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On New Classes of Extreme Shock Models and Some Generalizations

Published online by Cambridge University Press:  14 July 2016

Ji Hwan Cha*
Affiliation:
Ewha Womans University
Maxim Finkelstein*
Affiliation:
University of the Free State and Max Planck Institute for Demographic Research
*
Postal address: Department of Statistics, Ewha Womans University, Seoul, 120-750, Korea. Email address: [email protected]
∗∗Postal address: Department of Mathematical Statistics, University of the Free State, 339 Bloemfontein 9300, South Africa. Email address: [email protected]
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Abstract

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In extreme shock models, only the impact of the current, possibly fatal shock is usually taken into account, whereas in cumulative shock models, the impact of the preceding shocks is accumulated as well. A shock model which combines these two types is called a ‘combined shock model’. In this paper we study new classes of extreme shock models and, based on the obtained results and model interpretations, we extend these results to several specific combined shock models. For systems subject to nonhomogeneous Poisson processes of shocks, we derive the corresponding survival probabilities and discuss some meaningful interpretations and examples.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2011 

References

Anderson, P. K., Borgan, O., Gill, R. D. and Keiding, N. (1993). Statistical Models Based on Counting Processes. Springer, New York.Google Scholar
Beichelt, F. and Fischer, K. (1980). General failure model applied to preventive maintenance policies. IEEE Trans. Reliab. 29, 3941.Google Scholar
Block, H. W., Borges, W. S. and Savits, T. H. (1985). Age-dependent minimal repair. J. Appl. Prob. 22, 370385.Google Scholar
Cha, J. H. and Finkelstein, M. (2009). On a terminating shock process with independent wear increments. J. Appl. Prob. 46, 353362.Google Scholar
Çinlar, E. (1975). Introduction to Stochastic Processes. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
Cox, D. R. and Isham, V. (1980). Point Processes. Chapman and Hall, London.Google Scholar
Finkelstein, M. (2007). On some ageing properties of general repair processes. J. Appl. Prob. 44, 506513.CrossRefGoogle Scholar
Finkelstein, M. (2008). Failure Rate Modelling for Risk and Reliability. Springer, London.Google Scholar
Gut, A. and Hüsler, J. (2005). Realistic variation of shock models. Statist. Prob. Lett. 74, 187204.Google Scholar
Sumita, U. and Shanthikumar, J. G. (1985). A class of correlated cumulative shock models. Adv. Appl. Prob. 17, 347366.Google Scholar