On the efficiency of regression analysis with AR(p) errors

DOI10.1080/02664760600679775zbMath1147.62364OpenAlexW1997443318MaRDI QIDQ3532705

Teresa Alpuim, A. H. El-Shaarawi

Publication date: 28 October 2008

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

Full work available at URL: https://doi.org/10.1080/02664760600679775

zbMATH Keywords

trendseasonalitymaximum likelihoodleast squareslinear difference equationautoregressive stationary process

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (7)

Robust parameter estimation of regression model with AR(p) error terms ⋮ Empirical likelihood estimation for linear regression models with AR(p) error terms with numerical examples ⋮ Run length distribution for a modified EWMA scheme fitted with a stationary AR(p) model ⋮ Nonparametric tests in linear model with autoregressive errors ⋮ Conditional maximum Lq-likelihood estimation for regression model with autoregressive error terms ⋮ A comparison between the linear regression model with autocorrelated errors and the partial adjustment model ⋮ Parameter estimation of regression model with AR\((p)\) error terms based on skew distributions with EM algorithm

Cites Work

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• Estimating the autocorrelated error model with trended data
• Testing for trends in correlated data
• A Maximum Likelihood Procedure for Regression with Autocorrelated Errors
• Least squares estimation in the regression model with autoregressive-moving average errors
• A NOTE ON THE CONSISTENCY AND MAXIMA OF THE ROOTS OF LIKELIHOOD EQUATIONS
• On the Estimation of Regression Coefficients in the Case of an Autocorrelated Disturbance

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