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Kernel density estimation with doubly truncated data

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Kernel density estimation with doubly truncated data

Moreira, Carla Maria; De Uña Alvarez, Jacobo
DATE : 2012
UNESCO SUBJECT : 12 Matemáticas


In some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, which may be the NPMLE [2] or a semiparametric estimator [9]. Asymptotic properties of the introduced estimators are explored. Their finite sample behaviour is investigated through simulations.

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