Large deviations for the L1-distance in kernel density estimation

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Abstract We establish a large deviation limit theorem of Chernoff type for the L1-distance between the nonparametric kernel density estimator and the underlying density. The estimation is based on a sequence of independent and identically distributed random variables. The rate function is well identified, distribution-free and independent of the choice of the kernel.