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基于一般渐进II型删失数据间距的指数分布拟合优度检验。

Goodness-of-fit test for exponentiality based on spacings for general progressive Type-II censored data.

作者信息

Qin Xinyan, Yu Jiao, Gui Wenhao

机构信息

Department of Mathematics, Beijing Jiaotong University, Beijing, People's Republic of China.

出版信息

J Appl Stat. 2020 Sep 18;49(3):599-620. doi: 10.1080/02664763.2020.1821613. eCollection 2022.

Abstract

There have been numerous tests proposed to determine whether or not the exponential model is suitable for a given data set. In this article, we propose a new test statistic based on spacings to test whether the general progressive Type-II censored samples are from exponential distribution. The null distribution of the test statistic is discussed and it could be approximated by the standard normal distribution. Meanwhile, we propose an approximate method for calculating the expectation and variance of samples under null hypothesis and corresponding power function is also given. Then, a simulation study is conducted. We calculate the approximation of the power based on normality and compare the results with those obtained by Monte Carlo simulation under different alternatives with distinct types of hazard function. Results of simulation study disclose that the power properties of this statistic by using Monte Carlo simulation are better for the alternatives with monotone increasing hazard function, and otherwise, normal approximation simulation results are relatively better. Finally, two illustrative examples are presented.

摘要

已经提出了许多检验方法来确定指数模型是否适用于给定的数据集。在本文中,我们提出了一种基于间距的新检验统计量,以检验一般渐进式II型删失样本是否来自指数分布。讨论了检验统计量的零分布,它可以用标准正态分布近似。同时,我们提出了一种在零假设下计算样本期望和方差的近似方法,并给出了相应的功效函数。然后,进行了模拟研究。我们基于正态性计算功效的近似值,并将结果与在不同备择假设下具有不同类型危险函数的蒙特卡罗模拟结果进行比较。模拟研究结果表明,对于具有单调递增危险函数的备择假设,使用蒙特卡罗模拟的该统计量的功效特性更好,否则,正态近似模拟结果相对更好。最后,给出了两个说明性例子。

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