randlib::BivariateDistribution< T1, T2, T > Class Template Reference

The BivariateDistribution class
Abstract class for all bivariate probability distributions. More...

#include <bivariate.hpp>

Inheritance diagram for randlib::BivariateDistribution< T1, T2, T >:

Collaboration diagram for randlib::BivariateDistribution< T1, T2, T >:

Public Member Functions
virtual	~BivariateDistribution ()
Pair< T >	MinValue () const override
Pair< T >	MaxValue () const override
virtual LongDoublePair	Mean () const final
virtual LongDoubleTriplet	Covariance () const final
virtual long double	Correlation () const =0
virtual std::pair< T1, T2 >	GetMarginalDistributions () const final
virtual Pair< T >	Mode () const =0
Public Member Functions inherited from randlib::ProbabilityDistribution< Pair< T > >
virtual	~ProbabilityDistribution ()=default
virtual std::string	Name () const=0
virtual double	F (const Pair< T > &x) const=0
void	CumulativeDistributionFunction (std::span< const Pair< T > > x, std::span< double > y) const
virtual double	S (const Pair< T > &x) const
void	SurvivalFunction (std::span< const Pair< T > > x, std::span< double > y) const
Pair< T >	operator() (G &g) const
	Draws a variate with the given engine through the virtual interface.
Pair< T >	Variate () const
	Uses the engine of this object, so it is not thread-safe for one object; use operator() with one engine per thread instead.
void	Sample (std::span< Pair< T > > outputData) const
	Fills the output with variates drawn with the engine of this object.
void	Sample (G &g, std::span< Pair< T > > outputData) const
	Fills the output with variates drawn with the given engine.
void	Reseed (std::uint64_t seed)

Protected Member Functions
	BivariateDistribution ()
Protected Member Functions inherited from randlib::ProbabilityDistribution< Pair< T > >
std::string	toStringWithPrecision (const double a_value, const int n=6) const
	ProbabilityDistribution ()=default
DefaultEngine &	engine () const
virtual Pair< T >	variate (detail::EngineRef g) const=0
	Every concrete distribution implements this by calling its templated operator()
virtual void	sample (detail::EngineRef g, std::span< Pair< T > > outputData) const
	Fills the output with variate(g); distributions with a faster bulk algorithm override it.
fit_error	fitError (FitErrorCode code, const std::string &explanation) const

Protected Attributes
T1	X {}
	1st marginal distributions
T2	Y {}
	2nd marginal distributions

Additional Inherited Members
Public Types inherited from randlib::ProbabilityDistribution< Pair< T > >
using	value_type = Pair< T >
Static Protected Attributes inherited from randlib::ProbabilityDistribution< Pair< T > >
static constexpr size_t	MAX_ITER_REJECTION
	MAX_ITER_REJECTION upper boundary for maximum amount of iterations in rejection methods one thousand should be enough to be sure there is a bug (or rejection method is too slow to be used)
static constexpr char	POSITIVITY_VIOLATION []
static constexpr char	NON_NEGATIVITY_VIOLATION []
static constexpr char	UPPER_LIMIT_VIOLATION []
static constexpr char	LOWER_LIMIT_VIOLATION []

Detailed Description

template<class T1, class T2, typename T>
class randlib::BivariateDistribution< T1, T2, T >

The BivariateDistribution class
Abstract class for all bivariate probability distributions.

Constructor & Destructor Documentation

BivariateDistribution()

template<class T1 , class T2 , typename T >

randlib::BivariateDistribution< T1, T2, T >::BivariateDistribution ( )

inlineprotected

~BivariateDistribution()

template<class T1 , class T2 , typename T >

virtual randlib::BivariateDistribution< T1, T2, T >::~BivariateDistribution ( )

inlinevirtual

Member Function Documentation

Correlation()

template<class T1 , class T2 , typename T >

virtual long double randlib::BivariateDistribution< T1, T2, T >::Correlation ( ) const

pure virtual

Implemented in randlib::BivariateNormalRand< RealType >, randlib::NormalInverseGammaRand< RealType >, and randlib::TrinomialRand< IntType >.

Covariance()

template<class T1 , class T2 , typename T >

LongDoubleTriplet randlib::BivariateDistribution< T1, T2, T >::Covariance ( ) const

finalvirtual

GetMarginalDistributions()

template<class T1 , class T2 , typename T >

std::pair< T1, T2 > randlib::BivariateDistribution< T1, T2, T >::GetMarginalDistributions ( ) const

finalvirtual

MaxValue()

template<class T1 , class T2 , typename T >

Pair< T > randlib::BivariateDistribution< T1, T2, T >::MaxValue ( ) const

inlineoverridevirtual

Returns

maximum possible value that can be achieved by random variable

Implements randlib::ProbabilityDistribution< Pair< T > >.

Mean()

template<class T1 , class T2 , typename T >

LongDoublePair randlib::BivariateDistribution< T1, T2, T >::Mean ( ) const

finalvirtual

MinValue()

template<class T1 , class T2 , typename T >

Pair< T > randlib::BivariateDistribution< T1, T2, T >::MinValue ( ) const

inlineoverridevirtual

Returns

minimum possible value that can be achieved by random variable

Implements randlib::ProbabilityDistribution< Pair< T > >.

Mode()

template<class T1 , class T2 , typename T >

virtual Pair< T > randlib::BivariateDistribution< T1, T2, T >::Mode ( ) const

pure virtual

Implemented in randlib::BivariateNormalRand< RealType >, randlib::NormalInverseGammaRand< RealType >, and randlib::TrinomialRand< IntType >.

Member Data Documentation

X

template<class T1 , class T2 , typename T >

T1 randlib::BivariateDistribution< T1, T2, T >::X {}

protected

1st marginal distributions

Y

template<class T1 , class T2 , typename T >

T2 randlib::BivariateDistribution< T1, T2, T >::Y {}

protected

2nd marginal distributions

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The documentation for this class was generated from the following file:

• bivariate.hpp