A note on the monotonicity of the ES algorithm

DOI10.1080/00949655.2011.553195zbMath1432.62116OpenAlexW1977443069MaRDI QIDQ4912050

Zhengxiao Wu

Publication date: 21 March 2013

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

Full work available at URL: https://doi.org/10.1080/00949655.2011.553195

zbMATH Keywords

M-estimationES algorithmpenalized least-squaresrobust smoothingpseudo-data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Variable selection in quantile regression when the models have autoregressive errors

Cites Work

• Asymptotics for M-type smoothing splines
• The Role of Pseudo Data for Robust Smoothing with Application to Wavelet Regression

This page was built for publication: A note on the monotonicity of the ES algorithm