A linear regression model with persistent level shifts: an alternative to infill asymptotics

DOI10.1016/J.SPL.2014.08.018zbMath1307.62215OpenAlexW2067493897MaRDI QIDQ464480

Jonathan Woody, Robert B. Lund

Publication date: 27 October 2014

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2014.08.018

zbMATH Keywords

changepointsasymptotic normalitylinear modelinfill asymptoticsbreakpoints

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Non-Markovian processes: hypothesis testing (62M07)

Related Items (3)

Improved estimation in tensor regression with multiple change-points ⋮ Time series regression with persistent level shifts ⋮ Inference problem in generalized fractional Ornstein-Uhlenbeck processes with change-point

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimation of multiple-regime regressions with least absolutes deviation
• Structural breaks in time series
• Inference for single and multiple change-points in time series
• Asymptotic Statistics
• Simple linear regression with multiple level shifts

This page was built for publication: A linear regression model with persistent level shifts: an alternative to infill asymptotics