Inverse boosting for monotone regression functions

DOI10.1016/J.CSDA.2004.05.038zbMath1429.62142OpenAlexW2087126112MaRDI QIDQ957242

Yuwon Kim, Ja-Yong Koo

Publication date: 26 November 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2004.05.038

zbMATH Keywords

monotonicityinverse problemsnonparametric regressionregression splinegradient boostingbase learner

Mathematics Subject Classification ID

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

Related Items (4)

Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography ⋮ Bayesian Nonparametric Estimation of Continuous Monotone Functions with Applications to Dose–Response Analysis ⋮ Nonparametric and robust methods. (Editorial) ⋮ A stochastic approximation view of boosting

Uses Software

• fda (R)

Cites Work

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• Greedy function approximation: A gradient boosting machine.
• A statistical perspective on ill-posed inverse problems (with discussion)
• Monotone nonparametric regression
• Estimating a smooth monotone regression function
• Nonparametric regression under qualitative smoothness assumptions
• Multivariate adaptive regression splines
• Applied functional data analysis. Methods and case studies
• A shape constrained smoother: simulation study
• A Flexible and Fast Method for Automatic Smoothing
• Functional estimation under shape constraints
• Comparing Automatic Smoothers (A Public Service Enterprise)
• Estimating Smooth Monotone Functions
• Monotone B-Spline Smoothing
• Polychotomous Regression
• Inequality-Constrained Multivariate Smoothing Splines with Application to the Estimation of Posterior Probabilities

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