Delta Power Transformation: A New Family of Probability Distributions

L. Sapkota, Pankaj Kumar, Vijay Kumar
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Abstract

This research article presents a novel approach called the delta-power transformation, which introduces a new class of lifetime distributions. The article discusses the key features of one member from this family, which exhibits a hazard function with a distinctive shape resembling a J, reverse-J, constant, or monotonically increasing. The researchers delve into the statistical characteristics of this distribution and utilize the maximum likelihood estimation (MLE) approach to gauge its parameters. They conduct a simulation experiment to evaluate the precision of the estimation process, finding that biases and mean square errors diminish with larger sample sizes, even in cases involving small samples. Moreover, the study show-cases the practical utility of the suggested distribution through an examination of two real-world datasets. Evaluation criteria for model selection and goodness-of-fit test statistics indicate that the proposed model surpasses certain existing models in performance.
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德尔塔幂变换:新的概率分布系列
这篇研究文章介绍了一种名为三角幂变换的新方法,它引入了一类新的寿命分布。文章讨论了这一家族中一个成员的主要特征,该成员的危险函数具有独特的形状,类似于 J、反向 J、常数或单调递增。研究人员深入探讨了该分布的统计特征,并利用最大似然估计 (MLE) 方法测量了其参数。他们通过模拟实验评估了估计过程的精确度,发现偏差和均方误差随着样本量的增大而减小,即使在涉及小样本的情况下也是如此。此外,研究还通过对两个真实世界数据集的考察,展示了所建议的分布的实用性。模型选择和拟合优度测试统计的评估标准表明,所建议的模型在性能上超越了某些现有模型。
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