*** Find distribution of largest and smallest eigenvalues of 
sample covariance matrix ***; 

PROC IML; 
  V = {10 5, 5 12}; 
  R = root(V); print R V; 
  E = normal(123)//normal(123); print E; 
  Do rep = 1 to 10; 
   ESTV={0 0, 0 0};  
   Do i = 1 to 100;  ** sample size 100; 
   E = normal(123)//normal(123);
   W = R*E;  ESTV=ESTV + W*W`; 
   end; ESTV=ESTV/100; 
 EVAL = (eigval(ESTV))`; print EVAL; 
 end; 

 ** Challenge:  Change reps to 1000, output to dataset then 
 plot largest vs. smallest and make histograms of both;