var vec1: Vector;
resMu, resSigma : double;
CIMu,CISigma: TTwoElmReal;
begin
    // first, generate 1000 normaly distributed
    // numbers with Mu a=0.0 and Sigma =1.0
    vec1.Size(1000);
    RandomNormal(0.0,1.0,vec1);
  // Now extract the Mu,Sigma and their 95% confidence intervals.
    // Use at max 400 iterations and tolerance 0.0001
  NormalFit(vec1,resMu,resSigma,CIMu,CISigma);
end;

#include "StatRandom.hpp"
#include "MtxExpr.hpp"
#include "Statistics.hpp"
void __fastcall Example();
{
  sVector vec1;
    // first, generate 1000 normaly distributed
    // numbers with Mu a=0.0 and Sigma =1.0
    vec1.Size(1000,false);
    RandomNormal(0.0,1.0,vec1);
  double resMu, resSigma;
  TTwoElmReal CIMu, CISigma;
  // Now extract the Mu,Sigma and their 95% confidence intervals.
    // Use at max 400 iterations and tolerance 0.0001
  NormalFit(vec1,resMu,resSigma,CIMu,CISigma,0.05);
}