Modern Statistics for Spatial Point Processes*
Year: 2007
Type: article
Abstract: . We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs and Cox process models, diagnostic tools and model checking, Markov chain Monte Carlo algorithms, computational methods for likelihood‐based inference, and quick non‐likelihood approaches to inference.
Authors: JESPER MØLLER, RASMUS P. WAAGEPETERSEN
Institution: Aalborg University
Language: English
Subfield: Applied Mathematics
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2142477181