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ON A CLASS OF GENERALIZED MARSHALL–OLKIN BIVARIATE DISTRIBUTIONS AND SOME RELIABILITY CHARACTERISTICS

Published online by Cambridge University Press:  28 March 2013

Ramesh C. Gupta
Affiliation:
Department of Mathematics and Statistics, University of Maine, Orono, ME 04469-5752
S.N.U.A. Kirmani
Affiliation:
Department of Mathematics, University of Northern Iowa, Cedar Falls, IA 50614
N. Balakrishnan
Affiliation:
Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, CanadaL8S 4K1

Abstract

We consider here a general class of bivariate distributions from reliability point of view, and refer to it as generalized Marshall–Olkin bivariate distributions. This class includes as special cases the Marshall–Olkin bivariate exponential distribution and the class of bivariate distributions studied recently by Sarhan and Balakrishnan [25]. For this class, the reliability, survival, hazard, and mean residual life functions are all derived, and their monotonicity is discussed for the marginal as well as the conditional distributions. These functions are also studied for the series and parallel systems based on this bivariate distribution. Finally, the Clayton association measure for this bivariate model is derived in terms of the hazard gradient.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2013

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References

1.Bain, L.J. (1974). Analysis of linear failure rate life testing distribution. Technometrics 16: 551559.CrossRefGoogle Scholar
2.Balakrishnan, N. & Lai, C.D. (2009). Continuous bivariate distributions, 2nd edn.New York: Springer-Verlag.Google Scholar
3.Barlow, R.E., Marshall, A.W., & Proschan, F. (1963). Properties of probability distributions with monotone hazard rate. Annals of Mathematical Statistics 34: 375389.CrossRefGoogle Scholar
4.Barlow, R.E. & Proschan, F. (1975). Statistical theory and life testing. New York: Holt, Rinehart and Winston.Google Scholar
5.Clayton, D.G. (1978). A model for association in bivariate life tables and its applications in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65: 141151.CrossRefGoogle Scholar
6.Franco, M., Kundu, D., & Vivo, J.M. (2011). Multivariate extension of modified Sarhan-Balakrishnan bivariate distribution. Journal of Statistical Planning and Inference 140: 34003412.CrossRefGoogle Scholar
7.Franco, M. & Vivo, J.M. (2010). A multivariate extension of Sarhan and Balakrishnan's bivariate distribution and its ageing and dependence properties. Journal of Multivariate Analysis 101: 491499.CrossRefGoogle Scholar
8.Gupta, R.C. (2001). Non-monotonic failure rates and mean residual life functions. In System and bayesian reliability. Hayakawa, Y., Irony, T. & Xie, M. (eds.), Singapore: World Scientific, pp. 147162.CrossRefGoogle Scholar
9.Gupta, R.C. & Akman, O. (1995). Mean residual life function for certain types of non-monotonic ageing. Stochastic Models 11: 219225.Google Scholar
10.Gupta, R.C., Gupta, P.L., & Gupta, R.D. (1998). Modeling failure time data with Lehman's alternatives. Communications in Statistics – Theory and Methods 27: 887904.CrossRefGoogle Scholar
11.Gupta, R.C. & Kirmani, S.N.U.A. (2006). Stochastic comparisons in frailty models. Journal of Statistical Planning and Inference 136: 36473658.CrossRefGoogle Scholar
12.Gupta, R.D. & Kundu, D. (1999). Generalized exponential distributions. Australian and New Zealand Journal of Statistics 41: 173188.CrossRefGoogle Scholar
13.Gupta, R.D. & Kundu, D. (2001). Generalized exponential distributions: different methods of estimation. Journal of Statistical Computation and Simulation 69: 315337.CrossRefGoogle Scholar
14.Gupta, R.C. & Warren, R. (2001). Determination of change points of non-monotonic failure rates. Communications in Statistics — Theory and Methods 30: 19031920.CrossRefGoogle Scholar
15.Joe, H. (1997). Multivariate models and dependence concepts. New York: Chapman & Hall.Google Scholar
16.Karlin, S. (1968). Total positivity. Stanford, CA: Stanford University Press.Google Scholar
17.Kotz, S., Balakrishnan, N., & Johnson, N.L. (2000). Continuous multivariate distributions — Vol. 1, 2nd edn., Hoboken, NJ: John Wiley & Sons.CrossRefGoogle Scholar
18.Kundu, D. & Gupta, R.D. (2009). Bivariate generalized exponential distribution. Journal of Multivariate Analysis 100: 581593.CrossRefGoogle Scholar
19.Kundu, D. & Gupta, R.D. (2010). Modified Sarhan–Balakrishnan singular bivariate distribution. Journal of Statistical Planning and Inference 140: 526538.CrossRefGoogle Scholar
20.Lin, C.T., Wu, S.J.S., & Balakrishnan, N. (2003). Parameter estimation for the linear hazard rate distribution based on record and inter-record times. Communications in Statistics — Theory and Methods 32: 729748.CrossRefGoogle Scholar
21.Manatunga, A.K. & Oakes, D. (1996). A measure of association for bivariate frailty distributions. Journal of Multivariate Analysis 56: 6074.CrossRefGoogle Scholar
22.Marshall, A.W. & Olkin, O. (1967). A multivariate exponential distribution. Journal of the American Statistical Association 62: 3044.CrossRefGoogle Scholar
23.Marshall, A.W. & Olkin, I. (2009). Life distributions. New York: Springer-Verlag.Google Scholar
24.Oakes, D. (1989). Bivariate survival models induced by fralities. Journal of the American Statistical Association 84: 487493.CrossRefGoogle Scholar
25.Sarhan, A.M. & Balakrishnan, N. (2007). A new class of bivariate distributions and its mixture. Journal of Multivariate Analysis 98: 15081527.CrossRefGoogle Scholar
26.Sarhan, A. & Kundu, D. (2009). Generalized linear failure rate distribution. Communications in Statistics — Theory and Methods 38: 642660.CrossRefGoogle Scholar
27.Sen, A. & Bhattacharya, G.K. (1995). Inference procedures for linear failure rate model. Journal of Statistical Planning and Inference 46: 5976.CrossRefGoogle Scholar
28.Shaked, M. (1977). A family of concepts of dependence for bivariate distributions. Journal of the American Statistical Association 72: 642650.CrossRefGoogle Scholar
29.Takahasi, K. (1988). A note on hazard rates of order statistics. Communications in Statistics – Theory and Methods 17: 41334166.CrossRefGoogle Scholar