A nonparametric procedure for linear and nonlinear variable screening

DOI10.1080/10485252.2022.2078822OpenAlexW4281727121MaRDI QIDQ5051330

Maria Lucia Parrella, S. Milito, Francesco Giordano

Publication date: 23 November 2022

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2022.2078822

zbMATH Keywords

nonparametric regressionvariable screeninglocal polynomial estimatorstructure discoveryultra high dimension

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05)

Cites Work

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• Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood
• Marginal empirical likelihood and sure independence feature screening
• Tight conditions for consistency of variable selection in the context of high dimensionality
• Partially linear structure identification in generalized additive models with NP-dimensionality
• Fused mean-variance filter for feature screening
• Optimal global rates of convergence for nonparametric regression
• GRID: a variable selection and structure discovery method for high dimensional nonparametric regression
• Rodeo: Sparse, greedy nonparametric regression
• The fused Kolmogorov filter: a nonparametric model-free screening method
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models
• MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Ranking-Based Variable Selection for high-dimensional data
• Variable Selection Using Adaptive Nonlinear Interaction Structures in High Dimensions
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis