A robust spline approach in partially linear additive models

DOI10.1016/j.csda.2022.107611OpenAlexW3186046688WikidataQ114191792 ScholiaQ114191792MaRDI QIDQ2101391

Graciela Boente, Alejandra Mercedes Martínez

Publication date: 6 December 2022

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

Full work available at URL: https://arxiv.org/abs/2107.12987

zbMATH Keywords

\(B\)-splinesrobust estimationpartially linear additive models

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• robustbase

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric estimation of regression functions with both categorical and continuous data
• Robust estimation and variable selection in censored partially linear additive models
• High breakdown-point and high efficiency robust estimates for regression
• Additive models for quantile regression: model selection and confidence bands
• Spline-backfitted kernel smoothing of partially linear additive model
• Two-step spline estimating equations for generalized additive partially linear models with large cluster sizes
• Pointwise and uniform convergence of Fourier extensions
• Robust estimation for semi-functional linear regression models
• Efficient and fast spline-backfitted kernel smoothing of additive models
• Variable selection in nonparametric additive models
• Additive regression and other nonparametric models
• Hedonic housing prices and the demand for clean air
• Robust nonparametric regression estimation
• Convergence rate of sieve estimates
• Convergence rates and asymptotic normality for series estimators
• Robust estimators in semiparametric partly linear regression models.
• Variable selection in high-dimensional partially linear additive models for composite quantile regression
• Direct estimation of low-dimensional components in additive models.
• Bivariate tensor-product \(B\)-splines in a partly linear model
• Nonparametric and semiparametric models.
• Weak convergence and empirical processes. With applications to statistics
• Robust estimators in a generalized partly linear regression model under monotony constraints
• Kernel estimation of a partially linear additive model
• The asymptotics of MM-estimators for linear regression with fixed designs
• A Spline-Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval-Censored Data
• Variable selection in high-dimensional partly linear additive models
• Additive partial linear models with measurement errors
• Bounded Influence and High Breakdown Point Testing Procedures in Linear Models
• Estimation in a semiparametric model for longitudinal data with unspecified dependence structure
• A Fast Procedure for Outlier Diagnostics in Large Regression Problems
• Robust Statistics
• Additive regression splines with irrelevant categorial and continuous regressors
• Asymptotics for Redescending M-estimators in Linear Models with Increasing Dimension
• Nonparametric and Semiparametric Estimation of Additive Models with Both Discrete and Continuous Variables under Dependence
• On the convergence rates of Legendre approximation
• Estimation and variable selection for semiparametric additive partial linear models
• Partially linear additive quantile regression in ultra-high dimension

This page was built for publication: A robust spline approach in partially linear additive models