# 再谈“学生氏t-分布”

“最小信息熵准则”表述为：对于给定的数据考虑一组备选概率分布，最佳分布是具有最小信息熵的分布【6最大信息度准则”表述为：对于给定的数据考虑一组备选概率分布，最佳分布是具有最大信息度的分布【7这两个准则是等价的，因为信息熵和信息度的含义相反：信息熵是系统不确定性的量度，而信息度是系统确定性的量度。

1Huang H (2018) Uncertainty estimation with a small number of measurements, Part I: new insights on the t-interval method and its limitations Measurement Science and Technology 29  https://doi.org/10.1088/1361-6501/aa96c7

2  黄河宁（2020为什么基于t-分布计算小样本测量不确定度是一个谬误？-3 个悖论及其消解，ResearchGate 链接：https://www.researchgate.net/publication/343039726_weishenmejiyu_t-fenbujisuanxiaoyangbenceliangbuquedingdushiyigemiuwu_-3_gebeilunjiqixiaojie

3  黄河宁（2022关于学生氏t-分布的几点澄清，科学网，https://blog.sciencenet.cn/blog-3427112-1352436.html

4  黄河宁（2022为什么会产生对t-值和学生氏t-分布的认知偏差？科学网，https://blog.sciencenet.cn/blog-3427112-1353059.html

5  黄河宁（2022基于学生氏t-分布推断的谬误：两个悖论及其解决方法，及‘t-转换扭曲’”—PPT文件, 科学网，https://blog.sciencenet.cn/blog-3427112-1349082.html

6Huang, H. (2023) A minimum entropy criterion for distribution selection for measurement uncertainty analysisMeasurement Science and Technology, 35 (2024) 035014,  https://iopscience.iop.org/article/10.1088/1361-6501/ad1476

7Huang, H. (2023) A theory of informity, preprint, ResearchGatehttps://www.researchgate.net/publication/376206296_A_theory_of_informity

8D’Agostini G 1998  Jeffeys priors versus experienced physicist priors: arguments against objective Bayesian theory Proceedings of the 6th Valencia International Meeting on Bayesian Statistics (Alcossebre, Spain, May 30th-June 4th)

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