with Aaron King,
an expert of modeling and fitting stochastic dynamic systems
Many interesting scientific questions about biological dynamics can be naturally formulated using partially observed Markov processes (POMPs, AKA state space models or stochastic dynamical systems) and recent theoretical and computational developments make inference on these models possible. This workshop will teach participants how to use the R package pomp to formulate and simulate POMP models, to fit them to data, and to interpret the results. Special emphasis will be on exact and approximate likelihood as the key elements in parameter estimation, hypothesis testing, and model selection. Specifically, the course will cover sequential Monte Carlo and synthetic likelihood techniques.
The workshop will be appropriate for those interested in biological dynamics, infectious disease ecology, inference for stochastic processes, and time series analysis.
DATE & TIME:
Friday, January 25, 2019
8:30 a.m. – 4:30 p.m.
Collaboratorium (IRIC 352)
- Pre-workshop preparation is required.
- Bring your own laptop.
- Participants need not be advanced R users but basic skills in R will be expected.
Please complete the form below to register for The Modeler’s Workshop. Participation is limited to the first 20 registrants. You will receive a confirmation email after you submit this registration form.