Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes

Huang Chu and Zhang Li-Xin

Communications in Statistics - Theory and Methods, 2014, vol. 43, issue 22, 4669-4678

Abstract: In this article, we discuss the method of linear kernel quantile estimator proposed by Parzen (1979). We establish a Bahadur representation in sense of almost surely convergence with the rate log− αn under the case of S-mixing random variable sequence which was proposed by Berkes (2009). We also obtain the strong consistence of this estimator and its convergence rate.

Date: 2014
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DOI: 10.1080/03610926.2012.736582

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