From: pbristow_at_[hidden]
Date: 2007-08-14 04:35:46
Author: pbristow
Date: 2007-08-14 04:35:44 EDT (Tue, 14 Aug 2007)
New Revision: 38644
URL: http://svn.boost.org/trac/boost/changeset/38644
Log:
New example of how to construct distributions
Text files modified:
sandbox/math_toolkit/libs/math/example/distribution_construction.cpp | 143 ++++++++++++++++++++-------------------
1 files changed, 72 insertions(+), 71 deletions(-)
Modified: sandbox/math_toolkit/libs/math/example/distribution_construction.cpp
==============================================================================
--- sandbox/math_toolkit/libs/math/example/distribution_construction.cpp (original)
+++ sandbox/math_toolkit/libs/math/example/distribution_construction.cpp 2007-08-14 04:35:44 EDT (Tue, 14 Aug 2007)
@@ -7,84 +7,68 @@
// (See accompanying file LICENSE_1_0.txt
// or copy at http://www.boost.org/LICENSE_1_0.txt)
-// Examples of using constructing distributions, mainly negative_binomial.
-// The structure of distributions is rather different from some other
-// statistical libraries, in less object oriented language like FOTRTRAN and C,
-// that provide a few arguments to each free function.
-// This library provides each distribution as a template C++ class.
-// A distribution is constructed with a few arguments, and then
-// member and non-member functions are used to find values of the
-// distribution, often a functions of a random variate.
+// Caution: this file contains Quickbook markup as well as code
+// and comments, don't change any of the special comment markups!
+
+//[distribution_construction1
+
+/*`
+
+The structure of distributions is rather different from some other statistical libraries,
+for example in less object-oriented language like FORTRAN and C,
+that provide a few arguments to each free function.
+This library provides each distribution as a template C++ class.
+A distribution is constructed with a few arguments, and then
+member and non-member functions are used to find values of the
+distribution, often a function of a random variate.
+
+First we need some includes to access the negative binomial distribution
+(and the binomial, beta and gamma too).
+
+*/
#include <boost/math/distributions/negative_binomial.hpp> // for negative_binomial_distribution
using boost::math::negative_binomial_distribution; // default type is double.
- using boost::math::negative_binomial; // typedef provides default type is double.
+ using boost::math::negative_binomial; // typedef provides default type is double.
#include <boost/math/distributions/binomial.hpp> // for binomial_distribution.
#include <boost/math/distributions/beta.hpp> // for beta_distribution.
#include <boost/math/distributions/gamma.hpp> // for gamma_distribution.
-#include <iostream>
- using std::cout;
- using std::endl;
+//] [/distribution_construction1 end of Quickbook in C++ markup]
+
+//[distribution_construction2
+
+/*`
+Several examples of constructing distributions follow:
+*/
int main()
{
- cout << "Examples of constructing Distributions (negative_binomial).";
- #if defined(__FILE__) && defined(__TIMESTAMP__)
- cout << " " << __FILE__ << ' ' << __TIMESTAMP__ << ' '<< _MSC_FULL_VER << "\n";
- #endif
- cout << endl;
-
- // Several examples of constructing distributions, for example, negative binomial:
+ // First, a negative binomial distribution with 8 successes
+ // and a success fraction 0.25, 25% or 1 in 4, is constructed like this:
- // Distributions are fundamentally constructed like this:
boost::math::negative_binomial_distribution<double> mydist0(8., 0.25);
// But this is inconveniently long, so by writing
using namespace boost::math;
- // or
+ // or
using boost::math::negative_binomial_distribution;
- // can reduce typing.
+ // we can reduce typing.
// Since the vast majority of applications use double,
- // the RealType default is made double, so one can write:
+ // the RealType default is chosen to be double, so we can also write:
- negative_binomial_distribution<> mydist9(8., 0.25); // Uses default RealType = double.
+ negative_binomial_distribution<> mydist9(8., 0.25); // Uses default RealType = double.
// But the name "negative_binomial_distribution" is still inconveniently long,
// so for most distributions, a typedef is provided, for example:
// typedef negative_binomial_distribution<double> negative_binomial; // Reserved name of type double.
- // (Unless a clash would occur with the name of a function, for example gamma, beta)
-
+ // (Unless a clash would occur with the name of a function, for example gamma & beta)
+ // So, after a using statement,
using boost::math::negative_binomial;
- // Allows convenient reference to negative_binomial_distribution<double> thus:
+ // we have a convenient reference to negative_binomial_distribution<double> thus:
negative_binomial mydist(8., 0.25); //
- // You can, of course, still provide the type explicitly thus:
- negative_binomial_distribution<double> mydist1(8., 0.25); // Explicit double.
- negative_binomial_distribution<float> mydist2(8., 0.25); // Explicit float, double arguments -> float.
- negative_binomial_distribution<float> mydist3(8, 0.25); // Explicit float, integer & double arguments -> float.
