Example 1

  Uses MtxExpr, Math387, Statistics, StatRandom;
  procedure Example;
  var vec1: Vector;
    resA, resB : TSample;
    CIA,CIB: TTwoElmReal;
  begin
    // first, generate 1000 randomly beta distributed
    // numbers with parameters a=3 and b =2
    vec1.Size(1000);
    RandomBeta(3,2,vec1);
    // Now extract the a,b and their 95% confidence intervals.
    //Use at max 300 iterations and tolerance 0.001
    BetaFit(vec1,resA,resB,CIA,CIB,300,1e-3);
  end;

  #include "MtxVecCpp.h"
  #include "Statistics.hpp"
  #include "StatRandom.hpp"
  void __fastcall Example()
  {
    Vector vec1;
    vec1->Size(1000,false);
    // first, generate 1000 randomly beta distributed
    // numbers with parameters a=3 and b =2
    RandomBeta(3,2,vec1);
    double esta,estb;
    double cia[2];
    double cib[2];
    // Now extract the a,b and their 95% confidence intervals.
    //Use at max 300 iterations and tolerance 0.001
    BetaFit(vec1,esta,estb,cia,cib,300,1.0E-3,0.05);
  }

  using Dew.Math;
  using Dew.Stats;
  using Dew.Stats.Units;
  namespace Dew.Examples;
  {
    private void Example()
    {
      Vector v = new Vector(1000,false);
      // first, generate 1000 randomly beta distributed
      // numbers with parameters a=3 and b =2
      StatRandom.RandomBeta(3.0, 2.0, v);
      double esta,estb;
      double[2] cia,cib;
      // Now extract the a,b and their 95% confidence intervals.
      //Use at max 300 iterations and tolerance 0.001
      Statistics.BetaFit(v,out esta, out estb, out cia, out cib, 300, 1.0e-3, 0.05);