论文标题
什么是可能性函数，如何在粒子物理学中使用？
What is the likelihood function, and how is it used in particle physics?
论文作者
论文摘要
在LHC和粒子物理学的其他地方的数据分析中，可能性函数无处不在。部分原因是“概率”和“可能性”是日常英语中的虚拟同义词，但在数据分析中至关重要，因此有很大的混乱潜力。此外，统计推断的每种方法（可能性主义者，内曼 - 佩森，贝叶斯）都以不同的方式使用了似然函数。本说明旨在在高级本科生或初学者级别的研究生级别提供一些简短的介绍，并引用了一些论文，并包含许多有关可能性文献的指示。在统计的哲学基础中，提到了可能性原理（在粒子物理学分析中经常违反）。
Likelihood functions are ubiquitous in data analyses at the LHC and elsewhere in particle physics. Partly because "probability" and "likelihood" are virtual synonyms in everyday English, but crucially distinct in data analysis, there is great potential for confusion. Furthermore, each of various approaches to statistical inference (likelihoodist, Neyman-Pearson, Bayesian) uses the likelihood function in different ways. This note is intended to provide a brief introduction at the advanced undergraduate or beginning graduate student level, citing a few papers giving examples and containing numerous pointers to the vast literature on likelihood. The Likelihood Principle (routinely violated in particle physics analyses) is mentioned as an unresolved issue in the philosophical foundations of statistics.
