Abstract
This chapter is about the choice of the bandwidth (or smoothing factor) h ∈ (0, ∞) of the standard kernel estimate
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§11.8. References
L. Devroye, “Universal smoothing factor selection in density estimation: Theory and practice (with discussion),” Test, vol. 6, pp. 223–320, 1997.
L. Devroye, L. Györfi, and G. Lugosi, A Probabilistic Theory of Pattern Recognition, Springer-Verlag, New York, 1996.
L. Devroye and G. Lugosi, “A universally acceptable smoothing factor for kernel density estimation,” Annals of Statistics, vol. 24, pp. 2499–2512, 1996.
L. Devroye and G. Lugosi, “Non-asymptotic universal smoothing factors, kernel complexity and Yatracos classes,” Annals of Statistics, vol. 25, pp. 2626–2637, 1997.
L. Devroye and C. S. Penrod, “Distribution-free lower bounds in density estimation,” Annals of Statistics, vol. 12, pp. 1250–1262, 1984.
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Devroye, L., Lugosi, G. (2001). Bandwidth Selection for Kernel Estimates. In: Combinatorial Methods in Density Estimation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0125-7_11
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DOI: https://doi.org/10.1007/978-1-4613-0125-7_11
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