% straight forward outline of running of scripts
d(1,:) = [.01 .005 1];
d(2,:) = [.01 .005 .1];
d(3,:) = [.9 .01 .01];
d(5,:) = [.9 .01 1];
d(10,:) = [.05 .005 .1];
%d(6,:) = [.05 .01  .5];
d(6,:) = [.3 .05 .1];
d(8,:) = [.9 .01 .05];
d(7,:) = [10 5 5];
d(9,:) = [.3 .05 .1];
for count=8:10
count
    
    display('outline')
    display('basic parameters')
basics_f
p(1:3)=d(count,:)
r= p(2) + p(1)*exp(-p(3).*(0:m+m2)); %r= failure rate
    rel = exp(-r); %reliabilty of a component 
    pf = 1-rel; %prob component fails before 1 month
    display('simulating fails per month')
fails_per_month_f
    display('sampling from the prior distribution')
    
    obs(1:I) = K(1,1:I); %this gives I observed #failures in months 1:I. Only one obs for each month. 
                     % note that the first obs is 0 since 0 fails in first
                     % month.    
sampling_f
    display('samping from the posterior using importance sampling')
post_sampling_f
    display('sort and display results')
sort_disp
    display('posterior predictive')
post_pred
    display('cross validation')
    
    
     for i=c:I
         i
        recreated(count,i) = cross_val(i,obs);
     end
     observations(count,:) = obs;
    hold off
    figure(count)
    plot(c:I,recreated(count,c:I),'dg')
    hold on

    plot(1:I,obs)
    hold on     
    plot(I+1,post_prediction(I+1),'dg')
    plot(I+1,K(1,I+1),'dr')
    hold off
end