mirror of
				https://github.com/saitohirga/WSJT-X.git
				synced 2025-10-27 11:00:32 -04:00 
			
		
		
		
	
		
			
	
	
		
			170 lines
		
	
	
		
			6.9 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
		
		
			
		
	
	
			170 lines
		
	
	
		
			6.9 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
|  | // laplace_example.cpp
 | ||
|  | 
 | ||
|  | // Copyright Paul A. Bristow 2008, 2010.
 | ||
|  | 
 | ||
|  | // Use, modification and distribution are subject to the
 | ||
|  | // Boost Software License, Version 1.0.
 | ||
|  | // (See accompanying file LICENSE_1_0.txt
 | ||
|  | // or copy at http://www.boost.org/LICENSE_1_0.txt)
 | ||
|  | 
 | ||
|  | // Example of using laplace (& comparing with normal) distribution.
 | ||
|  | 
 | ||
|  | // Note that this file contains Quickbook mark-up as well as code
 | ||
|  | // and comments, don't change any of the special comment mark-ups!
 | ||
|  | 
 | ||
|  | //[laplace_example1
 | ||
|  | /*`
 | ||
|  | First we need some includes to access the laplace & normal distributions | ||
|  | (and some std output of course). | ||
|  | */ | ||
|  | 
 | ||
|  | #include <boost/math/distributions/laplace.hpp> // for laplace_distribution
 | ||
|  |   using boost::math::laplace; // typedef provides default type is double.
 | ||
|  | #include <boost/math/distributions/normal.hpp> // for normal_distribution
 | ||
|  |   using boost::math::normal; // typedef provides default type is double.
 | ||
|  | 
 | ||
|  | #include <iostream>
 | ||
|  |   using std::cout; using std::endl; using std::left; using std::showpoint; using std::noshowpoint; | ||
|  | #include <iomanip>
 | ||
|  |   using std::setw; using std::setprecision; | ||
|  | #include <limits>
 | ||
|  |   using std::numeric_limits; | ||
|  | 
 | ||
|  | int main() | ||
|  | { | ||
|  |   cout << "Example: Laplace distribution." << endl; | ||
|  | 
 | ||
|  |   try | ||
|  |   { | ||
|  |     { // Traditional tables and values.
 | ||
|  | /*`Let's start by printing some traditional tables.
 | ||
|  | */       | ||
|  |       double step = 1.; // in z 
 | ||
|  |       double range = 4; // min and max z = -range to +range.
 | ||
|  |       //int precision = 17; // traditional tables are only computed to much lower precision.
 | ||
|  |       int precision = 4; // traditional table at much lower precision.
 | ||
|  |       int width = 10; // for use with setw.
 | ||
|  | 
 | ||
|  |       // Construct standard laplace & normal distributions l & s
 | ||
|  |         normal s; // (default location or mean = zero, and scale or standard deviation = unity)
 | ||
|  |         cout << "Standard normal distribution, mean or location = "<< s.location() | ||
|  |           << ", standard deviation or scale = " << s.scale() << endl; | ||
|  |         laplace l; // (default mean = zero, and standard deviation = unity)
 | ||
|  |         cout << "Laplace normal distribution, location = "<< l.location() | ||
|  |           << ", scale = " << l.scale() << endl; | ||
|  | 
 | ||
|  | /*` First the probability distribution function (pdf).
 | ||
|  | */ | ||
|  |       cout << "Probability distribution function values" << endl; | ||
|  |       cout << " z  PDF  normal     laplace    (difference)" << endl; | ||
|  |       cout.precision(5); | ||
|  |       for (double z = -range; z < range + step; z += step) | ||
|  |       { | ||
|  |         cout << left << setprecision(3) << setw(6) << z << " "  | ||
|  |           << setprecision(precision) << setw(width) << pdf(s, z) << "  " | ||
|  |           << setprecision(precision) << setw(width) << pdf(l, z)<<  "  (" | ||
|  |           << setprecision(precision) << setw(width) << pdf(l, z) - pdf(s, z) // difference.
 | ||
|  |           << ")" << endl; | ||
|  |       } | ||
|  |       cout.precision(6); // default
 | ||
|  | /*`Notice how the laplace is less at z = 1 , but has 'fatter' tails at 2 and 3. 
 | ||
|  | 
 | ||
|  |    And the area under the normal curve from -[infin] up to z, | ||
|  |    the cumulative distribution function (cdf). | ||
|  | */ | ||
|  |       // For a standard distribution 
 | ||
|  |       cout << "Standard location = "<< s.location() | ||
|  |         << ", scale = " << s.scale() << endl; | ||
|  |       cout << "Integral (area under the curve) from - infinity up to z " << endl; | ||
|  |       cout << " z  CDF  normal     laplace    (difference)" << endl; | ||
|  |       for (double z = -range; z < range + step; z += step) | ||
|  |       { | ||
|  |         cout << left << setprecision(3) << setw(6) << z << " "  | ||
