Friday, February 12, 2016, 11h00
Location: Delta Classroom, Quelhas' Building, ISEG
In this talk, we address the treatment of uncertainty in different types of mathematical models: continuous dynamical systems, discrete mathematical models and stochastic models.
First, we analyse how uncertainty evolves in a continuous dynamical system modeled by differential equations. Then, we apply Bayesian techniques to processes of calibration in discrete mathematical models. Finally, we quantify parameters' uncertainty in stochastic models. Case studies will be presented and will be discussed for each modelling approach. Additionally, classical statistical techniques applied in different areas will be shown.