论文标题
非规范环境中的可能性渐近学：重点是可能性比的评论
Likelihood Asymptotics in Nonregular Settings: A Review with Emphasis on the Likelihood Ratio
论文作者
论文摘要
本文回顾了最常见的情况，其中一种或多种规律性条件是基于经典可能性的参数推理失败的基础。我们确定了三个主要问题类别：边界问题，不确定的参数问题 - 包括不可识别的参数和单数信息矩阵以及更改点问题。该评论重点介绍了似然比统计量的大样本特性。我们强调分析解决方案并在可用的情况下确认软件实施。此外，我们还提供了有关推导关键结果的可能工具的摘要见解。补充材料的注释书目列出了假设检验和与估计联系的其他方法。
This paper reviews the most common situations where one or more regularity conditions which underlie classical likelihood-based parametric inference fail. We identify three main classes of problems: boundary problems, indeterminate parameter problems -- which include non-identifiable parameters and singular information matrices -- and change-point problems. The review focuses on the large-sample properties of the likelihood ratio statistic. We emphasize analytical solutions and acknowledge software implementations where available. We furthermore give summary insight about the possible tools to derivate the key results. Other approaches to hypothesis testing and connections to estimation are listed in the annotated bibliography of the Supplementary Material.
