Globally stabilized 3L curve fitting

Abstract

Although some of the linear curve fitting techniques provide improvements over the classical least squares fit algorithm, most of them cannot globally stabilize majority of data sets, and are not robust enough to handle moderate levels of noise or missing data. In this paper, we apply ridge regression regularization to strengthen the stability and robustness of a linear fitting method, 3L fitting algorithm, while maintaining its Euclidean invariance.