An \(R\)-square coefficient based on final prediction error

DOI10.1016/J.STAMET.2006.11.004zbMath1248.62121OpenAlexW2085600065MaRDI QIDQ713779

Nicoleta Francisca Goşoniu, Valentin Rousson

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2006.11.004

zbMATH Keywords

multiple linear regressionAICoverfittingFPEexplained variancefitted model

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items (2)

Approximation algorithm of maximizing non-monotone non-submodular functions under knapsack constraint ⋮ On efficiency properties of an \(R\)-square coefficient based on final prediction error

Uses Software

• alr3

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotic properties of criteria for selection of variables in multiple regression
• Estimating the dimension of a model
• Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation
• Regression and time series model selection in small samples
• Selection of the order of an autoregressive model by Akaike's information criterion
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Model Selection and Multimodel Inference
• The Relationship between Variable Selection and Data Agumentation and a Method for Prediction
• Some Comments on C P

This page was built for publication: An \(R\)-square coefficient based on final prediction error