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Leverage and Influence in Autocorrelated Regression Models

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  • Martin L. Puterman

Abstract

This paper examines the effect of individual observations in regression models with AR(1) errors through use of the ‘hat matrix’ and other influential observation diagnostics. It shows both analytically and through examples that in many practical settings the first transformed observation can have a relatively large hat matrix diagonal component and a large influence on parameter estimates. This provides additional evidence for retaining the first observation when performing estimation in this setting.

Suggested Citation

  • Martin L. Puterman, 1988. "Leverage and Influence in Autocorrelated Regression Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(1), pages 76-86, March.
    • Handle: RePEc:bla:jorssc:v:37:y:1988:i:1:p:76-86
    DOI: 10.2307/2347495
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    Cited by:

    1. Roland Jeske & Seuck Song, 2003. "Relative efficiency of OLSE and COTE for seasonal autoregressive disturbances," Statistical Papers, Springer, vol. 44(3), pages 421-432, July.

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