Asymptotic properties of a conditional quantile estimator with randomly truncated data

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Abstract

Let Y be a response variable that is subject to left-truncation by a variable T. We consider the problem of estimating its conditional quantile function given a vector of covariates X. We derive almost sure (a.s.) consistency and asymptotic normality results for a kernel estimate of the conditional quantile function. Simulations are drawn to illustrate the results for finite samples.

AMS 1991 subject classifications

62G05
62G20

Keywords

Asymptotic normality
Consistency
Kernel
Quantile function
Truncated data

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