function [n_min] = bictest(d)
% N_MIN = BICTEST(D)
% 
%   Creates a random training set x_1,...,x_200 of dimension D, and
%   reports the first N such that for all n>N the BIC selects for the
%   training set x_1,...,x_n  the correct model (with diag. covariance)
% the values of BIC scores are mising and need to be filled in


N = 200;
X = randn(N,d);

delta_bic = [];

for t=d:N,
  I = (1:t)';

  C1 = cov(X(I,:),1); 
  C0 = diag(diag(C1)); 
  
  % here you should insert calculation of BIC score for the
  % Gassian models with diagonal covariance (bic_0) and full covariance 
  % (bic_1)
  
  bic_0 =
  
  bic_1 = 
  
  
  delta_bic = [delta_bic;bic_1-bic_0];
end;

% plot(delta_bic);

n_min = max(find(delta_bic>=0))+1;