A Generalized View on Continuum Regression

. We generalize the relationship between continuum regression (Stone & Brooks, 1990) and ridge regression, by showing that any optimization principle will yield a regressor proportional to a ridge regressor, provided only that the principle implies maximizing a function of the regressor’s sample correlation coefficient and its sample variance. This relationship shows that continuum regression as defined via ridge regression (“least squares ridge regression”) is a more generally valid methodology than previously realized, and also opens up for alternative choices of its second and subsequent factors.