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Influential Observations in Linear Regression
R. Dennis Cook
Journal of the American Statistical Association
Vol. 74, No. 365 (Mar., 1979), pp. 169-174
Stable URL: http://www.jstor.org/stable/2286747
Page Count: 6
You can always find the topics here!Topics: Datasets, Statistical discrepancies, Outliers, Correlations, Linear regression, Least squares, Statistical estimation, Ellipsoids, Point estimators, Statistics
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Characteristics of observations which cause them to be influential in a least squares analysis are investigated and related to residual variances, residual correlations, and the convex hull of the observed values of the independent variables. It is shown how deleting an observation can substantially alter an analysis by changing the partial F-tests, the studentized residuals, the residual variances, the convex hull of the independent variables, and the estimated parameter vector. Outliers are discussed briefly, and an example is presented.
Journal of the American Statistical Association © 1979 American Statistical Association