Facultade de Fisioterapia

Kernel density estimation with doubly truncated data

Moreira, Carla; de Uña-Álvarez, Jacobo
Abstract:
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. Real data illustration is included.
Year:
2012
Type of Publication:
Article
Journal:
Electronic Journal of Statistics
Volume:
6
Pages:
501-521
Month:
January
DOI:
http://dx.doi.org/10.1214/12-EJS683
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