rjgaussian.m

gaussian algorithm for Bayesian Model Selection

function [y] = rjGaussian(mu,x);
% PURPOSE : Gaussian basis function.
% INPUTS  : - mu: The basis centre.
%           - x:  The evaluation point in the domain.
% OUTPUTS : - y: The value of the Gaussian at x.
% AUTHOR  : Nando de Freitas - Thanks for the acknowledgement :-)
% DATE    : 21-01-99

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)=exp(-(15*15)*z.^(2));        % Gaussian
%  y(j,1)=exp(-(0.5)*inv(.00001)*z.^(2));        % Gaussian.
end;