Time series quantile regression using random forests

DOI10.1111/JTSA.12731MaRDI QIDQ6641051

Tomoshige Nakamura, Ryotato Shibuki, Hiroshi Shiraishi

Publication date: 20 November 2024

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

zbMATH Keywords

quantile regressionnonlinear autoregressive modelrandom forest

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Markov processes: estimation; hidden Markov models (62M05) Inference from stochastic processes (62Mxx)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Nonparametric estimation of conditional VaR and expected shortfall
• Generalized random forests
• Autoregression quantiles and related rank-scores processes
• Modeling of time series using random forests: theoretical developments
• Introduction to empirical processes and semiparametric inference
• Consistency of random forests
• Non-linear time series and Markov chains
• Local Linear Quantile Regression
• Estimation of Dynamic Models with Error Components
• Regression Quantiles
• Methods for Estimating a Conditional Distribution Function
• Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
• REGRESSION QUANTILES FOR TIME SERIES
• Random forests

This page was built for publication: Time series quantile regression using random forests

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6641051)