Gaussian Class Reference

Class representing Gaussian (or normal density) More...

#include <gaussian.h>

Inheritance diagram for Gaussian:

List of all members.

Public Member Functions
	Gaussian (const MatrixWrapper::ColumnVector &Mu, const MatrixWrapper::SymmetricMatrix &Sigma)
	Constructor.
	Gaussian (int dimension=0)
	constructor with only dimensions or nothing
virtual	~Gaussian ()
	Default Copy Constructor will do.
virtual Gaussian *	Clone () const
	Clone function.
virtual Probability	ProbabilityGet (const MatrixWrapper::ColumnVector &input) const
	Get the probability of a certain argument.
bool	SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const int num_samples, int method=DEFAULT, void *args=NULL) const
virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const
virtual MatrixWrapper::ColumnVector	ExpectedValueGet () const
	Get the expected value E[x] of the pdf.
virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const
	Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
void	ExpectedValueSet (const MatrixWrapper::ColumnVector &mu)
	Set the Expected Value.
void	CovarianceSet (const MatrixWrapper::SymmetricMatrix &cov)
	Set the Covariance Matrix.
virtual bool	SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const
	Draw multiple samples from the Pdf (overloaded)
virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const
	Draw 1 sample from the Pdf:
unsigned int	DimensionGet () const
	Get the dimension of the argument.
unsigned int	DimensionGet () const
	Get the dimension of the argument.
unsigned int	DimensionGet () const
	Get the dimension of the argument.
unsigned int	DimensionGet () const
	Get the dimension of the argument.
virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument.
virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument.
virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument.
virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument.
Friends
std::ostream &	operator<< (std::ostream &os, const Gaussian &g)
	output stream for Gaussian

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Detailed Description

Class representing Gaussian (or normal density)

Definition at line 27 of file gaussian.h.

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Constructor & Destructor Documentation

Gaussian	(	const MatrixWrapper::ColumnVector &	Mu,
		const MatrixWrapper::SymmetricMatrix &	Sigma
	)

Constructor.

Parameters:

Mu	Mean Vector of the Gaussian
Sigma	Covariance Matrix of the Gaussian

virtual ~Gaussian

(

)

[virtual]

Default Copy Constructor will do.

Destructor

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Member Function Documentation

virtual MatrixWrapper::SymmetricMatrix CovarianceGet

(

)

const [virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:

The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)

Todo:

extend this more general to n-th order statistic

Bug:

Discrete pdfs should not be able to use this!

Reimplemented from Pdf< MatrixWrapper::ColumnVector >.

void CovarianceSet

(

const MatrixWrapper::SymmetricMatrix &

cov

)

Set the Covariance Matrix.

Set the Covariance Matrix

Parameters:

cov	The new Covariance matrix

unsigned int DimensionGet

(

)

const [inherited]

Get the dimension of the argument.

Returns:

the dimension of the argument

unsigned int DimensionGet

(

)

const [inherited]

Get the dimension of the argument.

Returns:

the dimension of the argument

unsigned int DimensionGet

(

)

const [inherited]

Get the dimension of the argument.

Returns:

the dimension of the argument

unsigned int DimensionGet

(

)

const [inherited]

Get the dimension of the argument.

Returns:

the dimension of the argument

virtual void DimensionSet

(

unsigned int

dim

)

[virtual, inherited]

Set the dimension of the argument.

Parameters:

dim	the dimension

virtual void DimensionSet

(

unsigned int

dim

)

[virtual, inherited]

Set the dimension of the argument.

Parameters:

dim	the dimension

virtual void DimensionSet

(

unsigned int

dim

)

[virtual, inherited]

Set the dimension of the argument.

Parameters:

dim	the dimension

virtual void DimensionSet

(

unsigned int

dim

)

[virtual, inherited]

Set the dimension of the argument.

Parameters:

dim	the dimension

virtual MatrixWrapper::ColumnVector ExpectedValueGet

(

)

const [virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:

The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)

Note:

No set functions here! This can be useful for analytic functions, but not for sample based representations!

For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from Pdf< MatrixWrapper::ColumnVector >.

void ExpectedValueSet

(

const MatrixWrapper::ColumnVector &

mu

)

Set the Expected Value.

Set the Expected Value

Parameters:

mu	The new Expected Value

virtual Probability ProbabilityGet

(

const MatrixWrapper::ColumnVector &

input

)

const [virtual]

Get the probability of a certain argument.

Parameters:

input

T argument of the Pdf

Returns:

the probability value of the argument

Reimplemented from Pdf< MatrixWrapper::ColumnVector >.

virtual bool SampleFrom	(	vector< Sample< MatrixWrapper::ColumnVector > > &	list_samples,
		const unsigned int	num_samples,
		int	method = DEFAULT,
		void *	args = NULL
	)		const [virtual, inherited]

Draw multiple samples from the Pdf (overloaded)

Parameters:

list_samples	list of samples that will contain result of sampling
num_samples	Number of Samples to be drawn (iid)
method	Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
args	Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent...

Todo:

replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)

Bug:

Sometimes the compiler doesn't know which method to choose!

virtual bool SampleFrom	(	Sample< MatrixWrapper::ColumnVector > &	one_sample,
		int	method = DEFAULT,
		void *	args = NULL
	)		const [virtual, inherited]

Draw 1 sample from the Pdf:

There's no need to create a list for only 1 sample!

Parameters:

one_sample	sample that will contain result of sampling
method	Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
args	Pointer to a struct representing extra sample arguments

See also:

SampleFrom()

Bug:

Sometimes the compiler doesn't know which method to choose!

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

• gaussian.h