Some asymptotic results for kernel density estimation under random censorship
Zhang, Biao
Bernoulli, Tome 2 (1996) no. 3, p. 183-198 / Harvested from Project Euclid
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Random censored data consist of i.i.d. pairs of observations (Xi,δi), i=1,...,n. If δi=0, Xi denotes a censored observation, and if δi=1, Xi denotes a survival time, which is the variable of interest. In this paper, we apply the martingale method for counting processes to study asymptotic properties for the kernel estimator of the density function of the survival times. We also derive an asymptotic expression for the mean integrated square error of the kernel density estimator, which can be used to obtain an asymptotically optimal bandwidth.
Publié le : 1996-06-14
Classification:  bandwidth,  counting process,  martingale,  Kaplan-Meier estimator,  mean integrated square error 
@article{1193839223,
     author = {Zhang, Biao},
     title = {Some asymptotic results for kernel density estimation under random censorship},
     journal = {Bernoulli},
     volume = {2},
     number = {3},
     year = {1996},
     pages = { 183-198},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1193839223}
}

Zhang, Biao. Some asymptotic results for kernel density estimation under random censorship. Bernoulli, Tome 2 (1996) no. 3, pp.  183-198. http://gdmltest.u-ga.fr/item/1193839223/