Importance analysis with Markov chains
Publication
, Journal Article
Fricks, RM; Trivedi, KS
Published in: Proceedings of the Annual Reliability and Maintainability Symposium
January 1, 2003
An overview is given of novel techniques for computing importance measures in state space dependability models. Specifically, reward functions in a Markov reward model (MRM) are utilized for this purpose, in contrast to the common method of computing importance measures through combinatorial models and structure functions. The advantage of bringing these measures in the context of MRMs is that the mapping extends the applicability of these substantial results of reliability engineering.
Duke Scholars
Published In
Proceedings of the Annual Reliability and Maintainability Symposium
ISSN
0149-144X
Publication Date
January 1, 2003
Start / End Page
89 / 95
Citation
APA
Chicago
ICMJE
MLA
NLM
Fricks, R. M., & Trivedi, K. S. (2003). Importance analysis with Markov chains. Proceedings of the Annual Reliability and Maintainability Symposium, 89–95.
Fricks, R. M., and K. S. Trivedi. “Importance analysis with Markov chains.” Proceedings of the Annual Reliability and Maintainability Symposium, January 1, 2003, 89–95.
Fricks RM, Trivedi KS. Importance analysis with Markov chains. Proceedings of the Annual Reliability and Maintainability Symposium. 2003 Jan 1;89–95.
Fricks, R. M., and K. S. Trivedi. “Importance analysis with Markov chains.” Proceedings of the Annual Reliability and Maintainability Symposium, Jan. 2003, pp. 89–95.
Fricks RM, Trivedi KS. Importance analysis with Markov chains. Proceedings of the Annual Reliability and Maintainability Symposium. 2003 Jan 1;89–95.
Published In
Proceedings of the Annual Reliability and Maintainability Symposium
ISSN
0149-144X
Publication Date
January 1, 2003
Start / End Page
89 / 95