Statistical estimates for the conditioning of linear least squares problems

Abstract : In this paper we are interested in computing linear least squares (LLS) condition numbers to measure the numerical sensitivity of an LLS solution to perturbations in data. We propose a statistical estimate for the norm-wise condition number of an LLS solution where perturbations on data are measured using the Frobenius norm for matrices and the Euclidean norm for vectors. We also explain how condition numbers for the components of an LLS solution can be computed. We present numerical experiments that compare the statistical condition estimates with their corresponding exact values.
Type de document :
Article dans une revue
Lecture notes in computer science, springer, 2014, 8384, pp.124-133. 〈10.1007/978-3-642-55224-3_13〉
Liste complète des métadonnées

https://hal.inria.fr/hal-00991710
Contributeur : Marc Baboulin <>
Soumis le : jeudi 15 mai 2014 - 17:50:31
Dernière modification le : jeudi 11 janvier 2018 - 06:27:11

Identifiants

Citation

Marc Baboulin, Serge Gratton, Rémi Lacroix, Alan J. Laub. Statistical estimates for the conditioning of linear least squares problems. Lecture notes in computer science, springer, 2014, 8384, pp.124-133. 〈10.1007/978-3-642-55224-3_13〉. 〈hal-00991710〉

Partager

Métriques

Consultations de la notice

263