Generalised additive point process models for natural hazard occurrence

A review of earthquake occurrence models for seismic hazard analysis

A large number of probabilistic earthquake occurrence models are currently available for seismic hazard assessment. This paper reviews the basic assumptions of the various models, summarizes their stochastic representations and discusses the parameters needed for applications. While the Poisson model is one of the most commonly used in practice it is limited in its representation of the physica...

Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus

There are several statistical methods for time-to-event analysis, among which is the Cox proportional hazards model that is most commonly used. However, when the absolute change in risk, instead of the risk ratio, is of primary interest or when the proportional hazard assumption for the Cox proportional hazards model is violated, an additive hazard regression model may be more appropriate. In t...

Continuous-Time Versus Discrete-Time Point Process Models for Rainfall Occurrence Series

Several authors have had apparent success in applying continuous-time point process models to rainfall occurrence sequences. In this paper, it is shown that if rainfall occurrences are interpreted as the events of a point process (and not as a censored sample), the continuous-time point process methodology and estimation procedures are not directly applicable since they fail to account for the ...

Local generalised method of moments: an application to point process‐based rainfall models

Long series of simulated rainfall are required at point locations for a range of applications, including hydrological studies. Clustered point process-based rainfall models have been used for generating such simulations for many decades. These models suffer from a major limitation, however: their stationarity. Although seasonality can be allowed by fitting separate models for each calendar mont...

Automatic nonlinear fitting of additive and generalised additive models with wavelets