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Difference between revisions of "cpp/numeric/random/student t distribution"

From cppreference.com
< cpp‎ | numeric‎ | random
m (deg of freedoms = samples - 1)
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{{cpp/title|student_t_distribution}}
 
{{cpp/title|student_t_distribution}}
{{cpp/numeric/random/student_t_distribution/sidebar}}
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{{cpp/numeric/random/student_t_distribution/}}
{{ddcl | header=random | notes={{mark since c++11}} | 1=
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{{ddcl|header=random|=c++11|1=
 
template< class RealType = double >
 
template< class RealType = double >
 
class student_t_distribution;
 
class student_t_distribution;
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Produces random floating-point values {{math|x}}, distributed according to probability density function:
 
Produces random floating-point values {{math|x}}, distributed according to probability density function:
  
:{{math|P(x{{!}}n) {{=}} {{mfrac|1|{{mrad|n&pi;}}}} · {{mfrac|Γ({{mfrac|n+1|2}})|Γ({{mfrac|n|2}})}} · {{mparen|(|)|1+{{mfrac|x{{su|p=2}}|n}}|rows=3}} {{su|p=-{{mfrac|n+1|2}}}}}}
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:{{|(x{{!}}n) {{=}} {{mfrac|1|{{mrad|n&pi;}}}} · {{mfrac|Γ({{mfrac|n+1|2}})|Γ({{mfrac|n|2}})}} · {{mparen|(|)|1+{{mfrac|x{{su|p=2}}|n}}|rows=3}} {{su|p=-{{mfrac|n+1|2}}}}}}
  
where {{math|n}} is known as the number of ''degrees of freedom''. This distribution is used when estimating the ''mean'' of an unknown normally distributed value given {{math|n+1}} independent measurements, each with additive errors of unknown standard deviation, as in physical measurements. Or, alternatively, when estimating the unknown mean of a normal distribution with unknown standard deviation, given {{math|n+1}} samples.
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where {{math|n}} is known as the number of ''degrees of freedom''. This distribution is used when estimating the ''mean'' of an unknown normally distributed value given {{math|n + 1}} independent measurements, each with additive errors of unknown standard deviation, as in physical measurements. Or, alternatively, when estimating the unknown mean of a normal distribution with unknown standard deviation, given {{math|n + 1}} samples.
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===Member types===
 
===Member types===
{{tdcl list begin}}
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{{begin}}
{{tdcl list hitem | Member type | Definition}}
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{{hitem|Member type|Definition}}
{{tdcl list item | {{tt|result_type}} | {{cpp|RealType}}}}
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{{|{{tt|result_type}}|{{|RealType}}}}
{{tdcl list item | {{tt|param_type}} | the type of the parameter set, unspecified}}
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{{param_type}}
{{tdcl list end}}
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{{end}}
  
 
===Member functions===
 
===Member functions===
{{dcl list begin}}
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{{begin}}
{{dcl list template | cpp/numeric/random/distribution/dcl list constructor | student_t_distribution}}
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{{|cpp/numeric/random/distribution/constructor|student_t_distribution}}
{{dcl list template | cpp/numeric/random/distribution/dcl list reset | student_t_distribution}}
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{{|cpp/numeric/random/distribution/reset|student_t_distribution}}
  
{{dcl list h2 | Generation}}
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{{h2|Generation}}
{{dcl list template | cpp/numeric/random/distribution/dcl list operator() | student_t_distribution}}
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{{|cpp/numeric/random/distribution/operator()|student_t_distribution}}
  
{{dcl list h2 | Characteristics}}
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{{h2|Characteristics}}
{{dcl list template | cpp/numeric/random/student_t_distribution/dcl list n}}
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{{|cpp/numeric/random/student_t_distribution/n}}
{{dcl list template | cpp/numeric/random/distribution/dcl list param | student_t_distribution}}
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{{|cpp/numeric/random/distribution/param|student_t_distribution}}
{{dcl list template | cpp/numeric/random/distribution/dcl list min | student_t_distribution}}
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{{|cpp/numeric/random/distribution/min|student_t_distribution}}
{{dcl list template | cpp/numeric/random/distribution/dcl list max | student_t_distribution}}
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{{|cpp/numeric/random/distribution/max|student_t_distribution}}
{{dcl list end}}
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{{end}}
  
 
===Non-member functions===
 
===Non-member functions===
{{dcl list begin}}
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{{begin}}
{{dcl list template | cpp/numeric/random/distribution/dcl list operator_cmp | student_t_distribution}}
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{{|cpp/numeric/random/distribution/operator_cmp|student_t_distribution}}
{{dcl list template | cpp/numeric/random/distribution/dcl list operator_ltltgtgt | student_t_distribution}}
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{{|cpp/numeric/random/distribution/operator_ltltgtgt|student_t_distribution}}
{{dcl list end}}
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{{end}}
  
