/*
**	Monte Carlo Program for sample mean
*/

@ Data generation under Classical Linear Regression Assumptions @

seed   = 1;
tt     = 100; @ # of observations @
iter   = 1000; @ # of sets of different data @

storem  = zeros(iter,1) ;
stores  = zeros(iter,1) ; 

i = 1; do while i <= iter;

@ compute sample mean for each sample @

x = 3*rndns(tt,1,seed);
m = meanc(x);
storem[i,1]  = m;
stores[i,1]  = x[1,1];

i = i + 1; endo;

@ Reporting Monte Carlo results @

output file = mmonte.out reset;

format /rd 12,3;

"Monte Carlo results";
"-----------";
"Mean of x bar     ="  meanc(storem);
"mean of x rou     ="  meanc(stores);

library pgraph;
graphset;

v = seqa(-10, .2, 100);
@ {a1,a2,a3}=hist(storem,v); @
{b1,b2,b3}=hist(stores,v); 

output off ;