Chinese Annals of Mathematics, Series B

, Volume 36, Issue 6, pp 969–990 | Cite as

Conditional quantile estimation with truncated, censored and dependent data

  • Hanying LiangEmail author
  • Deli Li
  • Tianxuan Miao


This paper deals with the conditional quantile estimation based on left-truncated and right-censored data. Assuming that the observations with multivariate covariates form a stationary α-mixing sequence, the authors derive the strong convergence with rate, strong representation as well as asymptotic normality of the conditional quantile estimator. Also, a Berry-Esseen-type bound for the estimator is established. In addition, the finite sample behavior of the estimator is investigated via simulations.


Berry-Esseen-type bound Conditional quantile estimator Strong representation Truncated and censored data α-mixing 

2000 MR Subject Classification

62N02 62G20 


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Copyright information

© Fudan University and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of MathematicsTongji UniversityShanghaiChina
  2. 2.Department of Mathematical SciencesLakehead UniversityThunder Bay, OntarioCanada

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