%Here are the initial values for parameters used in the programme.

    %THE FOLLOWING ARE FOR SIMULATING THE NUMBER OF COMPONENTS FAILING EACH
    %MONTH. THESE SIMULATED VALUES WILL BE USED TO TEST THE MODEL.
    n=1000;     %number of components produced each month
    m=36;       %number of months that components are produced for
    m2=12;      %number of months observed after production finishes
    p = [.09 .01 .05]; %values for the parameters describing the failure rate
    n_sim =10;     %number of simulated values for no. components failing each month given the paras "p"
    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
    
    %THE FOLLOWING ARE USED WHEN SAMPLING FROM THE PRIOR AND POSTERIOR
    %DISTRBTIONS.
    KK=200000;    %number of values simulated from prior
    MM=20000;     %number of values sampled from posterior
    prior_l = 10;   %prior_l is the maximum initial failure rate = lambda_1 + lambda_2
    prior_x_al = 1; %expected value of the prior distribution for alpha.
    prior_var_al = 2;   %variance of the prior distribution for alpha.
    
    %prior for alpha is a gamma(a,b) - a=shape, b=scale. Expected value =
    %ab = prior_x_al, var = ab^2 = prior_var_al 
    %=> 
    %a = (prior_x_al)^2 / prior_var_al
    %b = prior_var_al/prior_x_al
    c=30;    %This is the number of cross validations that will happen. It will be from c:I. I must be between 2 and I
    no_pred=4;    %this is TO DO WITH NNUMBER OF PREDICTIONs
    I=13;       %number of observations available is I-1 since I=1 correspond to number that failed in month 0 -not defined
    %if real data was available, it would be put in here. Otherwise, I
    %simulated values for the number of component failing in month 1 to I
    %will be used.