来自于Multiple-Outlier模型的最小次序统计量序性质（英文）

发布时间：2018-11-03 09:13

【摘要】：本文中,我们研究来自于两个multiple-outlier模型的最小次序统计量的随机比较,其中两个模型中独立同分布的随机变量个数不同.令X_(1:n)(p,q)和X_(1:n~*)(p~*,q~*)分别表示来自于X_1,…,X_p,X_(p+1),…,X_n和X_1,…,X_(p),X_(p~*+1),…,X_(n)的最小次序统计量,这里q=n-p,q~*=n~*-p~*.在参数(p,q)和(p~*,q~*)满足某些优化序条件下,我们根据普通随机序,失效率序和似然比序给出了X_(1:n)(p,q)和X_(1:n~*)(p~*,q~*)的序比较.
[Abstract]:In this paper, we study the random comparison of the minimum order statistics from two multiple-outlier models, in which the number of independent and distributed random variables is different. Let X _ (1: n) (PQ) and X _ (1: n *) (p1: n *) denote respectively from X _ (1: n), 鈥，

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