Spatio-temporal determinantal point processes

01/06/2023

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Determinantal point processes are models for regular spatial point patterns, with appealing probabilistic properties. We present their spatio-temporal counterparts and give examples of these models, based on spatio-temporal covariance functions which are separable and non-separable in space and time.

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Spatio-temporal determinantal point processes

On spatial and spatio-temporal multi-structure point process models

Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes

The diffusion-based extension of the Matérn field to space-time

Constructing Large Nonstationary Spatio-Temporal Covariance Models via Compositional Warpings

Doubly stochastic models for replicated spatio-temporal point processes

Testing the first-order separability hypothesis for spatio-temporal point patterns

Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach

Spatio-temporal determinantal point processes

Related Research

On spatial and spatio-temporal multi-structure point process models

Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes

The diffusion-based extension of the Matérn field to space-time

Constructing Large Nonstationary Spatio-Temporal Covariance Models via Compositional Warpings

Doubly stochastic models for replicated spatio-temporal point processes

Testing the first-order separability hypothesis for spatio-temporal point patterns

Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach