Minimax optimal estimation in partially linear additive models under high dimension

DOI10.3150/18-BEJ1021zbMath1431.62175arXiv1612.05906MaRDI QIDQ1740526

Xianqiang Yang

Publication date: 30 April 2019

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.05906

zbMATH Keywords

semiparametrichigh dimensionminimax optimalpartial linear additive model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12) Minimax procedures in statistical decision theory (62C20)

Related Items (2)

Test for high dimensional partially linear models ⋮ Oracle posterior contraction rates under hierarchical priors

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotic properties of lasso in high-dimensional partially linear models
• Fast learning rate of multiple kernel learning: trade-off between sparsity and smoothness
• Semi-parametric regression: efficiency gains from modeling the nonparametric part
• Minimax optimal rates of estimation in high dimensional additive models
• Statistics for high-dimensional data. Methods, theory and applications.
• Sparsity in multiple kernel learning
• Optimal estimation in additive regression models
• Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
• SCAD-penalized regression in high-dimensional partially linear models
• Spline smoothing in regression models and asymptotic efficiency in \(L_ 2\)
• Additive regression and other nonparametric models
• Nonasymptotic analysis of semiparametric regression models with high-dimensional parametric coefficients
• Minimax risks for sparse regressions: ultra-high dimensional phenomenons
• Sparse and efficient estimation for partial spline models with increasing dimension
• Penalized least squares estimation in the additive model with different smoothness for the components
• Confidence sets in sparse regression
• On the uniform convergence of empirical norms and inner products, with application to causal inference
• Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models
• The Partial Linear Model in High Dimensions
• Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
• Minimax-optimal rates for sparse additive models over kernel classes via convex programming
• Introduction to nonparametric estimation

This page was built for publication: Minimax optimal estimation in partially linear additive models under high dimension