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Compound Poisson approximation in systems reliability


Barbour, A D; Chryssaphinou, Ourania; Roos, Malgorzata (1996). Compound Poisson approximation in systems reliability. Naval Research Logistics, 43(2):251-264.

Abstract

The compound Poisson "local" formulation of the Stein-Chen method is applied to problems in reliability theory. Bounds for the accuracy of the approximation of the reliability by an appropriate compound Poisson distribution are derived under fairly general conditions, and are applied to consecutive-2 and connected-s systems, and the 2-dimensional consecutive-k-out-ofn system, together with a pipeline model. The approximations are usually better than the Poisson "local" approach would give.

The compound Poisson "local" formulation of the Stein-Chen method is applied to problems in reliability theory. Bounds for the accuracy of the approximation of the reliability by an appropriate compound Poisson distribution are derived under fairly general conditions, and are applied to consecutive-2 and connected-s systems, and the 2-dimensional consecutive-k-out-ofn system, together with a pipeline model. The approximations are usually better than the Poisson "local" approach would give.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:610 Medicine & health
510 Mathematics
Language:English
Date:1996
Deposited On:16 Nov 2009 13:03
Last Modified:05 Apr 2016 13:27
Publisher:Wiley-Blackwell
ISSN:0894-069X
Funders:Schweizerischer National Fonds; Grant Number: 20-31262.91
Additional Information:The attached file is a preprint (accepted version) of an article published in [Naval Res. Logist. 43 (1996), no. 2, 251--264]
Publisher DOI:10.1002/(SICI)1520-6750(199603)43:2<251::AID-NAV6>3.0.CO;2-9
Related URLs:http://www.ams.org/mathscinet-getitem?mr=97b:60149
Permanent URL: http://doi.org/10.5167/uzh-22533

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