English

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

Applications 2016-01-18 v3 Statistics Theory Statistics Theory

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.

Keywords

Cite

@article{arxiv.1410.4724,
  title  = {Ordering Properties of Order Statistics from Heterogeneous Generalized Exponential and Gamma Populations},
  author = {Amarjit Kundu and Shovan Chowdhury and Asok K. Nanda and Nil Kamal Hazra},
  journal= {arXiv preprint arXiv:1410.4724},
  year   = {2016}
}

Comments

Due to some mathematical issues, we want to withdraw this article