88
Views
2
CrossRef citations to date
0
Altmetric
Articles

Sensitivity analysis for the generalized Cholesky block downdating problem

&
Pages 997-1022 | Received 01 May 2019, Accepted 11 Mar 2020, Published online: 09 Apr 2020
 

Abstract

In this article, first we will present the new rigorous perturbation bounds with normwise perturbation for the generalized Cholesky block downdating problem by combining the unified matrix–vector equation approach with the method of Lyapunov majorant functions and the Banach fixed point theorem. Then, we will derive the explicit expressions for the six distinct kinds of condition numbers, i.e. four normwise ones, mixed and componentwise ones. Furthermore, with the help of probabilistic spectral norm estimator and the small-sample statistical condition estimation method, these condition numbers can be estimated with high accuracy. At the end, the obtained results are illuminated by the numerical examples.

AMS classification (2010):

Acknowledgements

The authors would like to thanks the editor and the two anonymous referees for their helpful comments for improving the manuscript. They would also like to acknowledge Prof. Michiel E. Hochstenbach and Prof. Hanyu Li for providing the MATLAB program of probabilistic spectral norm estimator.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work is supported by the National Natural Science Foundation of China (Grant Numbers 11671060, 11571062, and 11771062).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 670.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.