From: pbristow_at_[hidden]
Date: 2007-08-28 09:22:00
Author: pbristow
Date: 2007-08-28 09:22:00 EDT (Tue, 28 Aug 2007)
New Revision: 39032
URL: http://svn.boost.org/trac/boost/changeset/39032
Log:
Removed file/folder
Removed:
sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp
Deleted: sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp
==============================================================================
--- sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp 2007-08-28 09:22:00 EDT (Tue, 28 Aug 2007)
+++ (empty file)
@@ -1,91 +0,0 @@
-// Copyright Paul A. 2007
-// Copyright John Maddock 2007
-// 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)
-
-// Simple example of computing probabilities for a binomial random variable.
-// Replication of source nag_binomial_dist (g01bjc).
-
-// Shows how to replace NAG C library calls by Boost Math Toolkit C++ calls.
-// Note that the default policy does not replicate the way that NAG
-// library calls handle 'bad' arguments, but you can define policies that do,
-// as well as other policies that may suit your application even better.
-// See the examples of changing default policies for details.
-
-#include <boost/math/distributions/binomial.hpp>
-
-#include <iostream>
- using std::cout; using std::endl; using std::ios; using std::showpoint;
-#include <iomanip>
- using std::fixed; using std::setw;
-
-int main()
-{
- cout << "Using the binomial distribution to replicate a NAG library call." << endl;
- using boost::math::binomial_distribution;
-
- // This replicates the computation of the examples of using nag-binomial_dist
- // using g01bjc in section g01 Somple Calculations on Statistical Data.
- // http://www.nag.co.uk/numeric/cl/manual/pdf/G01/g01bjc.pdf
- // Program results section 8.3 page 3.g01bjc.3
- //8.2. Program Data
- //g01bjc Example Program Data
- //4 0.50 2 : n, p, k
- //19 0.44 13
- //100 0.75 67
- //2000 0.33 700
- //8.3. Program Results
- //g01bjc Example Program Results
- //n p k plek pgtk peqk
- //4 0.500 2 0.68750 0.31250 0.37500
- //19 0.440 13 0.99138 0.00862 0.01939
- //100 0.750 67 0.04460 0.95540 0.01700
- //2000 0.330 700 0.97251 0.02749 0.00312
-
- cout.setf(ios::showpoint); // Trailing zeros to show significant decimal digits.
- cout.precision(5); // Might calculate this from trials in distribution?
- cout << fixed;
- // Binomial distribution.
-
- // Note that cdf(dist, k) is equivalent to NAG library plek probability of <= k
- // cdf(complement(dist, k)) is equivalent to NAG library pgtk probability of > k
- // pdf(dist, k) is equivalent to NAG library peqk probability of == k
-
- cout << " n p k plek pgtk peqk " << endl;
- binomial_distribution<>my_dist(4, 0.5);
- cout << setw(4) << (int)my_dist.trials() << " " << my_dist.success_fraction()
- << " " << 2 << " " << cdf(my_dist, 2) << " "
- << cdf(complement(my_dist, 2)) << " " << pdf(my_dist, 2) << endl;
-
- binomial_distribution<>two(19, 0.440);
- cout << setw(4) << (int)two.trials() << " " << two.success_fraction()
- << " " << 13 << " " << cdf(two, 13) << " "
- << cdf(complement(two, 13)) << " " << pdf(two, 13) << endl;
-
- binomial_distribution<>three(100, 0.750);
- cout << setw(4) << (int)three.trials() << " " << three.success_fraction()
- << " " << 67 << " " << cdf(three, 67) << " " << cdf(complement(three, 67))
- << " " << pdf(three, 67) << endl;
- binomial_distribution<>four(2000, 0.330);
- cout << setw(4) << (int)four.trials() << " " << four.success_fraction()
- << " " << 700 << " "
- << cdf(four, 700) << " " << cdf(complement(four, 700))
- << " " << pdf(four, 700) << endl;
-
- return 0;
-} // int main()
-
-/*
-
-Example of using the binomial distribution to replicate a NAG library call.
- n p k plek pgtk peqk
- 4 0.50000 2 0.68750 0.31250 0.37500
- 19 0.44000 13 0.99138 0.00862 0.01939
- 100 0.75000 67 0.04460 0.95540 0.01700
-2000 0.33000 700 0.97251 0.02749 0.00312
-
-
- */
-