Cover Image

Generalized random forest for extreme quantile regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vidagbandji, Lucien M., Berred, Alexandre, Bertelle, Cyrille, Amanton, Laurent
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Penalized estimation of GEV parameters for extreme quantile regression
by: Vidagbandji, Lucien M., et al.
Published: (2026)

Global quantile regression
by: Mrkvička, Tomáš, et al.
Published: (2023)

Extreme quantile regression with deep learning
by: Richards, Jordan, et al.
Published: (2024)

General Bayesian quantile regression for counts via generative modeling
by: Yamauchi, Yuta, et al.
Published: (2024)

Targeted tuning of random forests for quantile estimation and prediction intervals
by: Berkowitz, Matthew, et al.
Published: (2025)

A simulation study comparing statistical approaches for estimating extreme quantile regression with an application to forecasting of fire risk
by: Bernoussi, Amina El, et al.
Published: (2025)

Interval-censored linear quantile regression
by: Choi, Taehwa, et al.
Published: (2024)

Non-crossing convex quantile regression
by: Dai, Sheng, et al.
Published: (2022)

An efficient hybrid approach of quantile and expectile regression
by: Atanane, Abdellah, et al.
Published: (2025)

Change-plane analysis in functional response quantile regression
by: Guan, Xin, et al.
Published: (2025)

Multinomial probit model based on joint quantile regression
by: Okabe, Masaaki, et al.
Published: (2025)

The $\infty$-S test via regression quantile affine LASSO
by: Sardy, Sylvain, et al.
Published: (2024)

Locally sparse estimation for simultaneous functional quantile regression
by: Hu, Boyi, et al.
Published: (2026)

On function-on-function linear quantile regression
by: Mutis, Muge, et al.
Published: (2025)

Nonparametric quantile regression for spatio-temporal processes
by: Deb, Soudeep, et al.
Published: (2024)

Asymptotically-exact selective inference for quantile regression
by: Wang, Yumeng, et al.
Published: (2024)

Optimal subsampling for functional composite quantile regression in massive data
by: Pan, Jingxiang, et al.
Published: (2024)

Bayesian structured additive quantile regression for inflated bounded data
by: Queiroz, Francisco F., et al.
Published: (2026)

Penalized function-on-function linear quantile regression
by: Beyaztas, Ufuk, et al.
Published: (2025)

Inference on multiple quantiles in regression models by a rank-score approach
by: De Santis, Riccardo, et al.
Published: (2025)

Convolution-smoothing based locally sparse estimation for functional quantile regression
by: Liu, Hua, et al.
Published: (2025)

Semiparametric model averaging for high-dimensional quantile regression with nonignorable nonresponse
by: Xiong, Wei, et al.
Published: (2025)

Dynamic Bayesian regression quantile synthesis for forecasting outlook-at-risk
by: Kobayashi, Genya, et al.
Published: (2026)

A lack-of-fit test for quantile regression models with high-dimensional covariates
by: Conde-Amboage, Mercedes, et al.
Published: (2015)

Valid standard errors for Bayesian quantile regression with clustered and independent data
by: Ji, Feng, et al.
Published: (2024)

Invariant quantile regression for heterogeneous environments
by: Fu, Bo, et al.
Published: (2026)

Semiparametric quantile functional regression analysis of adolescent physical activity distributions in the presence of missing data
by: Ren, Benny, et al.
Published: (2024)

Fréchet random forests for metric space valued regression with non euclidean predictors
by: Capitaine, Louis, et al.
Published: (2019)

A robust mixed-effects quantile regression model using generalized Laplace mixtures to handle outliers and skewness
by: Burger, Divan A., et al.
Published: (2025)

Adjusting for bias due to measurement error in functional quantile regression models with error-prone functional and scalar covariates
by: Chen, Xiwei, et al.
Published: (2024)

Selecting fitted models under epistemic uncertainty using a stochastic process on quantile functions
by: René, Alexandre, et al.
Published: (2024)

Mixed effects models for extreme value index regression
by: Momoki, Koki, et al.
Published: (2023)

Model averaging with mixed criteria for estimating high quantiles of extreme values: Application to heavy rainfall
by: Shin, Yonggwan, et al.
Published: (2025)

Distributional outcome regression via quantile functions and its application to modelling continuously monitored heart rate and physical activity
by: Ghosal, Rahul, et al.
Published: (2023)

Partial frontiers are not quantiles
by: Dai, Sheng, et al.
Published: (2022)

Spatial quantile clustering of climate data
by: Gaetan, Carlo, et al.
Published: (2024)

Likelihood-ratio inference on differences in quantiles
by: Miller, Evan
Published: (2023)

Length-biased Birnbaum-Saunders quantile regression with application to water evaporation
by: Saulo, Helton, et al.
Published: (2026)

Monge-Kantorovich quantiles and ranks for image data
by: Thurin, Gauthier
Published: (2025)

The quantile-based classifier with variable-wise parameters
by: Berrettini, Marco, et al.
Published: (2024)