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A moment-based empirical likelihood ratio test for exponentiality using the probability integral transformation

机译:基于矩的概率积分变换基于矩的经验似然比检验

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摘要

A simple and efficient goodness-of-fit test for exponentiality is developed by exploiting the characterization of the exponential distribution using the probability integral transformation. We adopted the empirical likelihood methodology in constructing the test statistic. The proposed test statistic has a chi-square limiting distribution. For small to moderate sample sizes Monte-Carlo simulations revealed that our proposed tests are much more superior under increasing failure rate (IFR) and bathtub decreasing-increasing failure rate (BFR) alternatives. Real data examples were used to demonstrate the robustness and applicability of our proposed tests in practice.
机译:通过利用概率积分变换对指数分布进行表征,开发了一种简单有效的指数拟合优度检验。我们在构建检验统计量时采用了经验似然方法。拟议的测试统计量具有卡方限制分布。对于中小样本量,蒙特卡洛模拟显示,我们提出的测试在增加失败率(IFR)和减少浴缸减少-增加失败率(BFR)的替代方案下要优越得多。实际数据示例用于证明我们提出的测试在实践中的鲁棒性和适用性。

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