Outlier Detection Based on Robust Mahalanobis Distance and Its Application

• 作者: Lifang Li Songren Deng Xu Li Yunchuan Jiang
• 来源期刊: 统计学期刊(英文)
• 学科: 工学
• 关键词: MCD ESTIMATOR Rocke ESTIMATOR OUTLIER Mahalanobis DISTANCE
• 年，卷（期）: 2019,（1）
• 页码范围: 15-26
• 页数: 12页
• 分类号: TP39

摘要

Classical Mahalanobis distance is used as a method of detecting outliers, and is affected by outliers. Some robust Mahalanobis distance is proposed via the fast MCD estimator. However, the bias of the MCD estimator increases significantly as the dimension increases. In this paper, we propose the improved Mahalanobis distance based on a more robust Rocke estimator under high-dimensional data. The results of numerical simulation and empirical analysis show that our proposed method can better detect the outliers in the data than the above two methods when there are outliers in the data and the dimensions of data are very high.