On estimating the common point of intersection of curves

We propose an aparametric approximation technique to estimate the point of intersection of a pair of antagonistic curves, when it is assumed that the input information for both curves consists of several, possibly noisy candidate curves from different sources. The problem of determining an intersection point is inherent in the study of many equilibrium phenomena in the natural and behavioral sciences. Our technique is iterative and is based on an ad hoc line-to-point transformation and on common regression analysis. The article offers the rationale behind our approach, an analytical investigation of its applicability, and a thorough numerical study of the accuracy of the technique for one specific demand-and-supply case. Further applications, which extend from the model of two antagonistic curves, are also discussed.