Regression by Integration applied to Angström-Prescott-type Relations
Abstract
We present a novel approach for the determination of the relationship between two random variables, which we call Regression by Integration. The resulting curve is a least absolute error estimate. Compared to other regression methods, it has the advantage that, instead of a sample of simultaneously taken pairs of the two random variables, only a separate sample of each of the random variables is required. We demonstrate the practicability of the method on Ångström-Prescott-type relations and compare the results with those obtained by least square error fits.