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Diagnostics for Autocorrelated Regression Models

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This paper discusses the local influence approach to the linear regression model with AR(1) errors. Diagnostics for the autocorrelation models and for the autocorrelation coefficient only are proposed and developed respectively, when simultaneous perturbations of the response vector are allowed. Furthermore, the direction of maximum curvature of local influence analysis is shown to be exactly the same as that in Tsai & Wu (1992) when only the autocorrelation coefficient is of special interest.
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Keywords: Autocorrelation; direction of maximum curvature; observed information matrix

Document Type: Research Article

Affiliations: 1: Kangnung National University, 2: La Trobe University

Publication date: March 1, 1998

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