Mathematical Sciences: Conditional Inference in the Presenceof a Nuisance Parameter

数学科学：存在干扰参数时的条件推理

• 批准号: 9107062
• 负责人: Thomas Severini
• 金额: $ 3.86万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-07-15 至 1994-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9107062&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Conditional; Inference; Presenceof

In drawing statistical inferences when there are several variables present, often only some of these are of direct interest. However these are not always independent of the remainder. Therefore, inferences are usually drawn conditional upon the estimated values for the parameters which govern this remainder. Depending upon the nature of the dependencies and the particular estimates used, the primary statistical inferences may or may not be very stable. This research considers methods for constructing approximate ancillary statistics or close-to-ideal estimates for conditional inference in the presence of a multidimensional nuisance parameter.

当有几个变量存在时，在进行统计推断时，通常只有一些变量是直接相关的。然而，这些并不总是独立于其余的。因此，推论通常是根据支配这一余数的参数的估计值得出的。根据相关性的性质和使用的特定估计，主要的统计推断可能非常稳定，也可能不太稳定。这项研究考虑了在存在多维干扰参数的情况下，为条件推理构建近似辅助统计量或接近理想估计的方法。