A bootstrap procedure in linear regression with nonstationary errors

DOI10.2307/3315680zbMath0899.62056OpenAlexW2073016314MaRDI QIDQ4399504

Arthur B. Yeh

Publication date: 15 November 1998

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

Full work available at URL: https://doi.org/10.2307/3315680

zbMATH Keywords

consistencyalpha-mixingleast-squares estimatorblocking external bootstrapnonstationary sequence of errors

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric statistical resampling methods (62G09)

Related Items (4)

A WILD BOOTSTRAP FOR DEPENDENT DATA ⋮ Estimating the variance of a combined forecast: bootstrap-based approach ⋮ Block external bootstrap in partially linear models with nonstationary strong mixing error terms ⋮ Bootstrap Inference in Regressions with Estimated Factors and Serial Correlation

Cites Work

• Unnamed Item
• Bootstrapping regression models
• Efficiency and robustness in resampling
• The jackknife and the bootstrap for general stationary observations
• On Edgeworth expansion and moving block bootstrap for Studentized \(M\)-estimators in multiple linear regression models
• Bootstrapping robust regression
• The Little Bootstrap and Other Methods for Dimensionality Selection in Regression: X-Fixed Prediction Error

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