function [y] = rjGaussian(mu,x);if nargin < 2, error('Not enough input arguments.'); end[N,d] = size(x);      % N = number of data, d = dimension of x.y=zeros(N,1);for j=1:N,  z=norm(x(j,:)-mu(1,:));          % Euclidean distance.  y(j,1)= z.^(3);                 % Cubic spline.end;