Anisotropic log Gaussian Cox processes using normal variance mixture covariance function

Anisotropic log Gaussian Cox processes using normal variance mixture covariance function

In this paper, we introduce a new family of anisotropic log Gaussian Cox processes (LGCPs) that is useful to model spatial anisotropic point patterns that depict a degree of clustering. Our idea lies in building a new family of anisotropic LGCP using the normal variance mixture covariance function. We describe the moment properties of our new model. Finally, the estimation procedure is evaluated through a simulation study.