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Activity Number:
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584
- Advances in Semi- and Nonparametric Statistical Analysis
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2018 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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Abstract #329094
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Presentation
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Title:
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Asymptotics and Optimal Bandwidth Selection for Nonparametric Estimation of Density Level Sets
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Author(s):
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Wanli Qiao*
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Companies:
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George Mason University
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Keywords:
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level set; kernel density; nonparametric statistics; geometry; bandwidth selection; asymptotics
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Abstract:
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Bandwidth selection is crucial in the kernel estimation of density level sets. Risk based on the symmetric difference between the estimated and true level sets is usually used to measure their proximity. We provide an asymptotic Lp approximation to this risk, where p is characterized by the weight function in the risk. In particular the excess risk corresponds to an L2 type of risk, and is adopted in an optimal bandwidth selection rule for nonparametric level set estimation of d-dimensional density functions (d>=1).
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Authors who are presenting talks have a * after their name.
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