Multilinear regression fits a model represented by a linear combination of arbitrary functions of x to a set of observed data points.
The basis function Fj(x) most commonly will have the family of integer power, which the regression is based on.In the code: x[] and y[] will be the x and y coordinates of the observed data.n will be the number of observed data pointssigY[] will be the standard deviations of the observed data.par will be the number of model parametersa[] holds the parameters of the modelsigA[] will hold the uncertainties associated with the model parameters.mert is the value of the Chi-square merit function.f() is the user function.
