Six stage Identification and Assessment of Outliers and Influential Points in  Regression Models

Shaik Hussan Saheb, B Sarojamma

Six stage Identification and Assessment of Outliers and Influential Points in Regression Models

Authors

Shaik Hussan Saheb, B Sarojamma

Keywords:

Regression diagnostics; outliers; influential observations; leverage; hat matrix; Cook's distance; masking and swamping; robust regression.

Abstract

In regression analysis, a few unusual observations can change the fitted model. Suchobservations are of three kinds: outliers, which have a response far from the fitted line; highleverage points, which are far from the other observations in the predictor space; and influential points, which change the estimated coefficients

References

1)Andrews, D. F. and Pregibon, D. (1978). Finding the outliers that matter. Journal of the Royal Statistical Society, Series B, 40(1), 85–93.

2)Anscombe, F. J. and Tukey, J. W. (1963). The examination and analysis of residuals. Technometrics, 5(2), 141–160.

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Published

2026-06-20

How to Cite

Shaik Hussan Saheb, B Sarojamma. (2026). Six stage Identification and Assessment of Outliers and Influential Points in Regression Models. Journal of Computational Analysis and Applications (JoCAAA), 35(6), 270–288. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5839