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Discriminating between generalized exponential, geometric extreme exponential and Weibull distributions

机译:区分广义指数分布,几何极限指数分布和威布尔分布

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摘要

Generalized exponential, geometric extreme exponential and Weibull distributions are three non-negative skewed distributions that are suitable for analysing lifetime data. We present diagnostic tools based on the likelihood ratio test (LRT) and the minimum Kolmogorov distance (KD) method to discriminate between these models. Probability of correct selection has been calculated for each model and for several combinations of shape parameters and sample sizes using Monte Carlo simulation. Application of LRT and KD discrimination methods to some real data sets has also been studied.
机译:广义指数分布,几何极限指数分布和Weibull分布是三种非负偏斜分布,适用于分析生命周期数据。我们提出基于似然比检验(LRT)和最小Kolmogorov距离(KD)方法的诊断工具,以区分这些模型。使用蒙特卡洛模拟,已经为每个模型以及形状参数和样本大小的几种组合计算了正确选择的可能性。还研究了LRT和KD判别方法在一些实际数据集上的应用。

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