Regression on parametric manifolds: Estimation of spatial fields, functional outputs, and parameters from noisy data

DOI10.1016/j.crma.2012.05.002zbMath1245.65010OpenAlexW1993231584MaRDI QIDQ432694

Einar M. Rønquist, Anthony T. Patera

Publication date: 4 July 2012

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1721.1/99385

zbMATH Keywords

parameter estimationconfidence intervalsregressionempirical interpolation methodleast-squares formulation

Mathematics Subject Classification ID

Related Items (5)

A model-data weak formulation for simultaneous estimation of state and model bias ⋮ A reduced basis Kalman filter for parametrized partial differential equations ⋮ Functional Regression for State Prediction Using Linear PDE Models and Observations ⋮ Gaussian functional regression for linear partial differential equations ⋮ The generalized empirical interpolation method: stability theory on Hilbert spaces with an application to the Stokes equation

Cites Work

• An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
• Estimation techniques for distributed parameter systems
• A ‘best points’ interpolation method for efficient approximation of parametrized functions
• Unnamed Item

This page was built for publication: Regression on parametric manifolds: Estimation of spatial fields, functional outputs, and parameters from noisy data