Directional Outlyingness for Multivariate Functional Data
讲座名称：
Directional Outlyingness for Multivariate Functional Data
讲座时间：
2019-11-18
讲座人：
代文林
形式：
校区：
兴庆校区
实践学分：
讲座内容：
报告题目：Directional Outlyingness for Multivariate Functional Data
报告时间：11月18日下午2：30—4：00
报告地点: 数学楼2-3会议室
报告人：代文林
报告摘要：
The direction of outlyingness is crucial to describing the centrality of multivariate functional data. Motivated by this idea, classical depth is generalized to directional outlyingness for functional data. Theoretical properties of functional directional outlyingness are investigated and the total outlyingness can be naturally decomposed into two parts: magnitude outlyingness and shape outlyingness which represent the centrality of a curve for magnitude and shape, respectively. This decomposition serves as a visualization tool for the centrality of curves. Furthermore, an outlier detection procedure is proposed based on functional directional outlyingness.
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