Multilinear regression is to fit 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 powers 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 points
sigY[] will be the standard deviations of the observed data.
par will be the number of model parameters
a[] holds the parameters of the model
sigA[] will hold the uncertainties associated with the model parameters.
mert is the value of the Chi-square merit function.
f() is the user function.
