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On the u-th Geometric Conditional Quantile

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Author Info
Yebin Cheng () (Faculty of Economics and Econometrics, Universiteit van Amsterdam)
Jan G. de Gooijer () (Faculty of Economics and Econometrics, Universiteit van Amsterdam)

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Abstract

Motivated by Chaudhuri's work (1996) on unconditional geometric quantiles, we explore the asymptotic properties of sample geometric conditional quantiles, defined through kernel functions, in high dimensional spaces. We establish a Bahadur type linear representation for the geometric conditional quantile estimator and obtain the convergence rate for the corresponding remainder term. From this, asymptotic normality on the estimated geometric conditional quantile is derived. Based on these results we propose confidence ellipsoids for multivariate conditional quantiles. The methodology is illustrated via data analysis and a Monte Carlo study.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 04-072/4.

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Date of creation: 29 Jun 2004
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Handle: RePEc:dgr:uvatin:20040072

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Related research
Keywords: Asymptotic normality; Bahadur representation; geometric conditional quantile; confidence ellipsoids; kernel function;

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

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References listed on IDEAS
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  1. Abdous, B. & Theodorescu, R., 1992. "Note on the spatial quantile of a random vector," Statistics & Probability Letters, Elsevier, vol. 13(4), pages 333-336, March. [Downloadable!] (restricted)
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