Iteratively reweighted least square for kernel expectile regression with random features

DOI10.1080/00949655.2023.2182304OpenAlexW4323349134MaRDI QIDQ6050789

Yue Cui, Songfeng Zheng

Publication date: 19 September 2023

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2023.2182304

zbMATH Keywords

quadratic programmingweighted least squarekernel expectile regressionrandom Fourier features

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02) Statistics (62-XX)

Cites Work

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• Greedy function approximation: A gradient boosting machine.
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• Optimal expectile smoothing
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• Bayesian regularisation in geoadditive expectile regression
• KLERC: kernel Lagrangian expectile regression calculator
• 10.1162/15324430152748218
• Nonparametric multiple expectile regression via ER-Boost
• A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines

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