Ordering Results for Order Statistics from Two Heterogeneous Marshall-Olkin Generalized Exponential Distributions
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Adding parameters to a known distribution is a useful way of constructing flexible families of distributions. Marshall and Olkin (Biometrika, 84, 641–652, 1997) introduced a general method of adding a shape parameter to a family of distributions. In this paper, based on the Marshall-Olkin extension of a specified distribution, we introduce a new models referred to as Marshal-Olkin generalized exponential (MOGE) models, which include as a special case the well-known generalized exponential distribution. Next, we establish some stochastic comparisons between the corresponding order statistics based on majorization, weak majorization and p-larger theory. The results established here extend some well-known results in the literature about the generalized exponential distribution.
KeywordsWeak majorization order P-larger order Order statistics Usual stochastic order Marshall-Olkin generalized exponential model
AMS (2000) subject classificationPrimary: 60E15 Secondary: 90B25
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- Hirose, H. (2002). Maximum likelihood parameter estimation in the extended Weibull distribution and its applications to breakdown voltage estimation. IEEE Transactions on Reliability, 9, 524–536.Google Scholar
- Pledger, P. and Proschan, F. (1971). Comparisons of order statistics and of spacings from heterogeneous distributions. In: Optimizing Methods in Statistics, J. S. Rustagi ed, Academic Press, New York, 89–113.Google Scholar
- Ristic, M.M., Jose, K.K. and Ancy, J. (2007). A Marshall-Olkin gamma distribution and minification process. STARS: Stress and Anxiety Research Society, 11, 107–117.Google Scholar