Estimation of Reliability in a Multicomponent Stress-Strength Model.
WISCONSIN UNIV MADISON DEPT OF STATISTICS
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A stress-strength model is formulated for s out of k systems consisting of identical components. The authors consider minimum variance unbiased estimation of system reliability for data consisting of a random sample from the stress distribution and one from the strength distribution when the two distributions are related as Lehmann alternatives. The asymptotic distribution is obtained by expanding the unbiased estimate about the maximum likelihood value and establishing their equivalence. Performance of the two estimates for moderate samples is studied by Monte Carlo simulation. Uniformly most accurate unbiased confidence intervals are also obtained for system reliability. Author
- Statistics and Probability
- Manufacturing and Industrial Engineering and Control of Production Systems