Spatio-temporal determinantal point processes

TL;DR

This paper introduces spatio-temporal determinantal point processes, extending their spatial models to account for both space and time, with examples based on various covariance functions.

Contribution

It develops the theoretical framework for spatio-temporal determinantal point processes and provides examples using separable and non-separable covariance functions.

Findings

Models for regular spatial point patterns extended to space-time.

Examples include separable and non-separable covariance functions.

Foundation for future applications in spatio-temporal data analysis.

Abstract

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.