Function stuck in a 'while loop'

I have a function to find the coefficients of a polynomial correlation between 3 data sets. The code has 6 simultaneous equations in matrix form to calculate the 6 coefficients (using least squares regression) and then uses a while loop to reduce the rmse (root mean squared error) to a minimum while updates the coefficients therefore validating the results.

The code is this:

 function F = matrices;  %Name to call the function from the command window

   X = [259, 266, 298, 322, 310, 339, 398];               %These need to be 
   Y = [64.6, 65.48, 65.28, 65.66, 65.86, 65.83, 65.37];  %adjusted according 
   Z = [-42, -35.8, -24.8, -16, -19.7, -9.5 -1];          %to the correlation. 

 X2  =  X  .* X;          %Used to simplify the matrix notation within 
 X3  =  X2 .* X;          %the while loop.
 Y2  =  Y  .* Y;
 Y3  =  Y2 .* Y;
 Z2  =  Z  .* Z;

    n         =   7;     %Number of data points.
    RMSE      =   1;     %Initial RMSE guess to use in equation on line 28

    A  =  1;             %Initial coefficient guesses, need to make sure 
    B  =  1;             %that the initial guesses don't have an effect on 
    C  =  1;             %the final answer.
    D  =  1;
    E  =  1;
    F  =  1;

    while RMSE>0.01 %While loop to keep recalculating the root mean 
                         %squared error if it is larger than the tolerance, 
                         %or minimum value set previously.

        m     = A.*X2  +  B.*X  +  C.*Y2  +  D.*Y  +  E.*Y.*X  +  F;
                             %The assumed form of the correlation equation. 
        RMSE  = ((sum(((m-Z).^2).*(1:7)))/7).^(0.5);
                             %RMSE calculation used to create most valid
                             %correlation. 

        %Enter the least squares code to update the variables, A B C D E F?

       q = [X3 .* X,   X3,       X2 .* Y2,  X2 .* Y,  X3 .* Y,   X2;
            X3,        X2,       X .* Y2,   Y.* X,    X2 .* Y,   X;
            X2 .* Y2,  X .* Y2,  Y3 .* Y,   Y3,       Y3 .* X,   Y2;
            X2 .* Y,   X .* Y,   Y3,        Y2,       X .* Y2,   Y;
            X3 .* Y,   X2 .* Y,  Y3 .* X,   X .* Y2,  X2 .* Y2,  Y .* X;
            X2,        X,        Y2,        Y,        Y .* X,    ones(1,length(X))];

        p = [X2.*Z, X.*Z, Y2.*Z, Y.*Z, Y.*Z, Z2];

        x=q/p;                

        x(1) = 'A'    
        x(2) = 'B'      %Necessary to update the coefficient values, 
        x(3) = 'C'      %without these commands the x matrix is returned  
        x(4) = 'D'      %exactly the same every time.
        x(5) = 'E'
        x(6) = 'F'

    end     %To end the while loop.

    A       %To recall each of the calculated coefficients and the final  
    B       %root mean squared error value showing the validity of the 
    C       %corelation.  
    D
    E
    F

    RMSE    %A value closer to 0 is better.

 end

This will create the 6 coefficients and keep updating them without getting to a point where the rmse is low enough. Any ideas or suggestions would be appreciated.

Thanks

P.S. my company's version of matlab doesnt have a curve fitting toolbox which would solve all my problems, hence the long winded approach!