Comparing ARMA Processes with Roots of Modulus 1 and Polynomial Regression

DOI10.1080/03610926.2011.617482zbMath1319.62189OpenAlexW2050594980MaRDI QIDQ3167826

Delphine Blanke, Denis Bosq

Publication date: 29 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.617482

zbMATH Keywords

seasonalitypolynomial regressioninnovationARMAIMAreal and complex roots of modulus one

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)

Related Items (2)

Models Associated with Extended Exponential Smoothing ⋮ Bayesian prediction for stochastic processes: theory and applications

Uses Software

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Cites Work

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• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
• Time series: theory and methods.
• Automatic Lag Selection in Covariance Matrix Estimation
• Generalizations of the KPSS‐test for stationarity
• Inference and Prediction in Large Dimensions

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