% load the diabetes data from the paper
X=dlmread('diabX.tab',' ',1,1);
y=dlmread('diaby.tab',' ',1,1);
fit_from_R=dlmread('diabfit.tab',' ',1,1); % also load the answer from the R code that accompanied the paper, for comparison

% normalize the covariates
[n,m]=size(X);
stdX=std(X,0,1);
X=X./repmat(stdX,n,1);
% normalize the response
y=y-mean(y); 
stdy=std(y);
y=y./stdy;

% get the answer from LAR
betas=lars(X,y);

% correct for normalization
nsteps=size(betas,2);
betas=betas.*repmat((stdy./stdX)',1,nsteps);

% look at the betas as they change and compare to fit from R
figure(1);
s=sum(abs(betas),1);
plot(s, betas'); 
xlabel('|\beta|'); ylabel('\beta_i'); title('coefficients(\beta''s) as they change');

fprintf('discrepancy between matlab and R fit = %g\n',norm(betas-fit_from_R(2:end,:)'));