Statistical condition estimation for linear least squares

被引：26

作者：

Kenney, CS ^{[1
]}

Laub, AJ ^{[1
]}

Reese, MS ^{[1
]}

机构：

[1] Univ Calif Santa Barbara, Dept Elect & Comp Engn, Santa Barbara, CA 93106 USA

来源：

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS | 1998年 / 19卷 / 04期

关键词：

conditioning; sensitivity; linear least squares;

D O I：

10.1137/S0895479895291935

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Statistical condition estimation is applied to the linear least squares problem. The method obtains componentwise condition estimates via the Frechet derivative. A rigorous statistical theory exists that determines the probability of accuracy in the estimates. The method is as computationally efficient as normwise condition estimation methods, and it is easily adapted to respect structural constraints on perturbations of the input data. Several examples illustrate the method.

引用

页码：906 / 923

页数：18

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