Abstract
In many cases of multiple regression in an undefined system, some independent variables may not be orthogonal to each other. In such cases, the systems either are not solvable or induce incorrect results which could vary with the data used. Such problems are often overcome by using the Ridge regression method. This article proposes an alternative way of getting an exact least square estimator by using an iterative method. We prove the solvability of the proposed algorithm and demonstrate that our method outperforms traditional approaches.