- negative_binomial_distribution<float> mydist4(8.F, 0.25F); // Explicit float, float arguments, no conversion.
- negative_binomial_distribution<float> mydist5(8, 1); // Explicit integer, integer arguments -> float.
- negative_binomial_distribution<double> mydist6(8., 0.25); // Explicit double.
- negative_binomial_distribution<long double> mydist7(8., 0.25); // Explicit long double.
- // And if you have your own RealType called MyFPType,
- // for example NTL quad_float (128-bit floating-point), then:
- // negative_binomial_distribution<MyFPType> mydist6(8, 1); // Integer arguments -> MyFPType.
-
- // Deafult arguments to distribution constructors.
- // Note that default constructor arguments are only provided for some distributions.
- // negative_binomial_distribution<> mydist8;
- // error C2512 no appropriate default constructor available.
- // No default constructor are provided,
- // because it is difficult to chose any sensible default values for this distribution.
- // For other distribution, like the normal distribution,
- // it is obviously very useful to provide 'standard'
- // defaults for the mean and standard deviation thus:
- // normal_distribution(RealType mean = 0, RealType sd = 1)
-
- // Some examples using the provided typedef:
- using boost::math::negative_binomial; // Convenient access to the name.
- // Allows convenient reference to negative_binomial of default type double.
+ // Some more examples using the provided convenience typedef:
negative_binomial mydist10(5., 0.4); // Both arguments double.
// And automatic conversion takes place, so you can use integers and floats:
negative_binomial mydist11(5, 0.4); // Using provided typedef double, int and double arguments.
@@ -92,14 +76,14 @@
negative_binomial mydist12(5., 0.4F); // Double and float arguments.
negative_binomial mydist13(5, 1); // Both arguments integer.
- // For cases when the typdef distribution name
- // would clash with a math special function
- // (for example: binomial, beta and gamma)
+ // Similarly for most other distributions like the binomial.
+ binomial mybinomial(1, 0.5); // is more concise than
+ binomial_distribution<> mybinomd1(1, 0.5);
+
+ // For cases when the typdef distribution name would clash with a math special function
+ // (for example: beta and gamma)
// the typedef is deliberately not provided, and the longer version(s) must be used.
// For example:
- using namespace boost::math;
- // NOT binomial mybd0(1, 0.5); // error C2065: 'binomial' : undeclared identifier
-
using boost::math::beta;
// NOT beta mybetad0(1, 0.5); because beta is a math FUNCTION!
// error C2146: syntax error : missing ';' before identifier 'mybetad0'
@@ -108,23 +92,40 @@
// Instead use:
using boost::math::beta_distribution;
beta_distribution<> mybetad1(1, 0.5);
- // Other examples are:
- binomial_distribution<> mybinomd1(1, 0.5);
+ // or for the gamm distribution:
gamma_distribution<> mygammad1(1, 0.5);
- return 0;
-} // int main()
-
-/*
-
-Output is:
-
-Examples of constructing Distributions (Negative_binomial). ..\..\..\..\..\..\Boost-sandbox\
-
-*/
+ // We can, of course, still provide the type explicitly thus:
+ negative_binomial_distribution<double> mydist1(8., 0.25); // Explicit double.
+ negative_binomial_distribution<float> mydist2(8., 0.25); // Explicit float, double arguments -> float.
+ negative_binomial_distribution<float> mydist3(8, 0.25); // Explicit float, integer & double arguments -> float.
+ negative_binomial_distribution<float> mydist4(8.F, 0.25F); // Explicit float, float arguments, no conversion.
+ negative_binomial_distribution<float> mydist5(8, 1); // Explicit integer, integer arguments -> float.
+ negative_binomial_distribution<double> mydist6(8., 0.25); // Explicit double.
+ negative_binomial_distribution<long double> mydist7(8., 0.25); // Explicit long double.
+ // And if you have your own RealType called MyFPType,
+ // for example NTL quad_float (128-bit floating-point), then:
+ // negative_binomial_distribution<MyFPType> mydist6(8, 1); // Integer arguments -> MyFPType.
+ /*`
+ Default arguments to distribution constructors.
+ */
+ // Note that default constructor arguments are only provided for some distributions.
+ // So if you wrongly assume a default argument you will get an error message, for example:
+ // negative_binomial_distribution<> mydist8;
+ // error C2512 no appropriate default constructor available.
+ // No default constructors are provided for the negative binomial,
+ // because it is difficult to chose any sensible default values for this distribution.
+ // For other distributions, like the normal distribution,
+ // it is obviously very useful to provide 'standard'
+ // defaults for the mean and standard deviation thus:
+ // normal_distribution(RealType mean = 0, RealType sd = 1)
+ return 0;
+} // int main()
+/*`There is no useful output from this program, of course. */
+//] [/end of distribution_construction2]