wolffd@0: function [converged, decrease] = em_converged(loglik, previous_loglik, threshold, check_increased)
wolffd@0: % EM_CONVERGED Has EM converged?
wolffd@0: % [converged, decrease] = em_converged(loglik, previous_loglik, threshold)
wolffd@0: %
wolffd@0: % We have converged if the slope of the log-likelihood function falls below 'threshold', 
wolffd@0: % i.e., |f(t) - f(t-1)| / avg < threshold,
wolffd@0: % where avg = (|f(t)| + |f(t-1)|)/2 and f(t) is log lik at iteration t.
wolffd@0: % 'threshold' defaults to 1e-4.
wolffd@0: %
wolffd@0: % This stopping criterion is from Numerical Recipes in C p423
wolffd@0: %
wolffd@0: % If we are doing MAP estimation (using priors), the likelihood can decrase,
wolffd@0: % even though the mode of the posterior is increasing.
wolffd@0: 
wolffd@0: if nargin < 3, threshold = 1e-4; end
wolffd@0: if nargin < 4, check_increased = 1; end
wolffd@0: 
wolffd@0: converged = 0;
wolffd@0: decrease = 0;
wolffd@0: 
wolffd@0: if check_increased
wolffd@0:   if loglik - previous_loglik < -1e-3 % allow for a little imprecision
wolffd@0:     fprintf(1, '******likelihood decreased from %6.4f to %6.4f!\n', previous_loglik, loglik);
wolffd@0:     decrease = 1;
wolffd@0: converged = 0;
wolffd@0: return;
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: delta_loglik = abs(loglik - previous_loglik);
wolffd@0: avg_loglik = (abs(loglik) + abs(previous_loglik) + eps)/2;
wolffd@0: if (delta_loglik / avg_loglik) < threshold, converged = 1; end