Estimating a distribution in a smooth fashion. More...

Public Member Functions
	Smoother (const regression::Kernel &, double width, const std::vector< double > &values)

	Smoother (const regression::Kernel &kernel, double width, double xmin, double xmax, size_t n)

void	add (double x, double weight=1.0)
	Add a data point.

const std::vector< double > &	density (void) const
	estimated values

void	rescale (double factor)

void	reset (void)
	reset density to zero

const std::vector< double > &	value (void) const
	values in which distribution is estimated

Related Functions
(Note that these are not member functions.)
template<typename Iterator >
void	add (Smoother &h, Iterator first, Iterator last)

std::ostream &	operator<< (std::ostream &s, const Smoother &)

Detailed Description

Estimating a distribution in a smooth fashion.

Constructor & Destructor Documentation

theplu::yat::statistics::Smoother::Smoother	(	const regression::Kernel &	,
		double	width,
		const std::vector< double > &	values
	)

Constructor taking vector describing for which values distribution should be estimated.

theplu::yat::statistics::Smoother::Smoother	(	const regression::Kernel &	kernel,
		double	width,
		double	xmin,
		double	xmax,
		size_t	n
	)

Constructor creating observation points equally distributed between xmin and xmax.

Parameters

kernel	doing the smoothing
width
xmin	smallest observation point
xmax	largest observation point
n	number of observation points

void theplu::yat::statistics::Smoother::rescale ( double factor )

multiply each value with factor

template<typename Iterator >

Type Requirements:

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