Potluri S. S. Swetha, Hanene Hamdani, Mohamed Nejib Ouertani, Vasili B. V. Nagarjuna, Suleman Nasiru, Mohammed Elgarhy
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引用次数: 0
摘要
我们介绍了Kumaraswamy Modified Kies power Lomax分布,这是一种新颖的五参数概率模型,结合了Kumaraswamy Modified Kies- g家族和power Lomax分布的特点,为建模真实世界的数据提供了更高的灵活性。所提出的模型具有广泛的适应性,能够模拟各种密度形状,包括右倾斜、左倾斜、减少-增加-减少、平峰形和瘦峰形行为,以及浴缸、减少-增加-减少、倒浴缸和减少-增加形状等危险模式。我们推导了模型的统计特性,包括分位数函数、矩、阶统计量、矩生成函数和熵。精算结果表明,该模型具有较好的风险评估适应性。采用极大似然估计技术对参数进行估计,仿真研究表明了估计的有效性。针对生存和可靠性数据的三个实际应用程序突出了该模型在处理复杂模式方面的更好性能,使其对可靠性和生存分析应用程序特别有价值。Voung的统计值和留一对数似然值被用来证明模型比竞争模型的强度。
Kumaraswamy Modified Kies Power Lomax Distribution: Properties, Actuarial Measures, and Applications
We introduce the Kumaraswamy Modified Kies power Lomax distribution, a novel five-parameter probability model that combines the features of the Kumaraswamy Modified Kies-G family and the power Lomax distribution, offering improved flexibility in modelling real-world data. The proposed model demonstrates extensive adaptability through its ability to model diverse density shapes, including right-skewed, left-skewed, decreasing-increasing-decreasing, platykurtic, and leptokurtic behavior, as well as hazard patterns like the bathtub, decreasing-increasing-decreasing, inverted-bathtub, and decreasing-increasing shapes. We derive the statistical properties of the model, including the quantile function, moments, order statistics, moment-generating function, and entropy. The actuarial measures show the model's adaptability in risk evaluation. Maximum likelihood estimation technique is employed to estimate the parameters, and a simulation study shows the effectiveness of the estimates. Three real-world applications to survival and reliability data highlight the model's better performance in handling complex patterns, making it particularly valuable for reliability and survival analysis applications. The Voung's statistic and leave-one-out log-likelihood values are used to demonstrate the model's strength over the competing models.