The Annals of Statistics

Nearest Neighbor Estimation of a Bivariate Distribution Under Random Censoring

Michael G. Akritas

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Abstract

We consider the problem of estimating the bivariate distribution of the random vector $(X, Y)$ when $Y$ may be subject to random censoring. The censoring variable $C$ is allowed to depend on $X$ but it is assumed that $Y$ and $C$ are conditionally independent given $X = x$. The estimate of the bivariate distribution is obtained by averaging estimates of the conditional distribution of $Y$ given $X = x$ over a range of values of $x$. The weak convergence of the centered estimator multiplied by $n^{1/2}$ is obtained, and a closed-form expression for the covariance function of the limiting process is given. It is shown that the proposed estimator is optimal in the Beran sense. This is similar to an optimality property the product-limit estimator enjoys. Using the proposed estimator of the bivariate distribution, an extension of the least squares estimator to censored data polynomial regression is obtained and its asymptotic normality established.

Article information

Source
Ann. Statist. Volume 22, Number 3 (1994), 1299-1327.

Dates
First available in Project Euclid: 11 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176325630

JSTOR
links.jstor.org

Digital Object Identifier
doi:10.1214/aos/1176325630

Mathematical Reviews number (MathSciNet)
MR1311977

Zentralblatt MATH identifier
0819.62028

Subjects
Primary: 62G05: Estimation
Secondary: 62G30: Order statistics; empirical distribution functions 62H12: Estimation 62J05: Linear regression

Keywords
Conditional empirical processes conditional Kaplan-Meier estimator weak convergence Beran optimality polynomial regression

Citation

Akritas, Michael G. Nearest Neighbor Estimation of a Bivariate Distribution Under Random Censoring. The Annals of Statistics 22 (1994), no. 3, 1299--1327. doi:10.1214/aos/1176325630. http://projecteuclid.org/euclid.aos/1176325630.


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