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

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