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A slice tour for finding hollowness in high-dimensional data
Journal of Computational and Graphical Statistics ( IF 1.4 ) Pub Date : 2020-07-02 , DOI: 10.1080/10618600.2020.1777140
Ursula Laa 1, 2 , Dianne Cook 2 , German Valencia 1
Affiliation  

Abstract Taking projections of high-dimensional data is a common analytical and visualization technique in statistics for working with high-dimensional problems. Sectioning, or slicing, through high dimensions is less common, but can be useful for visualizing data with concavities, or nonlinear structure. It is associated with conditional distributions in statistics, and also linked brushing between plots in interactive data visualization. This short technical note describes a simple approach for slicing in the orthogonal space of projections obtained when running a tour, thus presenting the viewer with an interpolated sequence of sliced projections. The method has been implemented in R as an extension to the tourr package, and can be used to explore for concave and nonlinear structures in multivariate distributions. Supplementary materials for this article are available online.

中文翻译:

在高维数据中寻找空洞的切片之旅

摘要 对高维数据进行投影是统计学中处理高维问题的常用分析和可视化技术。通过高维进行切片或切片不太常见,但可用于可视化具有凹面或非线性结构的数据。它与统计中的条件分布相关联,还与交互式数据可视化中的绘图之间的刷亮相关联。这个简短的技术说明描述了一种简单的方法,用于在运行游览时获得的投影的正交空间中进行切片,从而向观看者展示一个插入的切片投影序列。该方法已在 R 中实现,作为 Tourr 包的扩展,可用于探索多元分布中的凹面和非线性结构。
更新日期:2020-07-02
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