Influential observations in linear regression
RD Cook - Journal of the American Statistical Association, 1979 - Taylor & Francis
Journal of the American Statistical Association, 1979•Taylor & Francis
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 …
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 …
Abstract
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.
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