Structural Change Monitoring for Random Coefficient Autoregressive Time Series

DOI10.1080/03610918.2013.800205zbMath1325.62169OpenAlexW2074980994MaRDI QIDQ5259144

Peiyan Qi, Zheng Tian, Fuxiao Li

Publication date: 24 June 2015

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.800205

zbMATH Keywords

boundary functionchange point monitoringrandom coefficient autoregressive time series of order \(p\)

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

Maximum likelihood estimation of the change point in stationary state of auto regressive moving average (ARMA) models, using SVD-based smoothing ⋮ Random autoregressive models: A structured overview ⋮ Changepoint Detection in Heteroscedastic Random Coefficient Autoregressive Models

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• The Cusum Test for Parameter Change in Time Series Models
• Monitoring Structural Change
• Estimation Mean Change-Point in ARCH Models with Heavy-Tailed Innovations

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