Mathematical Sciences: Location of Outliers in Structured Data

首席调查员将研究结构化数据中的离群值检测。离群值是指看起来与大多数观测结果不同的观测数据。众所周知，当存在异常值时，许多参数估计过程不能产生良好的结果。有鉴于此，处理离群值的一种方法是最初检测它们的存在。研究人员将基于基本集合程序继续研究这一检测问题，其中包括将许多模型与数据进行拟合，每个模型与原始数据的最小子集精确匹配。以适当的方式组合来自这些基本集合的信息，可以在单次传递中可靠地识别多个离群值。

The principal investigator will study the detection of outliers in structured data. Outliers are observations which appear different from the bulk of observations. It is known that many parameter estimation procedures fail to produce good results when outliers are present. In light of this, one method of handling outliers is to initially detect their presence. The investigator will continue to study this detection problem based on the elemental sets procedure, which involves fitting to the data many models, each an exact fit to a minimally-sized subset of the original data. Combining the information from these elemental sets in suitable ways, one may identify the multiple outliers reliably, and in a single pass.