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Computing Covariance Matrices for Constrained Nonlinear Large Scale Parameter Estimation Problems Using Krylov Subspace Methods

  • Ekaterina KostinaEmail author
  • Olga Kostyukova
Chapter
Part of the International Series of Numerical Mathematics book series (ISNM, volume 160)

Abstract

In the paper we show how, based on the preconditioned Krylov subspace methods, to compute the covariance matrix of parameter estimates, which is crucial for efficient methods of optimum experimental design.

Keywords

Constrained parameter estimation covariance matrix of parameter estimates optimal experimental design nonlinear equality constraints iterative matrix methods preconditioning 

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© Springer Basel AG 2012

Authors and Affiliations

  1. 1.University of MarburgMarburgGermany
  2. 2.Institute of MathematicsBelarus Academy of SciencesMinskBelarus

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