108
v1v2v3 (latest)

Ordering Properties of Order Statistics from Heterogeneous Generalized Exponential and Gamma Populations

Abstract

Let X1,X2,,XnX_1, X_2,\ldots, X_n (resp. Y1,Y2,,YnY_1, Y_2,\ldots, Y_n) be independent random variables such that XiX_i (resp. YiY_i) follows generalized exponential distribution with shape parameter θi\theta_i and scale parameter λi\lambda_i (resp. δi\delta_i), i=1,2,,ni=1,2,\ldots, n. Here it is shown that if (λ1,λ2,,λn)\left(\lambda_1, \lambda_2,\ldots,\lambda_n\right) is pp-larger than (resp. weakly supermajorizes) (δ1,δ2,,δn)\left(\delta_1,\delta_2,\ldots,\delta_n\right), then Xn:nX_{n:n} will be greater than Yn:nY_{n:n} in usual stochastic order (resp. reversed hazard rate order). That no relation exists between Xn:nX_{n:n} and Yn:nY_{n:n}, under same condition, in terms of likelihood ratio ordering has also been shown. It is also shown that, if YiY_i follows generalized exponential distribution with parameters (λˉ,θi)\left(\bar\lambda,\theta_i\right), where λˉ\bar\lambda is the mean of all λi\lambda_i's, i=1ni=1\ldots n, then Xn:nX_{n:n} is greater than Yn:nY_{n:n} in likelihood ratio ordering. Some new results on majorization have been developed which fill up some gap in the theory of majorization. Some results on multiple-outlier model are also discussed. In addition to this, we compare two series systems formed by gamma components with respect to different stochastic orders.

View on arXiv
Comments on this paper