Weighted quantile estimators
Methodology
2023-04-17 v1
Abstract
In this paper, we consider a generic scheme that allows building weighted versions of various quantile estimators, such as traditional quantile estimators based on linear interpolation of two order statistics, the Harrell-Davis quantile estimator and its trimmed modification. The obtained weighted quantile estimators are especially useful in the problem of estimating a distribution at the tail of a time series using quantile exponential smoothing. The presented approach can also be applied to other problems, such as quantile estimation of weighted mixture distributions.
Cite
@article{arxiv.2304.07265,
title = {Weighted quantile estimators},
author = {Andrey Akinshin},
journal= {arXiv preprint arXiv:2304.07265},
year = {2023}
}
Comments
28 pages, 13 figures, the paper source code is available at https://github.com/AndreyAkinshin/paper-wqe