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			104 lines
		
	
	
		
			3.6 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
		
		
			
		
	
	
			104 lines
		
	
	
		
			3.6 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
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								// inverse_gamma_distribution_example.cpp
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								// Copyright Paul A. Bristow 2010.
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								// Copyright Thomas Mang 2010.
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								// Use, modification and distribution are subject to the
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								// Boost Software License, Version 1.0.
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								// (See accompanying file LICENSE_1_0.txt
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								// or copy at http://www.boost.org/LICENSE_1_0.txt)
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								// Example 1 of using inverse gamma
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								#include <boost/math/distributions/inverse_gamma.hpp>
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								using boost::math::inverse_gamma_distribution;  //  inverse_gamma_distribution.
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								using boost::math::inverse_gamma;
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								#include <boost/math/special_functions/gamma.hpp>
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								using boost::math::tgamma; // Used for naive pdf as a comparison.
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								#include <boost/math/distributions/gamma.hpp>
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								using boost::math::inverse_gamma_distribution;
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								#include <iostream>
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								using std::cout;    using std::endl;
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								#include <iomanip>
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								using std::setprecision;
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								#include <cmath>
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								using std::sqrt;
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								int main()
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								{
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								  cout << "Example using Inverse Gamma distribution. " << endl;
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								  // TODO - awaiting a real example using Bayesian statistics.
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								#ifdef BOOST_NO_CXX11_NUMERIC_LIMITS
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								  int max_digits10 = 2 + (boost::math::policies::digits<double, boost::math::policies::policy<> >() * 30103UL) / 100000UL;
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								  cout << "BOOST_NO_CXX11_NUMERIC_LIMITS is defined" << endl;
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								#else
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								  int max_digits10 = std::numeric_limits<double>::max_digits10;
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								#endif
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								  cout << "Show all potentially significant decimal digits std::numeric_limits<double>::max_digits10 = "
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								    << max_digits10 << endl;
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								  cout.precision(max_digits10); //
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								  double shape = 1.;
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								  double scale = 1.;
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								  double x = 0.5;
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								  // Construction using default RealType double, and default shape and scale..
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								  inverse_gamma_distribution<> my_inverse_gamma(shape, scale); // (alpha, beta)
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								  cout << "my_inverse_gamma.shape() = " << my_inverse_gamma.shape()
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								    << ", scale = "<< my_inverse_gamma.scale() << endl;
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								  cout << "x = " << x << ", pdf = " << pdf(my_inverse_gamma, x)
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								    << ", cdf = " << cdf(my_inverse_gamma, x) << endl;
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								  // Construct using  typedef and default shape and scale parameters.
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								  inverse_gamma my_ig;
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								  inverse_gamma my_ig23(2, 3);
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								  cout << "my_inverse_gamma.shape() = " << my_ig23.shape()
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								    << ", scale = "<< my_ig23.scale() << endl;
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								  cout << "x = " << x << ", pdf = " << pdf(my_ig23, x)
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								    << ", cdf = " << cdf(my_ig23, x) << endl;
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								  // Example of providing an 'out of domain' or 'bad' parameter,
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								  // here a shape < 1, for which mean is not defined.
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								  // Try block is essential to catch the exception message.
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								  // (Uses the default policy which is to throw on all errors).
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								  try
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								  {
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								    inverse_gamma if051(0.5, 1);
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								    //inverse_gamma if051(0.5, 1);
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								    cout << "mean(if051) = " << mean(if051) << endl;
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								  }
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								  catch(const std::exception& e)
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								  { // Always useful to include try & catch blocks because default policies
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								    // are to throw exceptions on arguments that cause errors like underflow, overflow.
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								    // Lacking try & catch blocks, the program will abort without a message below,
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								    // which may give some helpful clues as to the cause of the exception.
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								    std::cout <<
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								      "\n""Message from thrown exception was:\n   " << e.what() << std::endl;
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								  }
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								  return 0;
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								}  // int main()
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								/*
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								Output is:
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								  Example using Inverse Gamma distribution.
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								  std::numeric_limits<double>::max_digits10 = 17
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								  my_inverse_gamma.shape() = 1, scale = 1
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								  x = 0.5, pdf = 0.54134113294645081, cdf = 0.1353352832366127
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								  my_inverse_gamma.shape() = 2, scale = 3
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								  x = 0.5, pdf = 0.17847015671997774, cdf = 0.017351265236664509
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								  Message from thrown exception was:
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								     Error in function boost::math::mean(const inverse_gamma_distribution<double>&): Shape parameter is 0.5, but for a defined mean it must be > 1
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								*/
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