RT Journal Article
T1 Kernel density estimation with doubly truncated data
A1 Moreira, Carla Maria
A1 De Uña Alvarez, Jacobo
K1 12 Matemáticas
AB 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.
PB Electronic Journal of Statistics
SN 19357524
YR 2012
FD 2012
LK http://hdl.handle.net/11093/1023
UL http://hdl.handle.net/11093/1023
LA eng
NO Electronic Journal of Statistics, 6: 501-521 (2012)
DS Investigo
RD 20-ene-2025