Parameter Estimation with Covariance Analysis

Application ID: 119161

When estimating the parameters of a multiphysics model, both experimental noise and modeling uncertainties will contribute to corresponding uncertainties in the final parameters estimated. In this verification example, we demonstrate the new Variance functionality in the Parameter Estimation study. This functionality allows you to use experimental variance data as weights in a least-squares optimization, from which the the full parameter covariance matrix and the confidence intervals can be computed.

This model example illustrates applications of this type that would nominally be built using the following products: