Adaptive normal reference bandwidth based on quantile for kernel density estimation
AbstractBandwidth selection is an important problem of kernel density estimation. Traditional simple and quick bandwidth selectors usually oversmooth the density estimate. Existing sophisticated selectors usually have computational difficulties and occasionally do not exist. Besides, they may not be robust against outliers in the sample data, and some are highly variable, tending to undersmooth the density. In this paper, a highly robust simple and quick bandwidth selector is proposed, which adapts to different types of densities.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.
Volume (Year): 38 (2011)
Issue (Month): 12 (March)
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