 
===Example===
 
===Example===
{{example cpp
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{{example
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| output=
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}}
 
}}
  
 
===External links===
 
===External links===
[http://mathworld.wolfram.com/Studentst-Distribution.html Weisstein, Eric W. "Student's t-Distribution."] From MathWorld--A Wolfram Web Resource.
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[://mathworld.wolfram.com/Studentst-Distribution.html Weisstein, Eric W. "Student's t-Distribution."] From MathWorld A Wolfram Web Resource.
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Latest revision as of 11:49, 17 October 2023

 
 
 
 
 
Defined in header <random>
template< class RealType = double >
class student_t_distribution;
(since C++11)

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

p(x|n) =
1
·
Γ(
n+1
2
)
Γ(
n
2
)
·

1+
x2
n


-
n+1
2

where n is known as the number of degrees of freedom. This distribution is used when estimating the mean of an unknown normally distributed value given n + 1 independent measurements, each with additive errors of unknown standard deviation, as in physical measurements. Or, alternatively, when estimating the unknown mean of a normal distribution with unknown standard deviation, given n + 1 samples.

std::student_t_distribution satisfies all requirements of RandomNumberDistribution.

Contents

[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
generates the next random number in the distribution
(public member function) [edit]
Characteristics
returns the n distribution parameter (degrees of freedom)
(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

#include <algorithm>
#include <cmath>
#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <vector>
 
template<int Height = 5, int BarWidth = 1, int Padding = 1, int Offset = 0, class Seq>
void draw_vbars(Seq&& s, const bool DrawMinMax = true)
{
    static_assert(0 < Height and 0 < BarWidth and 0 <= Padding and 0 <= Offset);
 
    auto cout_n = [](auto&& v, int n = 1)
    {
        while (n-- > 0)
            std::cout << v;
    };
 
    const auto [min, max] = std::minmax_element(std::cbegin(s), std::cend(s));
 
    std::vector<std::div_t> qr;
    for (typedef decltype(*std::cbegin(s)) V; V e : s)
        qr.push_back(std::div(std::lerp(V(0), 8 * Height,
                                        (e - *min) / (*max - *min)), 8));
 
    for (auto h{Height}; h-- > 0; cout_n('\n'))
    {
        cout_n(' ', Offset);
 
        for (auto dv : qr)
        {
            const auto q{dv.quot}, r{dv.rem};
            unsigned char d[]{0xe2, 0x96, 0x88, 0}; // Full Block: '█'
            q < h ? d[0] = ' ', d[1] = 0 : q == h ? d[2] -= (7 - r) : 0;
            cout_n(d, BarWidth), cout_n(' ', Padding);
        }
 
        if (DrawMinMax && Height > 1)
            Height - 1 == h ? std::cout << "┬ " << *max:
                          h ? std::cout << "│ "
                            : std::cout << "┴ " << *min;
    }
}
 
int main()
{
    std::random_device rd{};
    std::mt19937 gen{rd()};
 
    std::student_t_distribution<> d{10.0f};
 
    const int norm = 10'000;
    const float cutoff = 0.000'3f;
 
    std::map<int, int> hist{};
    for (int n = 0; n != norm; ++n)
        ++hist[std::round(d(gen))];
 
    std::vector<float> bars;
    std::vector<int> indices;
    for (const auto& [n, p] : hist)
        if (float x = p * (1.0f / norm); cutoff < x)
        {
            bars.push_back(x);
            indices.push_back(n);
        }
 
    for (draw_vbars<8, 5>(bars); const int n : indices)
        std::cout << " " << std::setw(2) << n << "   ";
    std::cout << '\n';
}

Possible output:

                        █████                               ┬ 0.3753
                        █████                               │
                  ▁▁▁▁▁ █████                               │
                  █████ █████ ▆▆▆▆▆                         │
                  █████ █████ █████                         │
                  █████ █████ █████                         │
            ▄▄▄▄▄ █████ █████ █████ ▄▄▄▄▄                   │
▁▁▁▁▁ ▃▃▃▃▃ █████ █████ █████ █████ █████ ▃▃▃▃▃ ▁▁▁▁▁ ▁▁▁▁▁ ┴ 0.0049
 -4    -3    -2    -1     0     1     2     3     4     5

[edit] External links

Weisstein, Eric W. "Student's t-Distribution." From MathWorld — A Wolfram Web Resource.