|  |           << setprecision(precision) << setw(width) << cdf(s, z) << "  " | ||
|  |           << setprecision(precision) << setw(width) << cdf(l, z) <<  "  (" | ||
|  |           << setprecision(precision) << setw(width) << cdf(l, z) - cdf(s, z) // difference.
 | ||
|  |           << ")" << endl; | ||
|  |       } | ||
|  |       cout.precision(6); // default
 | ||
|  | 
 | ||
|  | /*`
 | ||
|  | Pretty-printing a traditional 2-dimensional table is left as an exercise for the student, | ||
|  | but why bother now that the Boost Math Toolkit lets you write | ||
|  | */ | ||
|  |     double z = 2.;  | ||
|  |     cout << "Area for gaussian z = " << z << " is " << cdf(s, z) << endl; // to get the area for z.
 | ||
|  |     cout << "Area for laplace z = " << z << " is " << cdf(l, z) << endl; // 
 | ||
|  | /*`
 | ||
|  | Correspondingly, we can obtain the traditional 'critical' values for significance levels. | ||
|  | For the 95% confidence level, the significance level usually called alpha, | ||
|  | is 0.05 = 1 - 0.95 (for a one-sided test), so we can write | ||
|  | */ | ||
|  |      cout << "95% of gaussian area has a z below " << quantile(s, 0.95) << endl; | ||
|  |      cout << "95% of laplace area has a z below " << quantile(l, 0.95) << endl; | ||
|  |    // 95% of area has a z below 1.64485
 | ||
|  |    // 95% of laplace area has a z below 2.30259
 | ||
|  | /*`and a two-sided test (a comparison between two levels, rather than a one-sided test)
 | ||
|  | 
 | ||
|  | */ | ||
|  |      cout << "95% of gaussian area has a z between " << quantile(s, 0.975) | ||
|  |        << " and " << -quantile(s, 0.975) << endl; | ||
|  |      cout << "95% of laplace area has a z between " << quantile(l, 0.975) | ||
|  |        << " and " << -quantile(l, 0.975) << endl; | ||
|  |    // 95% of area has a z between 1.95996 and -1.95996
 | ||
|  |    // 95% of laplace area has a z between 2.99573 and -2.99573
 | ||
|  | /*`Notice how much wider z has to be to enclose 95% of the area.
 | ||
|  | */ | ||
|  |   } | ||
|  | //] [/[laplace_example1]
 | ||
|  |   } | ||
|  |   catch(const std::exception& e) | ||
|  |   { // Always useful to include try & catch blocks because default policies 
 | ||
|  |     // are to throw exceptions on arguments that cause errors like underflow, overflow. 
 | ||
|  |     // Lacking try & catch blocks, the program will abort without a message below,
 | ||
|  |     // which may give some helpful clues as to the cause of the exception.
 | ||
|  |     std::cout << | ||
|  |       "\n""Message from thrown exception was:\n   " << e.what() << std::endl; | ||
|  |   } | ||
|  |   return 0; | ||
|  | }  // int main()
 | ||
|  | 
 | ||
|  | /*
 | ||
|  | 
 | ||
|  | Output is: | ||
|  | 
 | ||
|  | Example: Laplace distribution. | ||
|  | Standard normal distribution, mean or location = 0, standard deviation or scale = 1 | ||
|  | Laplace normal distribution, location = 0, scale = 1 | ||
|  | Probability distribution function values | ||
|  |  z  PDF  normal     laplace    (difference) | ||
|  | -4     0.0001338   0.009158    (0.009024  ) | ||
|  | -3     0.004432    0.02489     (0.02046   ) | ||
|  | -2     0.05399     0.06767     (0.01368   ) | ||
|  | -1     0.242       0.1839      (-0.05803  ) | ||
|  | 0      0.3989      0.5         (0.1011    ) | ||
|  | 1      0.242       0.1839      (-0.05803  ) | ||
|  | 2      0.05399     0.06767     (0.01368   ) | ||
|  | 3      0.004432    0.02489     (0.02046   ) | ||
|  | 4      0.0001338   0.009158    (0.009024  ) | ||
|  | Standard location = 0, scale = 1 | ||
|  | Integral (area under the curve) from - infinity up to z  | ||
|  |  z  CDF  normal     laplace    (difference) | ||
|  | -4     3.167e-005  0.009158    (0.009126  ) | ||
|  | -3     0.00135     0.02489     (0.02354   ) | ||
|  | -2     0.02275     0.06767     (0.04492   ) | ||
|  | -1     0.1587      0.1839      (0.02528   ) | ||
|  | 0      0.5         0.5         (0         ) | ||
|  | 1      0.8413      0.8161      (-0.02528  ) | ||
|  | 2      0.9772      0.9323      (-0.04492  ) | ||
|  | 3      0.9987      0.9751      (-0.02354  ) | ||
|  | 4      1           0.9908      (-0.009126 ) | ||
|  | Area for gaussian z = 2 is 0.97725 | ||
|  | Area for laplace z = 2 is 0.932332 | ||
|  | 95% of gaussian area has a z below 1.64485 | ||
|  | 95% of laplace area has a z below 2.30259 | ||
|  | 95% of gaussian area has a z between 1.95996 and -1.95996 | ||
|  | 95% of laplace area has a z between 2.99573 and -2.99573 | ||
|  | 
 | ||
|  | */ | ||
|  | 
 |