A local version of spatio-temporal log-Gaussian Cox processes is proposed by using Local Indicators of Spatio-Temporal Association (LISTA) functions plugged into the minimum contrast procedure, to obtain space as well as time-varying parameters. The new procedure resorts to the joint minimum contrast fitting method to estimate the set of second-order parameters. This approach has the advantage of being suitable in both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. Simulation studies to assess the performance of the proposed fitting procedure are presented, and an application to seismic spatio-temporal point pattern data is shown.

Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu (2023). Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 180 [10.1016/j.csda.2022.107679].

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

Nicoletta D'Angelo
;
Giada Adelfio;Jorge Mateu
2023-01-01

Abstract

A local version of spatio-temporal log-Gaussian Cox processes is proposed by using Local Indicators of Spatio-Temporal Association (LISTA) functions plugged into the minimum contrast procedure, to obtain space as well as time-varying parameters. The new procedure resorts to the joint minimum contrast fitting method to estimate the set of second-order parameters. This approach has the advantage of being suitable in both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. Simulation studies to assess the performance of the proposed fitting procedure are presented, and an application to seismic spatio-temporal point pattern data is shown.
Settore SECS-S/01 - Statistica
Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu (2023). Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 180 [10.1016/j.csda.2022.107679].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/575469
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