Class for taking care of mean and covariance of two variables in a weighted manner. More...

#include <yat/statistics/AveragerPairWeighted.h>

Public Member Functions
	AveragerPairWeighted (void)
	The default constructor.

void	add (const double x, const double y, const double wx, const double wy)

double	correlation (void) const
	Pearson correlation coefficient. More...

double	covariance (void) const

double	msd (void) const

double	n (void) const

void	reset (void)
	Reset everything to zero.

double	sum_w (void) const

double	sum_xy (void) const

double	sum_xy_centered (void) const

const AveragerWeighted &	x_averager (void) const

const AveragerWeighted &	y_averager (void) const

const AveragerPairWeighted &	operator+= (const AveragerPairWeighted &)
	Addition assignment operator. More...

Related Functions
(Note that these are not member functions.)
template<class InputIterator1 , class InputIterator2 >
void	add (AveragerPairWeighted &ap, InputIterator1 first1, InputIterator1 last1, InputIterator2 first2)
	adding a ranges of values to AveragerPairWeighted ap More...

template<typename InputIterator1 , typename InputIterator2 , typename InputIterator3 , typename InputIterator4 >
void	add (AveragerPairWeighted &ap, InputIterator1 x, InputIterator1 xlast, InputIterator2 y, InputIterator3 wx, InputIterator4 wy)
	adding four ranges of values to AveragerPairWeighted ap More...

Detailed Description

Class for taking care of mean and covariance of two variables in a weighted manner.

See Also: Weighted Statistics

If nothing else stated, each function fulfills the following:

Setting a weight to zero corresponds to removing the data point from the dataset.
Setting all weights to unity, the yields the same result as from corresponding function in AveragerPair.
Rescaling weights does not change the performance of the object.

See Also: Averager AveragerWeighted AveragerPair

Member Function Documentation

void theplu::yat::statistics::AveragerPairWeighted::add	(	const double	x,
		const double	y,
		const double	wx,
		const double	wy
	)

Adding a pair of data points with value x and y, and their weights. If either of the weights are zero the addition is ignored

double theplu::yat::statistics::AveragerPairWeighted::correlation ( void ) const

Pearson correlation coefficient.

Returns: $\frac{\sum w_xw_y (x-m_x)(y-m_y)}{\sqrt{\sum w_xw_y (y-m_y)^2\sum w_xw_y (y-m_y)^2}}$ where m is calculated as $m_x = \frac {\sum w_xw_yx}{\sum w}$

double theplu::yat::statistics::AveragerPairWeighted::covariance ( void ) const

$\frac{\sum w_xw_y (x-m_x)(y-m_y)}{\sum w_xw_y}$ where m is calculated as $m_x = \frac {\sum w_xw_yx}{\sum w}$

double theplu::yat::statistics::AveragerPairWeighted::msd ( void ) const

Returns: $\frac{\sum w_xw_y(x-y)^2}{\sum w_xw_y}$

double theplu::yat::statistics::AveragerPairWeighted::n ( void ) const

Returns: $\frac{\left(\sum w_x w_y\right)^2}{\sum w_x^2w_y^2}$

const AveragerPairWeighted& theplu::yat::statistics::AveragerPairWeighted::operator+= ( const AveragerPairWeighted & )

Addition assignment operator.

Returns: resulting AveragerPairWeighted

Since: New in yat 0.8

double theplu::yat::statistics::AveragerPairWeighted::sum_w ( void ) const

Returns: $\sum w_xw_y$

double theplu::yat::statistics::AveragerPairWeighted::sum_xy ( void ) const

Returns: $\sum w_xw_yxy$

double theplu::yat::statistics::AveragerPairWeighted::sum_xy_centered ( void ) const

Returns: $\sum w_xw_y (x-m_x)(y-m_y)$ where m is calculated as $m_x = \frac {\sum w_xw_yx}{\sum w}$

const AveragerWeighted& theplu::yat::statistics::AveragerPairWeighted::x_averager ( void ) const

Note: the weights are calculated as

Returns: AveragerWeighted for x

const AveragerWeighted& theplu::yat::statistics::AveragerPairWeighted::y_averager ( void ) const

Note: the weights are calculated as

Returns: AveragerWeighted for y

Friends And Related Function Documentation

template<class InputIterator1 , class InputIterator2 >

void add	(	AveragerPairWeighted &	ap,
		InputIterator1	first1,
		InputIterator1	last1,
		InputIterator2	first2
	)

Type Requirement:

InputIterator1 models Data Iterator
InputIterator1 is Single Pass Iterator
InputIterator2 models Data Iterator
InputIterator2 is Single Pass Iterator

template<typename InputIterator1 , typename InputIterator2 , typename InputIterator3 , typename InputIterator4 >

void add	(	AveragerPairWeighted &	ap,
		InputIterator1	x,
		InputIterator1	xlast,
		InputIterator2	y,
		InputIterator3	wx,
		InputIterator4	wy
	)

Iterators must be unweighted.

Type Requirement:

InputIterator1 models Single Pass Iterator
InputIterator1 models Readable Iterator
InputIterator1 is weighted
InputIterator2 models Single Pass Iterator
InputIterator2 models Readable Iterator
InputIterator2 is weighted
InputIterator3 models Single Pass Iterator
InputIterator3 models Readable Iterator
InputIterator3 is weighted
InputIterator4 models Single Pass Iterator
InputIterator4 models Readable Iterator
InputIterator4 is weighted

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

yat/statistics/AveragerPairWeighted.h

Public Member Functions

Related Functions

Detailed Description

Member Function Documentation

Friends And Related Function Documentation