Maximal-entropy driven determination of weights in least-square approximation

Abstract

We exploit the idea to use the maximal-entropy method, successfully tested in information theory and statistical thermodynamics, to determine approximating function's coefficients and squared errors' weights simultaneously as output of one single problem in least-square approximation. We provide evidence of the method's capabilities and performance through its application to representative test cases by working with polynomials as a first step. We conclude by formulating suggestions for future work to improve the version of the method we present in this paper.

15 pages, 1 table, 10 figures. Accepted in Mathematical Methods in the Applied Sciences. Changes: fixed typo in Eq. (27)

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• Maximal-entropy driven determination of weights in least-square approximation

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