Petko Yanev (Université de Neuchâtel, Switzerland)

Numerical algorithms for estimating least squares problems
ERGO Optimization day: Thursday 18 August 2005 at 15.00, JCMB 5327

Abstract

The solution of least squares estimation problems is of great importance in the areas of numerical linear algebra, computational statistics and econometrics. The design and analysis of numerically stable and computationally efficient methods for solving such least squares problems is considered. The main computational tool used for the estimation of the least squares solutions is the QR decomposition, or the generalized QR decomposition. Specifically, emphasis is given to the design of sequential and parallel strategies for computing the main matrix factorizations which arise in the estimation procedures. The strategies are based on block-generalizations of the Givens sequences and efficiently exploit the structure of the matrices.

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