Inference in continuous time discrete-state stochastic models: applications in ecology, epidemiology and animal behaviour
University of Edinburgh
School of Mathematics
Statistics seminars, Spring 2010
Friday 12 February, 3:15pm, JCMB 5327 - Glenn Marion (Biomathematics and Statistics Scotland)
"Inference in continuous time discrete-state stochastic models: applications in ecology, epidemiology and animal behaviour"
Abstract
Discrete state-space Markov processes provide a remarkably flexible framework both to describe and infer the behaviour of a broad range of systems. I will outline how to conduct statistically sound parameter estimation for such models when, as is typically the case, only partial observations are available. Key issues and ongoing problems associated with this approach will be illustrated via examples taken from recent work such as: agent-based modelling of ruminant behaviour; the spread of alien plants across the UK; and models of disease spread in experimental crop mixtures. If time permits I will also discuss ongoing work on the applicability of Rissanen's minimum description length principle to model selection for such processes.
Natalia Bochkina n.bochkina@ed.ac.uk
