@article{paperid:1023912,
author = {Fakoor, Vahid and Sara Jomhoori and Ganjeali, Atieh},
title = {Density estimators for truncated dependent data},
journal = {Journal of the Iranian Statistical Society},
year = {2011},
volume = {10},
number = {1},
month = {March},
issn = {1726-4057},
pages = {45--61},
			numpages = {16},
keywords = {In some long term studies; a series of dependent and possibly
truncated lifetime data may be observed. Suppose that the lifetimes
have a common continuous distribution function F. A popular stochastic
measure of the distance between the density function f of the lifetimes
and its kernel estimate fn is the integrated square error (ISE). In this
paper; we derive a central limit theorem for the integrated square error
of the kernel density estimators in the left-truncation model. It is
assumed that the lifetime observations form a stationary strong mixing
sequence. A central limit theorem (CLT) for the ISE of the kernel hazard
rate estimators is also presented.},
}