基于增强的雷利逆向韦布尔模型的生存分析
Mohammed Elgarhy1,2, Mohamed Kayid3, Arne Johannssen4
1Mathematics and Computer Science Department, Faculty of Science, Beni-Suef University, Beni-Suef 62521, Egypt.
Heliyon
|December 17, 2024
概括
一个新的生存模型,卡维亚-马诺哈兰-雷利逆向韦布尔分布 (KMRIWD),与现有模型相比,为真实世界的数据提供了更好的适应性. 这种统计学进步提供了增强的可靠性分析能力.
科学领域:
- 统计 统计 统计 统计
- 可靠性工程可靠性工程
- 可能性理论概率理论.
背景情况:
- 生存模型对于分析各种领域的时间到事件数据至关重要.
- 现有的分布可能无法充分捕捉复杂的故障模式.
- 卡维亚-马诺哈兰转换为开发新的统计分布提供了一个灵活的框架.
研究的目的:
- 介绍和分析一种新的两参生存模型:卡维亚-马诺哈兰-雷利逆向韦布尔分布 (KMRIWD).
- 调查拟议的KMRIWD的统计属性和可靠性措施.
- 评估KMRIWD的参数估计技术的性能.
主要方法:
- 通过结合卡维亚-马诺哈兰转换和雷利逆向韦布尔分布来开发KMRIWD.
- 分析关键的统计属性和可靠性函数.
- 使用最大概率方法和各种采样策略进行参数估计.
- 通过蒙特卡洛模拟进行性能评估.
- 使用现实世界数据集对现有生存模型进行比较分析.
主要成果:
- 定义KMRIWD,并得出其基本的统计和可靠性特征.
- 获得KMRIWD参数的最大概率估计.
- 蒙特卡洛模拟证明了估计方法的有效性.
- 经验分析证实了KMRIWD在真实数据上的竞争模型中具有优越的适应性.
结论:
- 拟议的KMRIWD是一个灵活有效的生存模式.
- 在适应现实世界的可靠性数据方面,KMRIWD表现出卓越的性能.
- 这种新的分布为可靠性分析和相关的统计建模提供了有价值的工具.
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