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不同的估计技术和数据分析常量部分加速寿命测试的功率半物流分布的数据分析.
Ghadah A Alomani1, Amal S Hassan2, Amer I Al-Omari3
1Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia.
Scientific reports
|September 6, 2024
概括
部分加速寿命测试 (PALT) 需要强大的估计策略. 这项研究比较了经典和贝叶斯式的功率半物流分布方法,发现间距的最大乘积和贝叶斯式方法对可靠性工程最有效.
科学领域:
- 可靠性工程可靠性工程
- 统计建模 统计建模
- 加快生命测试加速生命测试
背景情况:
- 部分加速寿命测试 (PALT) 在标准加速寿命测试 (ALT) 结果不能推断到现实世界使用条件时至关重要.
- 在PALT中估计可靠性参数具有重大挑战,特别是在完整的数据集的情况下.
- 功率半物流分布经常用于可靠性研究中的生命周期数据模型.
研究的目的:
- 调查和比较各种古典和贝叶斯估计技术在恒定的PALT下对功率半物流分布的参数进行估计.
- 为了评估这些估计方法的性能,使用诸如平均平方误差 (MSE),绝对平均偏差,间隔长度和覆盖概率等指标.
- 评估构造的贝叶斯可信区间与近似置信区间之间的有效性.
主要方法:
- 使用了几种经典的估计技术:安德森-达林,最大概率,克拉梅尔--米斯,普通最小平方,加权最小平方和最大间距积.
- 采用贝叶斯估计方法来估计参数和加速因子.
- 进行了模拟研究,以比较所有方法的性能.
- 构建了近似置信区间和贝叶斯可信区间.
主要成果:
- 间距估计方法的最大产品在大多数场景中表现出卓越的性能,实现了最小的MSE和平均偏差.
- 贝叶斯估计方法在考虑MSE和平均偏差时,通常优于其他技术.
- 与近似信心区间相比,贝叶斯可信区间的覆盖概率更高,平均长度更短.
- 对两个现实世界工程数据集的分析证实了拟议方法的实际适用性.
结论:
- 间距和贝叶斯方法的最大乘积强烈推用于常量PALT中的参数估计,使用功率半物流分布式数据.
- 贝叶斯可信区间为评估参数不确定性提供了一个更可靠的替代方法,而不是近似的置信区间.
- 研究的估计策略是实用的,适用于现实世界的工程可靠性问题.
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