Large deviations for the L1-distance in kernel density estimation

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.