crn::UnivariateRandomTools Namespace Reference

Univariate random toolbox class. More...

Functions
std::vector< double >	NewUniformSample (size_t n=1, bool reseed=true)
	Creates a data sample following an uniform probability law. More...
std::vector< double >	NewGaussianSample (double mu=0.0, double sigma=1.0, size_t n=1, size_t m=100, bool reseed=true)
	Creates a data sample following a Gaussian probability law. More...
std::vector< double >	NewGaussianMixtureSample (const UnivariateGaussianMixture &Mx, size_t n=1, size_t m=100, bool reseed=true)
	Creates a data sample following a Gaussian probability law. More...

Detailed Description

Univariate random toolbox class.

Tools for random samples

Author

Jean DUONG

Date

August 2008

Version

0.2

Function Documentation

std::vector< double > crn::UnivariateRandomTools::NewGaussianMixtureSample	(	const UnivariateGaussianMixture &	Mx,
		size_t	n = 1,
		size_t	m = 100,
		bool	reseed = true
	)

Creates a data sample following a Gaussian probability law.

Simulate a gaussian mixture random sample

Parameters

[in]	Mx	UnivariateGaussianMixture*
[in]	n	size of gaussian sample (default = 1)
[in]	m	size of temporary uniform sample (default = 100)
[in]	reseed	shall the random seed be reinitialized?

Returns

a set of patterns generated by the Gaussian law

Definition at line 103 of file CRNUnivariateRandomTools.cpp.

std::vector< double > crn::UnivariateRandomTools::NewGaussianSample	(	double	mu = 0.0,
		double	sigma = 1.0,
		size_t	n = 1,
		size_t	m = 100,
		bool	reseed = true
	)

Creates a data sample following a Gaussian probability law.

Simulate a gaussian random sample

With default values mu = 0 and sigma = 1, we obtain the normal random sample

Parameters

[in]	mu	mean of gaussian distribution (default = 0)
[in]	sigma	deviation of gaussian distribution (default = 1)
[in]	n	size of gaussian sample (default = 1)
[in]	m	size of temporary uniform sample (default = 100)
[in]	reseed	shall the random seed be reinitialized?

Returns

a set of patterns generated by the Gaussian law

Definition at line 65 of file CRNUnivariateRandomTools.cpp.

std::vector< double > crn::UnivariateRandomTools::NewUniformSample	(	size_t	n = 1,
		bool	reseed = true
	)

Creates a data sample following an uniform probability law.

Simulate a uniform random sample in [0;1]

Parameters

[in]	n	size of sample
[in]	reseed	shall the random seed be reinitialized?

Returns

a set of patterns generated by the uniform law

Definition at line 38 of file CRNUnivariateRandomTools.cpp.