npstat::DistributionMixND Class Reference

Inheritance diagram for npstat::DistributionMixND:

Public Member Functions
	DistributionMixND (unsigned dim)
	DistributionMixND (const DistributionMixND &)
DistributionMixND &	operator= (const DistributionMixND &)
virtual DistributionMixND *	clone () const
DistributionMixND &	add (const AbsDistributionND &distro, double weight)
void	setWeights (const double *weights, unsigned nWeights)
unsigned	nComponents () const
const AbsDistributionND &	getComponent (const unsigned n) const
double	getWeight (unsigned n) const
virtual double	density (const double *x, unsigned dim) const
virtual void	unitMap (const double *rnd, unsigned bufLen, double *x) const
virtual bool	mappedByQuantiles () const
virtual unsigned	random (AbsRandomGenerator &g, double *x, unsigned lenX) const
virtual gs::ClassId	classId () const
virtual bool	write (std::ostream &) const
Public Member Functions inherited from npstat::AbsDistributionND
	AbsDistributionND (const unsigned dim)
	AbsDistributionND (const AbsDistributionND &r)
AbsDistributionND &	operator= (const AbsDistributionND &r)
bool	operator== (const AbsDistributionND &r) const
bool	operator!= (const AbsDistributionND &r) const
unsigned	dim () const

Static Public Member Functions
static const char *	classname ()
static unsigned	version ()
static DistributionMixND *	read (const gs::ClassId &id, std::istream &)
Static Public Member Functions inherited from npstat::AbsDistributionND
static const char *	classname ()
static unsigned	version ()
static AbsDistributionND *	read (const gs::ClassId &id, std::istream &)

Protected Member Functions
virtual bool	isEqual (const AbsDistributionND &) const

Additional Inherited Members
Protected Attributes inherited from npstat::AbsDistributionND
const unsigned	dim_

Member Function Documentation

add()

DistributionMixND& npstat::DistributionMixND::add	(	const AbsDistributionND &	distro,
		double	weight
	)

Add a component to the mixture. Weight must be positive. All weights will be normalized internally so that their sum is 1.

classId()

virtual gs::ClassId npstat::DistributionMixND::classId ( ) const

inlinevirtual

Prototype needed for I/O

Implements npstat::AbsDistributionND.

clone()

virtual DistributionMixND* npstat::DistributionMixND::clone ( ) const

inlinevirtual

"Virtual copy constructor"

Implements npstat::AbsDistributionND.

density()

virtual double npstat::DistributionMixND::density ( const double *  x, unsigned  dim  ) const

virtual

Probability density

Implements npstat::AbsDistributionND.

getComponent()

const AbsDistributionND& npstat::DistributionMixND::getComponent ( const unsigned  n ) const

inline

Get the mixture component with the given number

getWeight()

double npstat::DistributionMixND::getWeight

(

unsigned

n

)

const

Get the component weight

mappedByQuantiles()

virtual bool npstat::DistributionMixND::mappedByQuantiles ( ) const

inlinevirtual

The following method should return "true" in case the "unitMap" method is implemented by a sequence of conditional quantile functions. Distributions with such maps permit quantile-based interpolation procedures.

Implements npstat::AbsDistributionND.

nComponents()

unsigned npstat::DistributionMixND::nComponents ( ) const

inline

Number of mixture components

random()

virtual unsigned npstat::DistributionMixND::random ( AbsRandomGenerator &  g, double *  x, unsigned  lenX  ) const

virtual

Random number generator according to the given distribution. Should return the number of random points used up from the generator. Length of the provided buffer "x" should be equal to the function dimensionality.

Reimplemented from npstat::AbsDistributionND.

setWeights()

void npstat::DistributionMixND::setWeights	(	const double *	weights,
		unsigned	nWeights
	)

Set all weights. Number of weights provided should be equal to the number of components. Weights will be normalized internally.

unitMap()

virtual void npstat::DistributionMixND::unitMap ( const double *  rnd, unsigned  bufLen, double *  x  ) const

virtual

Mapping from the unit hypercube into the density support region. Note that "bufLen" does not have to be equal to the dimensionality of the function. There may be an efficient way to generate just the leading dimensions in case "bufLen" is smaller than the dimensionality.

Implements npstat::AbsDistributionND.

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

• stat/DistributionMixND.hh