JTank.cc File Reference

Test application for estimate of maximam number from limited sampling. More...

#include <string>
#include <iostream>
#include <iomanip>
#include <vector>
#include "TRandom3.h"
#include "JTools/JStats.hh"
#include "JMath/JMathSupportkit.hh"
#include "Jeep/JParser.hh"

Go to the source code of this file.

Functions
int	main (int argc, char **argv)

Detailed Description

Test application for estimate of maximam number from limited sampling.

This estimate is known as the German tank problem.

Author

mdejong

Definition in file JTank.cc.

Function Documentation

main()

int main	(	int	argc,
		char **	argv )

Definition at line 21 of file JTank.cc.

{
  using namespace std;
  using namespace JPP;
 
  size_t    N;
  size_t    k;
  size_t    start;
  size_t    M;
  Int_t     seed;
  int       debug;
 
  try { 
 
    JParser<> zap;
 
    zap['N'] = make_field(N);
    zap['k'] = make_field(k);
    zap['s'] = make_field(start)          = 1;
    zap['M'] = make_field(M)              = 1;
    zap['S'] = make_field(seed)           = 0;
    zap['d'] = make_field(debug)          = 3;
    
    zap(argc, argv);
  }
  catch(const exception& error) {
    FATAL(error.what() << endl);
  }
 
 
  gRandom->SetSeed(seed);
 
 
  /*
  // https://en.wikipedia.org/wiki/German_tank_problem
  cout << getMinimumVarianceUnbiasedEstimator(60, 4) << endl;
  cout << getBayesianMedian(60, 4) << endl;
  cout << getBayesianMean(60, 4) << endl;
  */
 
  vector<size_t> buffer;
 
  for (size_t i = 0; i != N; ++i) {
    buffer.push_back(start + i);                 // serial numbers
  }
 
  JStats Q[] = {
    JStats("frequentist"),
    JStats("Bayesian median"),
    JStats("Bayesian mean")
  };
 
  for (size_t counter = 0; counter != M; ++counter) {
 
    size_t m = 0;
 
    for (size_t i = 0; i != k; ++i) {
 
      const size_t l = gRandom->Integer(N - i);  // remaining serial numbers
 
      if (buffer[l] > m) {
        m = buffer[l];
      }
 
      swap(buffer[l], buffer[N - i - 1]);        // remove observation
    }
 
    Q[0].put(getMinimumVarianceUnbiasedEstimator(m, k, start));
    Q[1].put(getBayesianMedian(m, k, start));
    Q[2].put(getBayesianMean(m, k, start));
  }
 
  if (debug >= debug_t) {
 
    for (size_t i = 0; i != sizeof(Q)/sizeof(Q[0]); ++i) {
 
      cout << setw(24) << left << Q[i].getTitle() << right << FIXED(7,3) << Q[i].getMean();
 
      if (Q[i].getCount() > 1) {
        cout << ' ' << FIXED(7,3) << Q[i].getSTDev();
      }
 
      cout << endl;
    }
  }
}