Abstract
A new kernel-type density estimator is presented in the context of left truncated and right censored data. This estimator is obtained by the convolution of a kernel with an estimator of the distribution function based on presmoothing ideas. Asymptotic properties, including an i.i.d. representation, consistency, asymptotic normality and mean integrated squared error expressions, are given. The practical performance of this estimator is illustrated in a simulation study and used to analyse the lifetime density in a real data example.
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