‌‌‌Abstract

This tutorial will be delivered by Dr. Max Werner and will run from 12 pm - 2 pm. Point processes are a class of stochastic models that are convenient for modelling discrete random events in space and/or time. In contrast to models that represent the underlying process, point processes are a simple and flexible alternative that can be calibrated directly to the empirical statistics of the considered points. Applications range from earth sciences (earthquakes, volcanic eruptions, rainfall, wildfires) via neuroscience and ecology to engineering (communications, queuing theory), particle physics, finance and social sciences. This tutorial will provide a hands-on introduction to modelling with point processes, including parameter estimation, model selection and simulation. To help you get started, we will use existing point process software to analyse and model sample data sets in the classroom. At the end of the tutorial, you will be able to:

* identify opportunities for stochastic modelling using point processes;

*use existing R packages for parameter estimation of basic temporal point processes; perform model selection using likelihood-based approaches;

*simulate from simple processes;

* perform simple spatial modelling; and find resources for further information, both applied and theoretical.

Registration

Numbers are limited so booking via Eventbrite is essential. 

'Methods and Tools for Uncertainty Analysis of Numerical Models' tutorial series

This tutorial is part of a series of interactive tutorials‌ starting in October 2015 to bring together researchers at the University of Bristol from different faculties to share methods and tools for model uncertainty analysis.

Researchers will come away from the tutorial with resources to apply the methods and tools in their discipline.

Tutorials will include discussions, demonstrations and opportunities for networking. Resources such as papers, software and contacts will be provided so that participants can explore the method or tool in more details based on their application.

Tutorials are open to doctoral students, postgraduates, early career and established researchers.