Speaker: Andrea Arnold, North Carolina State University
Bayesian Filtering for Time-Varying Parameter Estimation in Biological Models
Abstract: Many applications in the life sciences involve unknown system parameters that must be estimated using little to no prior information. In particular, some parameters may be known to vary with time with no known evolution model, yet may be subject to certain structural characteristics such as periodicity. We show how nonlinear Bayesian filtering techniques can be employed in this setting to estimate unknown, time-varying parameters, while naturally providing a measure of uncertainty in the estimation. Results are demonstrated using real-world data from several biological applications, including cardiovascular dynamics and the transmission of infectious diseases.Time: Thursday, February 16, 2017, 11:00 - 11:50 a.m.
Department of Mathematical Sciences
George Mason University
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Fairfax, VA 22030-4444
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