Residual information criterion for single-index model selections

DOI10.1080/10485250310001624800zbMath1049.62077OpenAlexW2076394127MaRDI QIDQ4819559

Prasad A. Naik, Chih-Ling Tsai

Publication date: 27 September 2004

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

Full work available at URL: https://doi.org/10.1080/10485250310001624800

zbMATH Keywords

local polynomial regressionsliced inverse regressionresidual likelihoodvariable and smoothing estimator selections

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Linear inference, regression (62J99)

Related Items (4)

Variable selection for single-index varying-coefficients models with applications to synergistic \(\mathrm{G} \times \mathrm{E}\) interactions ⋮ Estimation of single index model with missing response at random ⋮ Weighted estimation of single index models with right censored responses ⋮ Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Slicing regression: A link-free regression method
• Estimating the dimension of a model
• Direct estimation of the index coefficient in a single-index model
• Smoothing methods in statistics
• Single-index model selections
• Regression and time series model selection in small samples
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Generalized Partially Linear Single-Index Models
• Model Selection and Multimodel Inference
• Regression Model Selection—A Residual Likelihood Approach
• Semiparametric Estimation of Index Coefficients
• Informative Drop-Out in Longitudinal Data Analysis

This page was built for publication: Residual information criterion for single-index model selections