威布尔生成分布的一个推论适定性及其应用

Brijesh P Singh, Utpal Dhar Das
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引用次数: 0

摘要

本文试图利用威布尔分布建立一种灵活的单参数连续分布。威布尔分布是医疗和工程领域中使用最广泛的寿命分布。指数分布和瑞利分布是威布尔分布的特殊情况。在本研究中,我们使用这两个分布来开发一个新的分布。讨论了该分布的重要统计性质,如矩、矩生成和特征函数。还导出了各种熵测度,如Rényi、Shannon和累积熵。还获得了pdf和cdf的kthkt h阶统计数据。讨论了危险函数的性质及其极限行为。获得了参数的非闭合形式的最大似然估计,从而使用迭代过程来获得估计。对不同的样本量进行了模拟研究,并观察到参数λλ的MLE、MSE和Bias。一些真实的数据集用于检查模型相对于医学和工程科学的一些数据集的其他有效分布的适用性。在尾部区域,所提出的模型效果更好。各种模型选择标准,如-2LL、AIC、AICc、BIC、K-S和A-D检验表明,所提出的分布比其他有能力的分布表现更好,因此将其视为一种替代分布。对于本研究中考虑的数据集,与其他一些两参数复杂分布相比,所提出的单参数分布更灵活。
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An Inferential Aptness of a Weibull Generated Distribution and Application
In this article an attempt has been made to develop a flexible single parameter continuous distribution using Weibull distribution. The Weibull distribution is most widely used lifetime distributions in both medical and engineering sectors. The exponential and Rayleigh distribution is particular case of Weibull distribution. Here in this study we use these two distributions for developing a new distribution. Important statistical properties of the proposed distribution is discussed such as moments, moment generating and characteristic function. Various entropy measures like Rényi, Shannon and cumulative entropy are also derived. The kthkt⁢h order statistics of pdf and cdf also obtained. The properties of hazard function and their limiting behavior is discussed. The maximum likelihood estimate of the parameter is obtained that is not in closed form, thus iteration procedure is used to obtain the estimate. Simulation study has been done for different sample size and MLE, MSE, Bias for the parameter λλ has been observed. Some real data sets are used to check the suitability of model over some other competent distributions for some data sets from medical and engineering science. In the tail area, the proposed model works better. Various model selection criterion such as -2LL, AIC, AICc, BIC, K-S and A-D test suggests that the proposed distribution perform better than other competent distributions and thus considered this as an alternative distribution. The proposed single parameter distribution is found more flexible as compare to some other two parameter complicated distributions for the data sets considered in the present study.
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