测试同位素考希假设的测试
Jihad Fahs1, Ibrahim Abou-Faycal1, Ibrahim Issa1,2
1Department of Electrical and Computer Engineering, American University of Beirut, P.O. Box 11-0236, Beirut 1107 2020, Lebanon.
Entropy (Basel, Switzerland)
|January 8, 2025
概括
比较考奇和高斯分布的概率测试显示错误概率并不总是随样本大小呈指数下降. 指数中的领先项是对数式,在最佳贝叶斯式错误行为中存在惊人的差异.
科学领域:
- 统计 统计 统计 统计
- 可能性理论概率理论.
- 信号处理 信号处理
背景情况:
- 同otropic Cauchy分布是一个重尾分布.
- 它类似于有限的第二时刻定律的高斯分布.
- 在统计推断中,区分考契分布和高斯分布至关重要.
研究的目的:
- 分析概率比测试 (LRT) 的性能,以区分同位素考希分布和同位素高斯分布.
- 为了描述这些测试的错误概率,随着观察次数 (n) 的增加.
- 为了研究最佳贝叶斯错误概率的非对称行为.
主要方法:
- 对同位素Cauchy与同位素高斯假设的概率测试的推导和分析.
- 对大样本大小 (n) 的错误概率进行非对称分析.
- 在错误概率指数中的领先项和常数的计算.
主要成果:
- 对于LRTs的错误概率并不总是随着n的指数下降.
- 错误概率指数中的领先项被证明是对数.
- 确定了控制这种对数分解的特定常数.
- 最佳贝叶斯错误概率表现出明显的非对称行为.
结论:
- 在某些条件下,LRTs在区分考西分布和高斯分布的表现具有非指数式误差衰减.
- 错误指数中的对数衰减是一个关键特征.
- 这项研究突出了重尾与轻尾分布的统计测试的非对称性表现的根本差异.
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