where N is the total number of theoretical and experimental values, x is the scaled property, y is the reference data point, index 1 ≤ i ≤ N enumerates the data points, and σ is the initially unknown uncertainty of all data points. In the case of absolute scale factor fitting, x i = ν The function Φ(s) can be interpreted through the maximal likelihood principle as the negative logarithm of the probability p(s) of the solution s, namely Φ(s) = ln(N ) -ln(p(s)) , where N is the normalization constant.