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In this article, we propose a nonparametric approach for estimating the intensity function of temporal point processes based on kernel estimators. In particular, we use asymmetric kernel estimators characterized by the gamma distribution, in order to describe features of observed point patterns adequately. Some characteristics of these estimators are analyzed and discussed both through simulated results and applications to real data from different seismic catalogs. 相似文献
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The paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.
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Adelfio Giada Agosto Arianna Chiodi Marcello Giudici Paolo 《Statistical Methods and Applications》2021,30(2):665-688
Statistical Methods & Applications - We propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The... 相似文献
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