Cox point processes: why one realisation is not enough. (English) Zbl 07763648
Summary: We review a rich class of point process models, Cox point processes, and illustrate the necessity of more than one observation (point patterns) in performing parameter estimation. Furthermore, we introduce a new Cox point process model by treating the intensity function of the underlying Poisson point process as a random mixture of normal components. The behaviour and performance of the new model are compared with those of popular Cox point process models. The new model is exemplified with an application that involves a single point pattern corresponding to earthquake events in California, USA.
{© 2018 The Authors. International Statistical Review © 2018 International Statistical Institute}
{© 2018 The Authors. International Statistical Review © 2018 International Statistical Institute}
MSC:
| 62-XX | Statistics |
Keywords:
Cox point process; earthquake modelling; mixture models; Poisson point process; random intensity functionReferences:
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