Algorithms for robust multivariate statistics

数理统计提供了许多有用的分析和解释技术，可用于任何有实验或测量数据的领域。然而，其中一些技术需要大量的计算，这使得它们很难在越来越频繁的大型数据集上使用。拟议的研究项目将侧重于寻找更有效的方法来使用计算机来应用数理统计中的电力分析技术。这将允许将这些技术应用于海量数据集，以便执行以前不可能进行的分析。例如，这种数据集出现在地理信息系统、遥感、卫星图像、医学图像、商业管理系统和生物信息学中。

Mathematical statistics provides many useful analysis and interpretation techniques that can be used in any field where experimental or measured data is present. However, some of these techniques require large amounts of computation that make them difficult to use on large data sets that occur increasingly often. The proposed research project will focus on finding more efficient ways of using a computer to apply power analysis techniques from mathematical statistics. This will allow the application of these techniques to massive data sets in order to perform analyses that were previously not possible. Such data sets occur, for example, in geographic information systems, remote sensing, satellite imagery, medical imagery, business management systems, and bioinformatics.