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- W3103358654 abstract "Taking projections of high-dimensional data is a common analytical and visualisation technique in statistics for working with high-dimensional problems. Sectioning, or slicing, through high dimensions is less common, but can be useful for visualising data with concavities, or non-linear structure. It is associated with conditional distributions in statistics, and also linked brushing between plots in interactive data visualisation. 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 non-linear structures in multivariate distributions." @default.
- W3103358654 created "2020-11-23" @default.
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- W3103358654 date "2020-07-02" @default.
- W3103358654 modified "2023-10-15" @default.
- W3103358654 title "A Slice Tour for Finding Hollowness in High-Dimensional Data" @default.
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- W3103358654 doi "https://doi.org/10.1080/10618600.2020.1777140" @default.
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