Tuesday, May 29, 2018 - 9:00am - 9:50am
Marisa Eisenberg (University of Michigan)
Connecting dynamic models with data to yield insights and predictive results often requires a variety of parameter estimation, identifiability, and uncertainty quantification techniques. These approaches can help to determine what is possible to estimate from a given model and data set, and help guide new data collection. Here, we will discuss different approaches to examining parameter identifiability and uncertainty, and examine how these issues affect parameter estimation and intervention predictions.
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