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Quantifying Uncertainty in Model Predictions

Presented by: 
A Lloyd North Carolina State University
Date: 
Wednesday 21st August 2013 - 11:00 to 11:30
Venue: 
INI Seminar Room 1
Session Title: 
Experimental Design and Inference
Abstract: 
Quantifying uncertainty in a model's predictions is crucial if we are to have faith in those predictions. Uncertainties arise from a number of sources, including uncertainty in the values of the model's parameters (parametric uncertainty), uncertainty in the structure of the model and stochasticity in the model's dynamics. In this talk I will discuss and apply a number of uncertainty quantification (UQ) techniques to simple disease transmission models.
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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons