Bootstrap and cross-validation estimates of the prediction error for linear regression models

DOI10.1214/AOS/1176346800zbMath0557.62039OpenAlexW1974133324MaRDI QIDQ761734

Bernd Droge, Olaf Bunke

Publication date: 1984

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176346800

zbMATH Keywords

model selectioncross-validationbias corrected bootstrap estimatorestimators of the prediction errornormally distributed observations

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (10)

Simulation experiments with CWA, a new stable regression algorithm, and comparisons with two other stable regression algorithms ⋮ Model selection in linear regression using paired bootstrap ⋮ Model choice for prediction in generalized linear models ⋮ On finite-sample properties of adaptive least squares regression estimates ⋮ A note on estimating the msep in nonlinear regression ⋮ Asymptotic optimality of full cross-validation for selecting linear regression models ⋮ Minimax Linear and Quadratic Estimators in Semiparametric Multivariate Regression Models ⋮ Regression and Contrast Estimates Based on Adaptive Regressograms Depending on Qualitative Explanatory Variables ⋮ A stepwise procedure for the selection of nonlinear regression models ⋮ A Modified Akaike Criterion for Model Choice in Generalized Linear Models

Uses Software

• alr3

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