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LIKELIHOOD RATIO ORDERING OF THE INSPECTION PARADOX

Published online by Cambridge University Press:  01 October 2004

Taizhong Hu  and
Weiwei Zhuang
Taizhong Hu
Affiliation:
Department of Statistics and Finance, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China, E-mail: [email protected]; [email protected]
Weiwei Zhuang
Affiliation:
Department of Statistics and Finance, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China, E-mail: [email protected]; [email protected]
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Abstract

In this article, some results on stochastic comparisons of the inspection paradox introduced by Ross [Probability in the Engineering and Informational Sciences 17: 47–51 (2003)] are established in the sense of the likelihood ratio order.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 18 , Issue 4 , October 2004 , pp. 503 - 510
Copyright
© 2004 Cambridge University Press

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References

REFERENCES

Barlow, R.E. & Proschan, F. (1975). Statistical theory of reliability and life testing. New York: Holt, Rinehart, and Winston.
Müller, A. & Stoyan, D. (2002). Comparison methods for stochastic models and risks. West Sussex: Wiley.
Ross, S.M. (2003). The inspection paradox. Probability in Engineering and Informational Sciences 17: 47–51.Google Scholar
Shaked, M. & Shanthikumar, J.G. (1994). Stochastic orders and their applications. New York: Academic Press.
Shanthikumar, J.G. & Yao, D. (1991). Bivariate characterization of some stochastic order relations. Advances in Applied Probability 23: 642–659.Google Scholar