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Initial and final behaviour of failure rate functions for mixtures and systems

Published online by Cambridge University Press:  14 July 2016

Henry W. Block*
Affiliation:
University of Pittsburgh
Yulin Li*
Affiliation:
University of Pittsburgh
Thomas H. Savits*
Affiliation:
University of Pittsburgh
*
Postal address: Department of Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA
Postal address: Department of Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA
Postal address: Department of Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA

Abstract

In this paper we consider the initial and asymptotic behaviour of the failure rate function resulting from mixtures of subpopulations and formation of coherent systems. In particular, it is shown that the failure rate of a mixture has the same limiting behaviour as the failure rate of the strongest subpopulation. A similar result holds for systems except the role of strongest subpopulation is replaced by strongest min path set.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2003 

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Footnotes

The first and third authors were supported by NSF grant DMS-0072207.

References

Barlow, R. E., and Proschan, F. (1975). Statistical Theory of Reliability. Holt, Rinehart and Winston, New York.Google Scholar
Barlow, R. E., Marshall, A. M., and Proschan, F. (1963). Properties of probability distributions with monotone hazard rate. Ann. Math. Statist. 34, 375389.CrossRefGoogle Scholar
Block, H. W., and Joe, H. (1997). Tail behavior of the failure rate functions of mixtures. Lifetime Data Anal. 3, 269288.Google Scholar
Block, H. W., and Savits, T. H. (1997). Burn-in. Statist. Sci. 12, 119.Google Scholar
Block, H. W., Mi, J., and Savits, T. H. (1993). Burn-in and mixed populations. J. Appl. Prob. 30, 692702.Google Scholar
Block, H. W., Savits, T. H., and Wondmagegnehu, E. T. (2003). Mixtures of distributions with increasing linear failure rates. J. Appl. Prob. 40, 485504.CrossRefGoogle Scholar
Clarotti, C. A., and Spizzichino, F. (1990). Bayes burn-in decision procedures. Prob. Eng. Inf. Sci. 4, 437445.Google Scholar
Gupta, P. L., and Gupta, R. C. (1996). Ageing characteristics of the Weibull mixtures. Prob. Eng. Inf. Sci. 10, 591600.Google Scholar
Gurland, J., and Sethuraman, J. (1995). How pooling failure data may reverse increasing failure rates. J. Amer. Statist. Assoc. 90, 14161423.CrossRefGoogle Scholar