Arguments:

A	vector of size npars; returns the coefficients
Covar	matrix of dimensions [npars, npars]; returns the covariances of the coefficients. If the covariances are not needed, one may call the function with Covar=NULL / nil.
AStatus	vector of size npars; decides which parameters are treated as free or as fixed
npars	total number of parameters
X, Y	vectors of size lenZ and htZ, respectively, spanning the x-y coordinate system of the matrix MZ
MZ, MInvVar	matrices of dimensions [htZ, lenZ], holding the input data and, in the weighted variant, the inverse of their variances
funcs	user-defined model function

 
Your model function may actually contain more parameters than you wish to treat as adjustable. This is why you have to provide the vector AStatus, which contains the necessary information about which parameters are to be held fixed at their input values (AStatus[i] = 0) and which are free (AStatus[i] = 1). Any fixed parameters must be initialized in A prior to calling MF_linfit. npars denotes the total number of parameters in A (not only the free parameters!).

You must provide a model function "funcs" which, for any pair of arguments x, y, must calculate the individual f_i(x, y) and store them in a vector BasFuncs of size npars. In C/C++, it has to be defined as
void MyFunc( fVector BasFuncs, float x, float y, unsigned nfuncs);
{
  BasFuncs[0] = f0( x, y );
  BasFuncs[1] = f1( x, y);
  . . .
}
and shall be passed to MF_linfit by calling
MF_linfit( A, AStatus, npars, X, Y, MZ, htZ, lenZ, MyFunc );
In Pascal/Delphi, the model function has to be defined as
procedure MyFunc( BasFuncs:fVector; x, y:Single; nfuncs:UInt );
begin
  VF_Pelement( BasFuncs, 0 )^ := f0( x, y );
  VF_Pelement( BasFuncs, 1 )^ := f1( x, y );
  . . .
end;
and shall be passed to MF_linfit by calling
MF_linfit( A, AStatus, npars, X, Y, MZ, htZ, lenZ, @MyFunc );
Note the address-of operator in front of "MyFunc.". In Turbo Pascal, the model function must be compiled with the Force-Far-Calls option {$F+}.

The functions f0( x, y ) etc. must not contain the parameters a_i.
In the weighted variant, MF_linfitwW, the matirx MInvVar has to contain the inverse of the variances of the individual X-Y-Z data points, and the matrix MCovar will be filled with the covariances of the parameters a_i on output: MCovar_i,j = covariance( a_i, a_j ).

Internally, MF_linfit employs a Singular Value Decomposition algorithm to obtain a solution even for (near-)singular linear systems. Thereby, coefficients a_i whose significance is lower than a threshold, Thresh, are set to 0 instead of infinity. The default threshold can be modified by calling VF_setLinfitNeglect. The current threshold can be retrieved by VF_getLinfitNeglect. As VF_setLinfitNeglect is not thread-safe, this function should not be used to set different thresholds for different calls to VF / MF_linfit etc. Rather than repeatedly changing the default value, use the "wEdit" variants of VF / MF_linfit, namely MF_linfitwEdit, MF_linfitwWwEdit etc.

In the rare case of failure, this function returns 1 (TRUE) and sets all A[i] = 0.