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std::gamma_distribution

From cppreference.com
< cpp‎ | numeric‎ | random
 
 
Numerics library
 
Pseudo-random number generation
 
 
Defined in header <random>
template< class RealType = double >
class gamma_distribution;
(since C++11)

Produces random positive floating-point values x, distributed according to probability density function:

\(\mathsf{p}(x\mid\alpha,\beta) = \frac{e^{-x/\beta} }{\beta^\alpha\cdot\Gamma(\alpha)}\cdot x^{\alpha-1} \)P(x|α,β) =
e-x/β
βα
· Γ(α)
· xα-1

where α is known as the shape parameter and β is known as the scale parameter. The shape parameter is sometimes denoted by the letter k and the scale parameter is sometimes denoted by the letter θ.

For floating-point α, the value obtained is the sum of α independent exponentially distributed random variables, each of which has a mean of β.

std::gamma_distribution satisfies RandomNumberDistribution.

[edit] Template parameters

RealType - The result type generated by the generator. The effect is undefined if this is not one of float, double, or long double.

[edit] Member types

Member type Definition
result_type (C++11) RealType
param_type (C++11) the type of the parameter set, see RandomNumberDistribution.

[edit] Member functions

constructs new distribution
(public member function) [edit]
(C++11)
resets the internal state of the distribution
(public member function) [edit]
Generation
(C++11)
generates the next random number in the distribution
(public member function) [edit]
Characteristics
(C++11)
returns the distribution parameters
(public member function) [edit]
(C++11)
gets or sets the distribution parameter object
(public member function) [edit]
(C++11)
returns the minimum potentially generated value
(public member function) [edit]
(C++11)
returns the maximum potentially generated value
(public member function) [edit]

[edit] Non-member functions

(C++11)(C++11)(removed in C++20)
compares two distribution objects
(function) [edit]
performs stream input and output on pseudo-random number distribution
(function template) [edit]

[edit] Example

Run this code
#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <string>
 
int main()
{
 std::random_device rd;
 std::mt19937 gen(rd());
 
 // A gamma distribution with alpha = 1, and beta = 2
 // approximates an exponential distribution.
 std::gamma_distribution<> d(1, 2);
 
 std::map <int, int> hist;
 for (int n = 0; n != 10000; ++n)
 ++hist[2 * d(gen)];
 
 for (auto const& [x, y] : hist)
 if (y / 100.0 > 0.5)
 std::cout << std::fixed << std::setprecision (1)
 << x / 2.0 << '-' << (x + 1) / 2.0 << ' '
 << std::string (y / 100, '*') << '\n';
}

Possible output:

0.0-0.5 **********************
0.5-1.0 ****************
1.0-1.5 *************
1.5-2.0 **********
2.0-2.5 ********
2.5-3.0 ******
3.0-3.5 *****
3.5-4.0 ****
4.0-4.5 ***
4.5-5.0 **
5.0-5.5 **
5.5-6.0 *
6.0-6.5 *
6.5-7.0
7.0-7.5
7.5-8.0

[edit] External links

Weisstein, Eric W. "Gamma Distribution." From MathWorld — A Wolfram Web Resource.
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