Location of Outliers in Multiple Regression Using Resampled Values.

Within the regression context, this method begins with the set of exactly fitted coefficients determined from each "p"-dimensional subset of the sample. Outlying points in this "p"-dimensional coefficient space correspond to outliers in the original "n"-dimensional data space. Resampled values are used to detect points through a proposed detection rule that avoids masking and swamping and allows multiple outliers to be identified. Citation Copyright 1992 by Kluwer Academic Publishers.