Learned-loss boosting

DOI10.1016/j.csda.2012.05.019zbMath1255.62112OpenAlexW2050405957MaRDI QIDQ1927174

James O. Ramsay, Giles Hooker

Publication date: 30 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2012.05.019

zbMATH Keywords

density estimationfunctional data analysisrobust estimates

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Nonparametric robustness (62G35)

Uses Software

• fda (R)
• gss

Cites Work

• Unnamed Item
• Greedy function approximation: A gradient boosting machine.
• On the estimation of a probability density function by the maximum penalized likelihood method
• Smoothing spline density estimation: Theory
• Functional data analysis.
• The elements of statistical learning. Data mining, inference, and prediction
• A practical guide to splines.
• Smoothing spline ANOVA models