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一个灵活的扩展的逻辑物流模型与不同的故障率形状和应用程序的灵活扩展

Ahmed Z Afify¹, Mohamed E Mead², Hamada H Hassan³

¹Department of Statistics, Mathematics, and Insurance, Benha University, Benha, 13511, Egypt. ahmedzafify87@gmail.com.

Scientific reports

|January 23, 2026

概括

我们介绍了库马拉斯瓦米α-power log-logistic (KAPLL) 分布,这是可靠性和生存分析的一个灵活的新模型. 在现实应用中,KAPLL分布有效地模拟了各种危险率,并且在现实应用中表现出高于标准逻辑逻辑模型的性能.

科学领域:

统计统计统计统计
可靠性工程可靠性工程
生存分析的分析.

背景情况:

逻辑逻辑分布是生存分析和可靠性工程中的一个基本模型.
现有的逻辑逻辑模型的概括在捕捉复杂的危险率行为方面存在局限性.
需要更灵活的统计分布来建模各种老化和故障模式.

研究的目的:

介绍和调查小说库马拉斯瓦米阿尔法功率逻辑逻辑 (KAPLL) 分布的数学属性.
评估KAPLL分布在建模各种危险率形状和尾巴行为中的灵活性.
为了比较不同参数估计方法对KAPLL分布的性能.

主要方法:

这项研究得出了KAPLL分布的数学属性.
对KAPLL模型的参数估计使用八种经典估计技术进行.
模拟研究是为了对估计方法的有效性进行排名.
从可靠性,工程,生物医学和环境科学中分析现实世界的数据集.

主要成果:

卡普尔分布表现出了显著的灵活性,能够模拟广泛的危险率行为,包括增加,减少,浴和复杂的形状.
卡普尔分布可以表示对称和不对称的密度函数.
模拟结果为KAPLL模型提供了对最有效的参数估计方法的见解.
概率比测试证实了KAPLL模型在统计学上比基线逻辑分布在多个真实数据集上的显著改进.

结论:

拟议的KAPLL分布提供了更大的灵活性,并克服了现有的逻辑逻辑概括的局限性.
卡普尔模型是一个多功能工具,用于分析可靠性,工程,生物医学和环境科学领域的各种现象.
该研究为KAPLL分布的参数估计提供了宝贵的指导,有利于工程师和应用统计学家.

关键词:

浴危险率浴危险率是什么库马拉斯瓦米阿尔法级动力级别逻辑-物流分发是如何进行的最大的可能性.订单统计数据订单统计数据实际数据是真实的数据.

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