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Density Level Sets: Asymptotics, Inference, and Visualization
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DOI：10.1080/01621459.2016.1228536.png)
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摘要
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We study the plug-in estimator for density level sets under Hausdorff loss. We derive asymptotic theory for this estimator, and based on this theory, we develop two bootstrap confidence regions for level sets. We introduce a new technique for visualizing density level sets, even in multidimensions, which is easy to interpret and efficient to compute. Supplementary materials for this article are available online.
Keyword:
Anomaly detection
Asymptotic theory
Level set clustering
Nonparametric inference
Visualization
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