The Glory of Suboptimal Factor Rotation: Why Local Minima in Analytic Optimization of Simple Structure are More Blessing Than Curse

Factor rotation algorithms do not generally find the best solutions of which they are capable, but when enriched with the capacity to conduct repeated searches from random starting positions, a rotation algorithm's propensity to converge to optima that are merely local can be fashioned into a seine for catching interpretively provocative rotations of the input factors.

Abstract

Yet another facet of factor indeterminacy rears its ugly head: Factor rotation algorithms do not generally find the best solutions of which they are capable. But when enriched with the capacity to conduct repeated searches from random starting positions, a rotation algorithm's propensity to converge to optima that are merely local can be fashioned into a seine for catching interpretively provocative rotations of the input factors that might otherwise elude discovery.