Log Gaussian Cox Processes
Copyright policy )Log Gaussian Cox Processes
Planar Cox processes directed by a log Gaussian intensity process are investigated in the univariate and multivariate cases. The appealing properties of such models are demonstrated theoretically as well as through data examples and simulations. In particular, the first, second and third‐order properties are studied and utilized in the statistical analysis of clustered point patterns. Also empirical Bayesian inference for the underlying intensity surface is considered.
- Aalborg University Denmark
- Aalborg University Library (AUB) Denmark
- Aarhus University Denmark
- Norwegian University of Science and Technology Norway
Neyman-Scott processes, empirical Bayesian inference, Random fields, spatial point processes, Point processes (e.g., Poisson, Cox, Hawkes processes), multivariate Cox processes, parameter estimation
Neyman-Scott processes, empirical Bayesian inference, Random fields, spatial point processes, Point processes (e.g., Poisson, Cox, Hawkes processes), multivariate Cox processes, parameter estimation
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