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Estimation of P(X > Y) for the power Lindley distribution based on progressively type II right censored samples

机译:基于逐步II型右删失样本的幂Lindley分布的P(X> Y)估计

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In this study, we discuss the problem of estimating , when X and Y are two independent power Lindley random variables, based on progressively type II right censored order statistics. The maximum likelihood estimator of rho and its asymptotic distribution, asymptotic interval estimator of rho, Bayesian point estimators for rho under symmetric and asymmetric loss functions as well as credible intervals for rho are achieved when X and Y have a common parameter. Since it seems that the integrals pertaining to the Bayes estimation cannot be obtained in explicit forms, we propose the Metropolis-Hastings within Gibbs algorithm to find the approximate Bayes estimates of rho. A simulation study is given in order to evaluate the proposed estimators and compare the different methods, developed in the paper. The corresponding results for the general case (when X and Y have no common parameters), as well as two examples, are also provided. The paper finishes with some remarks.
机译:在这项研究中,我们讨论了基于渐进式II型右删失阶统计量,当X和Y是两个独立的幂Lindley随机变量时的估计问题。当X和Y具有相同的参数时,可以得到rho的最大似然估计量及其渐近分布,rho的渐近间隔估计量,在对称和非对称损失函数下的rho的贝叶斯点估计量以及rho的可靠区间。由于似乎无法以显式形式获得与贝叶斯估计有关的积分,因此我们建议在Gibbs算法中使用Metropolis-Hastings来找到rho的近似贝叶斯估计。为了评估拟议的估计量并比较本文中开发的不同方法,进行了仿真研究。还提供了一般情况下的相应结果(当X和Y没有公共参数时)以及两个示例。本文以一些评论结束。

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