概率密度的时刻不确定性的最大透标准
Jordan M Stoyanov1,2, Aldo Tagliani3, Pier Luigi Novi Inverardi3
1Institute of Mathematics & Informatics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
Entropy (Basel, Switzerland)
|February 23, 2024
概括
这项研究引入了使用最大率的概率分布中的时刻不确定性的新标准. 这有助于识别那些不是唯一由它们的时刻决定的分布,特别是在正半线上.
科学领域:
- 概率理论的概率理论是什么
- 数学统计的数学统计.
- 信息理论是信息理论.
背景情况:
- 具有有限整数顺序时刻的绝对连续概率分布可以是确定时刻或不确定时刻.
- 在各种统计应用中,区分定时分布和不定时分布至关重要.
研究的目的:
- 在正半线上确定概率分布的时刻不确定性 (M-不确定性) 的新标准 (Stieltjes案).
- 在整个实线上 (汉堡事件) 导出M-不确定分布的相关结果.
- 探索最大,对称性和M-不确定性之间的关系.
主要方法:
- 应用最大的方法.
- 在Stieltjes案件中开发了一个M不确定性的新标准.
- 汉堡客户案的相关结果的推导.
主要成果:
- 对于正半线上的分布,建立了一个新的M不确定性标准.
- 对于整个实直线上的M-不确定的分布,可以推导出有用的结果.
- 阐明了最大,对称性和M-不确定性之间的关系.
结论:
- 最大的方法提供了一个强大的工具,用于识别M-不确定的概率分布.
- 这些发现为分布的属性提供了新的见解,这些分布的属性并不完全取决于它们的动量.
- 该研究将最大化与对称性属性联系在瞬间不确定性的背景下.
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