Optimal asymptotic quadratic error of density estimators for strong mixing or chaotic data
Under mild mixing conditions, we show that the kernel density estimator has exactly the same asymptotic quadratic error as in the i.i.d. case. Curiously, that result remains almost valid if the data are chaotic.
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Volume (Year): 22 (1995)
Issue (Month): 4 (March)
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- Vieu, Philippe, 1991. "Quadratic errors for nonparametric estimates under dependence," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 324-347, November.
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