Estimation of reliability and its derivatives for large time Horizons in Markovian systems

Perwez Shahabuddin, Marvin K. Nakayama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A number of importance sampling methods have been previously proposed for estimating the system unreliability of highly reliable Markovian systems. These techniques are effective when the time horizon of interest is small. However, for large time horizons, these methods are no longer efficient. We describe a technique in which instead of estimating the actual measure, we estimate bounds on the measure. The bounds can be estimated efficiently, and for large time horizons, they are close to the actual measure. Similar techniques for derivative estimation are also presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 25th Conference on Winter Simulation, WSC 1993
EditorsWilliam E. Biles, Gerald W. Evans, Edward C. Russell, Mansooreh Mollaghasemi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages422-429
Number of pages8
ISBN (Electronic)078031381X
DOIs
StatePublished - Dec 1 1993
Externally publishedYes
Event25th Conference on Winter Simulation, WSC 1993 - Los Angeles, United States
Duration: Dec 12 1993Dec 15 1993

Publication series

NameProceedings - Winter Simulation Conference
VolumePart F129590
ISSN (Print)0891-7736

Other

Other25th Conference on Winter Simulation, WSC 1993
CountryUnited States
CityLos Angeles
Period12/12/9312/15/93

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications

Keywords

  • Derivative estimation
  • Importance sampling
  • Likelihood ratios
  • Markov chains
  • Regenerative systems
  • Reliability
  • Variance reduction

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