Likelihood cross-validation bandwidth selection for nonparametric kernel density estimatorsFootnote^†
AMS 1980 subject classifications Primary 62602: secondary 62020. xPart of this work was prepared with the support of the Netherlands Organization for Scientific Research, Grant number SMC 611-303-013.

Bert Van Es Department of Mathematics and Computer Science, University of Amsterdam, Plantage Muidergracht 24, 1018 TV, Amsterdam, The Netherlands

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A. J. Van Es & A. J. Hoogstrate. (1997) How much do plug-in bandwidth selectors adapt to non-smoothness?. Journal of Nonparametric Statistics 8:2, pages 185-197.
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Somayeh Rahmani, Vahid Khajehvand & Mohsen Torabian. (2020) Kullback-Leibler distance criterion consolidation in cloud. Journal of Network and Computer Applications 170, pages 102789.
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Yongjin Kim, Gyeongdeok Kim, Yongtae Lee & Kwangho Jang. (2020) Bandwidth Selection of Kernel Density Estimation for GIS-based Crime Occurrence Map Visualization. Bandwidth Selection of Kernel Density Estimation for GIS-based Crime Occurrence Map Visualization.

Qing Wang & Bruce G. Lindsay. (2015) Improving cross-validated bandwidth selection using subsampling-extrapolation techniques. Computational Statistics & Data Analysis 89, pages 51-71.
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Bert van Es. (1997) A note on the integrated squared error of a kernel density estimator in non-smooth cases. Statistics & Probability Letters 35:3, pages 241-250.
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