Geometric Anisotropic Spatial Point Pattern Analysis and Cox Processes
From MaRDI portal
Publication:5418634
DOI10.1111/sjos.12041zbMath1416.62547OpenAlexW2098403508MaRDI QIDQ5418634
Publication date: 26 May 2014
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: http://vbn.aau.dk/ws/files/60884357/R_2012_01.pdf
spectral densityBayesian inferencepair correlation functionlog Gaussian Cox processminimum contrast estimationK-functionshot noise Cox processsecond-order intensity-reweighted stationarityWhittle-Matern covariance function
Inference from spatial processes (62M30) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
Related Items
Spatial Cox processes in an infinite-dimensional framework ⋮ A second-order test to detect spatio-temporal anisotropic effects in point patterns ⋮ Multivariate geometric anisotropic Cox processes ⋮ Local spatial log-Gaussian Cox processes for seismic data
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A practical guide to the spectral analysis of spatial point processes
- Asymptotic Palm likelihood theory for stationary point processes
- Going off grid: computationally efficient inference for log-Gaussian Cox processes
- Studies in the history of probability and statistics XLIX On the Matérn correlation family
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- On the Second-Order and Orientation Analysis of Planar Stationary Point Processes
- The second-order analysis of stationary point processes
- Log Gaussian Cox Processes
- Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
- Shot noise Cox processes
- An Introduction to the Theory of Point Processes
- Statistical Analysis and Modelling of Spatial Point Patterns
- Assessing Spatial Point Process Models Using Weighted K-functions: Analysis of California Earthquakes
- Assessing Isotropy for Spatial Point Processes
- The spectral analysis of two-dimensional point processes
