Variance of the bivariate density estimator for left truncated right censored data

Kathryn Prewitt and Ulkü Gürler

Statistics & Probability Letters, 1999, vol. 45, issue 4, 351-358

Abstract: In this study the variance of the bivariate kernel density estimators for the left truncated and right censored (LTRC) observations are considered. In LTRC models, the complete observation of the variable Y is prevented by the truncating variable T and the censoring variable C. Consequently, one observes the i.i.d. samples from the triplets (T,Z,[delta]) only if T[less-than-or-equals, slant]Z, Z=min(Y,C) and [delta] is one if Z=Y and zero otherwise. Gürler and Prewitt (1997, submitted for publication) consider the estimation of the bivariate density function via nonparametric kernel methods and establish an i.i.d. representation of their estimators. Asymptotic variance of the i.i.d. part of their representation is developed in this paper. Application of the results are also discussed for the data-driven and the least-squares cross validation bandwidth choice procedures.

Keywords: Bivariate; distribution; Truncation/censoring; Kernel; density; estimators (search for similar items in EconPapers)
Date: 1999
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