瑞利分布的累积残差熵表征及相关的拟合优度检验

S. Baratpour, F. Khodadadi
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引用次数: 10

摘要

瑞利分布广泛用于寿命建模,在电子真空器件和通信工程中具有重要意义。Rao等(2004)提出了累积残差熵(Cumulative Residual Entropy, CRE),它是将Shannon熵扩展到累积分布函数。本文首先介绍了一类一般的最大CRE分布,然后描述了瑞利分布的特征,并用它来构造拟合优度检验,以确定这种模型的适当性。为了构建检验统计量,我们使用了Baratpour和Habibi(2012)引入的累积残差Kullback-Leibler信息(CKL)。通过蒙特卡罗模拟,给出了不同样本量下的临界值。对各种备选方案和样本量进行蒙特卡罗功率分析,以便将所提出的检验与基于经验分布的几种现有拟合优度检验进行比较。我们发现所提出的测试具有良好的功率性能。通过一个实例说明了所提出的测试方法的应用。
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A Cumulative Residual Entropy Characterization of the Rayleigh Distribution and Related Goodness-of-Fit Test
Rayleigh distribution is widely used for life-time modeling and is important in electro vacuum devices and communication engineering. Rao et al. (2004) suggested the Cumulative Residual Entropy (CRE), which is the extension of the Shannon entropy to the the cumulative distribution function. In this paper, a general class of maximum CRE distributions is introduced and then we characterize the Rayleigh distribution and use it to construct a goodness-of-fit test for ascertaining appropriateness of such model. For constructing the test statistics, we use Cumulative residual Kullback-Leibler information (CKL) that was introduced by Baratpour and Habibi (2012). Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for the test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed test with several existing goodness-of-fit tests based on the empirical distribution. We find that the proposed test has good power properties. The use of the proposed test is shown in an illustrative example.
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