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The minimum and maximum order statistics from many of the common bivariate exponential distributions are predominantly generalized mixtures of exponentials; however, the maximum from the Friday and Patil bivariate exponential (FPBVE) model is either a generalized mixture of three or fewer exponentials or a generalized mixture of gamma and exponentials. In this article, we obtain conditions based on the weights and parameters of the generalized mixtures of gamma and one or two exponential distributions that yield legitimate probability models. Furthermore, we analyze properties of the failure rate of the maximum from the FPBVE model. This answers a question raised in Baggs and Nagaraja (1996 Baggs , G. E. , Nagaraja , H. N. ( 1996 ). Reliability properties of order statistics from bivariate exponential distributions . Commun. Statist. Stochastic Mod. 12 : 611631 .[Taylor & Francis Online] [Google Scholar]).  相似文献   
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Friday and Patil bivariate exponential (FPBVE) distribution family is one of the most flexible bivariate exponential distributions in the literature; among others, it contains the bivariate exponential models due to Freund, Marshall–Olkin, Block–Basu, and Proschan–Sullo as particular cases. In this article, we discuss the stochastic aging of the maximum statistic from FPBVE model in according to the log-concavity of its density function, i.e., in the increasing or decreasing likelihood ratio classes (ILR or DLR), and consequently in the IFR and DFR classes. Furthermore, a kind of DFR distributions which are not DLR is derived from our classification.  相似文献   
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Recently Kundu and Gupta [2010, Modified Sarhan-Balakrishnan singular bivariate distribution, Journal of Statistical Planning and Inference, 140, 526-538] introduced the modified Sarhan-Balakrishnan bivariate distribution and established its several properties. In this paper we provide a multivariate extension of the modified Sarhan-Balakrishnan bivariate distribution. It is a distribution with a singular part. Different ageing and dependence properties of the proposed multivariate distribution have been established. The moment generating function, the product moments can be obtained in terms of infinite series. The multivariate hazard rate has been obtained. We provide the EM algorithm to compute the maximum likelihood estimators and an illustrative example is performed to see the effectiveness of the proposed method.  相似文献   
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