Asymptotic Properties of Conditional Quantile Estimator Under Left-Truncated and α-Mixing Conditions

Author: Wang Jiang-Feng  

Publisher: Taylor & Francis Ltd

ISSN: 0361-0926

Source: Communications in Statistics: Theory and Methods, Vol.40, Iss.14, 2011-01, pp. : 2462-2486

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Abstract

In this article, we establish strong uniform convergence and asymptotic normality of estimators of conditional quantile and conditional distribution function for a left truncated model when the data exhibit some kind of dependence. It is assumed that the observations form a stationary α-mixing sequence. The results of Lemdani et al. (2009) are relaxed from the i.i.d. assumption to α-mixing setting. Finite sample behavior of the estimators is investigated via simulations as well.