalizing constants: From importance sampling to bridge sampling to path sampling

This page was built for publication: NON-PARAMETRIC BAYESIAN INFERENCE FOR INHOMOGENEOUS MARKOV POINT PROCESSES