使用三角函数的新分布家族:在医疗保健领域的属性和应用
Omalsad Hamood Odhah1, Huda M Alshanbari1, Zubair Ahmad2
1Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Heliyon
|May 6, 2024
概括
对于连续数据,引入了一个新的指数功率正弦-G 分布家族和指数功率正弦-韦布尔模型. 与现有分布相比,这些模型在医疗数据分析方面表现优越.
科学领域:
- 统计 统计 统计 统计
- 可能性理论概率理论.
- 数学建模的数学建模
背景情况:
- 概率分布对于各种领域的现实数据建模至关重要.
- 现有的分布可能无法完全捕捉所有连续数据集的复杂性.
- 持续需要具有更高灵活性的新型统计模型.
研究的目的:
- 引入一种新的灵活的概率分布家族,称为指数乘正弦-G家族.
- 开发和分析这个家族中的一个特定模型:指数乘位正弦-韦布尔分布.
- 评估拟议模型在实际应用中的有效性,特别是在医疗保健领域.
主要方法:
- 分布的指数乘积正弦-G 家庭的发展.
- 关键性质的数学导出,包括量子函数,可识别性和时刻.
- 使用最大概率估计器估计模型参数.
- 进行模拟研究以评估模型行为.
- 将指数乘积正弦-韦布尔模型应用于现实世界医疗保健数据集的应用和比较.
主要成果:
- 已经成功地制定了指数功率正弦-G家族和指数功率正弦-韦布尔模型.
- 导出了关键的数学属性和估计方法.
- 模拟研究提供了对模型性能的见解.
- 在基于七个评估标准的两个医疗保健数据应用中,指数功率正弦-韦布尔模型的表现优于竞争分布.
结论:
- 提出的指数功率正弦G家族为连续数据建模提供了一个有价值的新工具.
- 指数级正弦-韦布尔模型显示了分析复杂现象的巨大潜力,特别是在医疗保健领域.
- 该研究强调了该模型的最佳性和灵活性,以应对实际的数据分析挑战.
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