The influence of numerical error on parameter estimation and uncertainty quantification for advective PDE models.

ABSTRACT: Advective partial differential equations can be used to describe many scientific processes. Two significant sources of error that can cause difficulties in inferring parameters from experimental data on these processes include (i) noise from the measurement and collection of experimental data and (ii) numerical error in approximating the forward solution to the advection equation. How this second source of error alters parameter estimation and uncertainty quantification during an inverse problem methodology is not well understood. As a step towards a better understanding of this problem, we present both analytical and computational results concerning how a least squares cost function and parameter estimator behave in the presence of numerical error in approximating solutions to the underly

SUBMITTER: Nardini JT 

PROVIDER: S-EPMC8191598 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature