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Trimming influential observations for improved single-index model estimated sufficient summary plots

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  • Prendergast, Luke A.

Abstract

The detection and subsequent treatment of influential observations have been well covered with respect to ordinary least squares (OLS) under an assumed multiple linear regression (MLR) model using measures such as Cook's Distance. However, OLS can be shown to be a useful method under a much wider variety of models. The purpose of this paper is twofold. Firstly we introduce a new diagnostic, similar to Cook's Distance, that is useful for detecting influential observations under an assumed single-index model. Secondly we show, via simulation, how trimming observations according to such diagnostics can greatly benefit the analysis even when no gross outliers are evident.

Suggested Citation

  • Prendergast, Luke A., 2008. "Trimming influential observations for improved single-index model estimated sufficient summary plots," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5319-5327, August.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:12:p:5319-5327
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    References listed on IDEAS

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    1. Luke A. Prendergast, 2007. "Implications of influence function analysis for sliced inverse regression and sliced average variance estimation," Biometrika, Biometrika Trust, vol. 94(3), pages 585-601.
    2. L. A. Prendergast, 2005. "Influence Functions for Sliced Inverse Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 385-404, September.
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    Cited by:

    1. Luke A. Prendergast & Simon J. Sheather, 2013. "On Sensitivity of Inverse Response Plot Estimation and the Benefits of a Robust Estimation Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 219-237, June.

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