% dice(n,r) alternates between fair and loaded dice, runs r simulations of length n each, and estimates the hidden sequence

function [void] = dice(n,r)

HS = 'FL';                     % names of the hidden states
OS = '123456';                 % names of the observed states
A  = [[.95 .05]; [.1 .9]];     % transition probabilities among hidden states
mu = [0.5 0.5];                % initial distribution of hidden states
E  = [[1/6 1/6 1/6 1/6 1/6 1/6]; [1/10 1/10 1/10 1/10 1/10 1/2]];
                               % emission probabilities

Pi = hmmsim(mu,A,n);           % simulate hidden Markov model
fprintf('Die     ');
show(Pi,HS);                   % display the hidden states

X = [];
for i=1:r,
  x = obssim(Pi,E);            % simulate observed states
  fprintf('Roll    ');
  show(x,OS);                  % display the observed states
  X = [X; x];                  % add these states as another row of X
end

PiStar = viterbi(mu,A,E,X);    % find most likely hidden sequence
fprintf('Viterbi ');
show(PiStar,HS);               % display it
fprintf('Errors  ');
show((PiStar==Pi)+1,'* ');     % mark errors