High quantile regression for extreme events

High quantile regression for extreme events

Abstract For extreme events, estimation of high conditional quantiles for heavy tailed distributions is an important problem. Quantile regression is a useful method in this field with many applications. Quantile regression uses an L 1-loss function, and an optimal solution by means of linear program...

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Bibliographic Details
Main Authors: Mei Ling Huang, Christine Nguyen
Format: Article
Language:English
Published: SpringerOpen 2017-05-01
Series:Journal of Statistical Distributions and Applications
Subjects:
Bivariate Pareto distribution
Conditional quantile
Extreme value distribution
Generalized Pareto distribution
Linear programming
Weighted loss function
Online Access:http://link.springer.com/article/10.1186/s40488-017-0058-3

Internet

http://link.springer.com/article/10.1186/s40488-017-0058-3

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