Gradient boosting for extreme quantile regression
From MaRDI portal
Publication:6144813
DOI10.1007/s10687-023-00473-xarXiv2103.00808OpenAlexW3135716056MaRDI QIDQ6144813
Sebastian Engelke, Jasper Velthoen, Clément Dombry, Juan-Juan Cai
Publication date: 8 January 2024
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2103.00808
extreme value theorygeneralized Pareto distributiontree-based methodsgradient boostingextreme quantile regression
Nonparametric regression and quantile regression (62G08) Extreme value theory; extremal stochastic processes (60G70)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- Generalized random forests
- Estimating tails of probability distributions
- Residual life time at great age
- Statistical inference using extreme order statistics
- Exceedances over high thresholds: a guide to threshold selection
- Tail dimension reduction for extreme quantile estimation
- Cyber claim analysis using generalized Pareto regression trees with applications to insurance
- Improving precipitation forecasts using extreme quantile regression
- Extremal quantile regression
- On kernel smoothing for extremal quantile regression
- Regression Quantiles
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- On a Minimum Distance Procedure for Threshold Selection in Tail Analysis
- Generalized Additive Models for Exceedances of High Thresholds With an Application to Return Level Estimation for U.S. Wind Gusts
- Tail Index Regression
- Generalized Additive Modelling of Sample Extremes
- Optimization by Gradient Boosting
- Random forests
- Stochastic gradient boosting.