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- W4321471569 abstract "Density-based clustering methodology has been widely considered in the statistical literature for classifying Euclidean observations. However, this approach has not been contemplated for directional data yet. In this work, directional density-based clustering methodology is fully established for the unit hypersphere by solving the computational problems associated to high dimensional spaces. We also provide a circular and spherical exploratory tool for studying the effect of the smoothing parameter when kernel density estimation methods are considered. An extensive simulation study shows the performance of the resulting classification procedure for the circle and for the sphere. The methodology is also applied to analyse an exoplanets dataset." @default.
- W4321471569 created "2023-02-22" @default.
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- W4321471569 date "2023-02-20" @default.
- W4321471569 modified "2023-09-24" @default.
- W4321471569 title "Directional density-based clustering" @default.
- W4321471569 doi "https://doi.org/10.48550/arxiv.2302.09897" @default.
- W4321471569 hasPublicationYear "2023" @default.
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