使用威布尔,逻辑正常和马分布的移位混合模型
1Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667 India.
概括
这项研究引入了新的混合模型,使用Weibull,lognormal和gamma分布. 对于小型数据集,转移混合模型在统计和可靠性分析中表现出卓越的性能.
科学领域:
- 统计 统计 统计 统计
- 可靠性工程可靠性工程
- 可能性分布的概率分布.
背景情况:
- 混合模型在各种领域被广泛使用.
- 现有的模型可能对所有数据类型都没有最佳的性能.
- 韦布尔分布,lognormal分布和马分布是模拟的常见选择.
研究的目的:
- 开发一个框架,用于构建三重混合模型及其转移版本.
- 评估这些拟议模型的统计和可靠性特性.
- 在真实数据上评估转移混合模型的性能.
主要方法:
- 使用韦布尔分布,lognormal分布和马分布构建三重混合模型.
- 通过最大概率估计 (MLE) 和预期-最大化算法进行参数估计.
- 在实际数据集上使用适合性测试的模型的应用和比较.
主要成果:
- 拟议的混合模型及其转移版本已成功构建.
- 为模型建立了统计和可靠性指数.
- 转移混合模型在与现实数据相匹配时显示出显著的实用性.
- 合适性测试表明,对于某些数据集,转移模型的优势.
结论:
- 转移混合模型,特别是对于小数据集,被认为是最适合的模型.
- 这项研究为应用先进的混合模型提供了有价值的框架.
- 这些发现对数据分析的可靠性和统计学有影响.
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