%---------------------------------------------------------------------
%function [h, outlier, outlier_index] = experiment_least_squares(A, b)
%
% Matlab function to compute a least squares fit for more general
% data than the hill-height problem in experiment_least_squares1.m
%
%-----------
% On entry, 
%-----------
%   A is a m x n matrix with entries corresponding to the linear model
%   b is a n x 1 vector with the observed 
%
%------------
% On return, 
%------------
% h = best fit parameters
% outlier = observation value that is worst fit
% outlier_index = index of observation value that is worst fit
%  
%    Started  : Sun 8 Feb 2009
%    Modified : Wed 11 Feb 2009
%
%---------------------------------------------------------------------
function [h, outlier, outlier_index] = experiment_least_squares(A, b)

    h = A\b;
    residual = b - A*h;
    [outlier, outlier_index] = max(abs(residual));
    
return