Modified Lagrange Interpolating Polynomial (MLIP) Method: A Straightforward Procedure to Improve Function Approximation - Uriel A. Filobello-Nino; Hector Vazquez-Leal; Mario A. Sandoval-Hernandez; Jose A. Dominguez-Chavez; Alejandro Salinas-Castro; Victor M. Jimenez-Fernandez; Jesus Huerta-Chua; Claudio Hoyos-Reyes; Norberto Carrillo-Ramon; Javier Flores-Mendez (AppliedMath, 2025)
This work presents the modified Lagrange interpolating polynomial (MLIP) method, which aims to provide a straightforward procedure for deriving accurate analytical approximations of a given function. The method introduces an exponential function with several parameters which multiplies one of the terms of a Lagrange interpolating polynomial. These parameters will adjust their values to ensure that the proposed approximation passes through several points of the target function, while also adopting the correct values of its derivative at several points, showing versatility. Lagrange interpolating polynomials (LIPs) present the problem of introducing oscillatory terms and are, therefore, expected to provide poor approximations for the derivative of a given function. We will see that one of the relevant contributions of MLIPs is that their approximations contain fewer oscillatory terms compared to those obtained by LIPs when both approximations pass through the same points of the function to be represented; consequently, better MLIP approximations are expected. A comparison of the results obtained by MLIPs with those from other methods reported in the literature highlights the method’s potential as a useful tool for obtaining accurate analytical approximations when interpolating a set of points. It is expected that this work contributes to break the paradigm that an effective modification of a known method has to be lengthy and complex.