San Francisco, California
London, United Kingdom
This tutorial will be delivered by Dr. Max Werner and will run from 12 - 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 workshop 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 workshop, 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.
Numbers are limited so booking via this Eventbrite is essential.
When & Where