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Likelihood ratio ordering of convolutions of heterogeneous exponential and geometric random variables

机译:异构指数和几何随机变量卷积的似然比排序

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摘要

In this paper, we study the convolutions of heterogeneous exponential and geometric random variables in terms of the weakly majorization order (>=(w)) of parameter vectors and the likelihood ratio order (>=(Ir)). It is proved that >=(w) order between two parameter vectors implies >=(Ir) order between convolutions of two heterogeneous exponential (geometric) samples. For the two-dimensional case, it is found that there exist stronger equivalent characterizations. These results strengthen the corresponding ones of Boland et al. [Boland, P.J., El-Neweihi, E., Proschan, F., 1994. Schur properties of convolutions of exponential and geometric random variables. journal of Multivariate Analysis 48, 157-167] by relaxing the conditions on parameter vectors from the majorization order (>=(m)) to >=(w) order.
机译:在本文中,我们根据参数向量的弱主次顺序(> =(w))和似然比顺序(> =(Ir))研究了异类指数和几何随机变量的卷积。证明两个参数向量之间的> =(w)阶意味着两个异质指数(几何)样本的卷积之间的> =(Ir)阶。对于二维情况,发现存在更强的等效特征。这些结果加强了Boland等人的相应研究。 [Boland,P.J.,El-Neweihi,E.,Proschan,F.,1994。指数和几何随机变量的卷积的Schur性质。 [多变量分析杂志48,157-167],将参数向量上的条件从主序(> =(m))降到> =(w)阶。

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