We propose a local version of the spatio-temporal log-Gaussian Cox processes (LGCPs) employing the Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure to obtain space as well as time-varying parameters. We resort to the joint minimum contrast method fitting method to estimate the set of second-order parameters for the class of spatio-temporal LGCPs. This approach has the advantage of being usable in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field (GRF).

Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu (2022). Locally weighted spatio-temporal minimum contrast for Log-Gaussian Cox Processes. In Proceedings of the 10th International Workshop on Spatio-Temporal Modelling (pp. 173-178).

Locally weighted spatio-temporal minimum contrast for Log-Gaussian Cox Processes

Nicoletta D'Angelo
;
Giada Adelfio;
2022-01-01

Abstract

We propose a local version of the spatio-temporal log-Gaussian Cox processes (LGCPs) employing the Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure to obtain space as well as time-varying parameters. We resort to the joint minimum contrast method fitting method to estimate the set of second-order parameters for the class of spatio-temporal LGCPs. This approach has the advantage of being usable in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field (GRF).
2022
Settore SECS-S/01 - Statistica
978-84-9144-364-3
Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu (2022). Locally weighted spatio-temporal minimum contrast for Log-Gaussian Cox Processes. In Proceedings of the 10th International Workshop on Spatio-Temporal Modelling (pp. 173-178).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/555745
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