Abstract
In multiple regression it is shown that parameter estimates based on minimum
residual sum of squares have a high probability of being unsatisfactory, if not incorrect,
if the prediction vectors are not orthogonal. Proposed is an estimation procedure
based on adding small positive quantities to the diagonal of X'X. Introduced is the
ridge trace, a method for showing in two dimensions the effects of nonorthogonality.
It is then shown how to augment X'X to obtain biased estimates with smaller mean
square error.
