lti::varianceFunctor< T >::parameters Class Reference

the parameters for the class varianceFunctor More...

#include <ltiVarianceFunctor.h>

Inheritance diagram for lti::varianceFunctor< T >::parameters:

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Collaboration diagram for lti::varianceFunctor< T >::parameters:

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List of all members.

Public Types
enum	eVarianceType { Empirical = 0, Maxlikely = 1 }
Public Member Functions
	parameters ()
	parameters (const parameters &other)
	~parameters ()
const char *	getTypeName () const
parameters &	copy (const parameters &other)
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
virtual functor::parameters *	clone () const
Public Attributes
bool	rowWise
eVarianceType	type
bool	correlation

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Detailed Description

template<class T>
class lti::varianceFunctor< T >::parameters

the parameters for the class varianceFunctor

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Member Enumeration Documentation

template<class T >

enum lti::varianceFunctor::parameters::eVarianceType

Type of the variance.

Enumerator:

Empirical	Empirical Variance: .
Maxlikely	Maximum Likelihood Variance: .

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Constructor & Destructor Documentation

template<class T >

lti::varianceFunctor< T >::parameters::parameters

(

void

)

[inline]

default constructor

Reimplemented from lti::statisticsFunctor::parameters.

References lti::varianceFunctor< T >::parameters::Empirical, lti::varianceFunctor< T >::parameters::rowWise, and lti::varianceFunctor< T >::parameters::type.

Referenced by lti::varianceFunctor< T >::parameters::clone().

template<class T >

lti::varianceFunctor< T >::parameters::parameters

(

const parameters &

other

)

[inline]

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented from lti::statisticsFunctor::parameters.

References lti::varianceFunctor< T >::parameters::copy().

template<class T >

lti::varianceFunctor< T >::parameters::~parameters

(

)

[inline, virtual]

destructor

Reimplemented from lti::statisticsFunctor::parameters.

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Member Function Documentation

template<class T >

virtual functor::parameters* lti::varianceFunctor< T >::parameters::clone

(

)

const [inline, virtual]

returns a pointer to a clone of the parameters

Reimplemented from lti::statisticsFunctor::parameters.

References lti::varianceFunctor< T >::parameters::parameters().

template<class T >

parameters& lti::varianceFunctor< T >::parameters::copy

(

const parameters &

other

)

[inline]

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:

a reference to this parameters object

Reimplemented from lti::statisticsFunctor::parameters.

References lti::statisticsFunctor::parameters::copy(), lti::varianceFunctor< T >::parameters::rowWise, and lti::varianceFunctor< T >::parameters::type.

Referenced by lti::varianceFunctor< T >::parameters::parameters().

template<class T >

const char* lti::varianceFunctor< T >::parameters::getTypeName

(

void

)

const [inline, virtual]

returns name of this type

Reimplemented from lti::statisticsFunctor::parameters.

template<class T >

virtual bool lti::varianceFunctor< T >::parameters::read	(	ioHandler &	handler,
		const bool	complete = true
	)			[inline, virtual]

read the parameters from the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also read, otherwise only the data block will be read.

Returns:

true if write was successful

Reimplemented from lti::functor::parameters.

References lti::varianceFunctor< T >::parameters::Empirical, lti::varianceFunctor< T >::parameters::Maxlikely, lti::ioHandler::readBegin(), lti::ioHandler::readEnd(), lti::varianceFunctor< T >::parameters::rowWise, and lti::varianceFunctor< T >::parameters::type.

template<class T >

virtual bool lti::varianceFunctor< T >::parameters::write	(	ioHandler &	handler,
		const bool	complete = true
	)			const [inline, virtual]

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::functor::parameters.

References lti::varianceFunctor< T >::parameters::Empirical, lti::varianceFunctor< T >::parameters::rowWise, lti::varianceFunctor< T >::parameters::type, lti::ioHandler::writeBegin(), and lti::ioHandler::writeEnd().

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Member Data Documentation

template<class T >

bool lti::varianceFunctor< T >::parameters::correlation

If this flag is true, the covariance matrix is normalized to contain the correlation coefficients instead of the covariances.

Default value: false

template<class T >

bool lti::varianceFunctor< T >::parameters::rowWise

If this flag is true, the variance computation will be row-wise, i.e.

the result will contain a sum of the rows. This is much faster than column-wise, since data do not have to be copied.

Default value: true

Referenced by lti::varianceFunctor< T >::parameters::copy(), lti::varianceFunctor< T >::parameters::parameters(), lti::varianceFunctor< T >::parameters::read(), and lti::varianceFunctor< T >::parameters::write().

template<class T >

eVarianceType lti::varianceFunctor< T >::parameters::type

The type of the variance computation.

If type == empirical, the empirical variance or covariance matrix is computed (division by number of samples minus 1), otherwise, the maximum likelihood estimator is computed (division by number of samples).

Default value: Empirical

Referenced by lti::varianceFunctor< T >::parameters::copy(), lti::varianceFunctor< T >::parameters::parameters(), lti::varianceFunctor< T >::parameters::read(), and lti::varianceFunctor< T >::parameters::write().

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

• ltiVarianceFunctor.h