Modern Statistics for Spatial Point Processes

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156 Citationer (Scopus)

Abstrakt

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.
Udgivelsesdato: DEC
OriginalsprogEngelsk
TidsskriftScandinavian Journal of Statistics
Vol/bind34
Udgave nummer4
Sider (fra-til)643-684
Antal sider42
ISSN0303-6898
DOI
StatusUdgivet - 2007

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