npstat::QuantileRegressionOnKDTree< Point, Numeric > Class Template Reference

#include <LocalQuantileRegression.hh>

Inheritance diagram for npstat::QuantileRegressionOnKDTree< Point, Numeric >:

Public Member Functions
	QuantileRegressionOnKDTree (const KDTree< Point, Numeric > &dataTree, const Functor1< double, Point > &regressedValue, const QuadraticOrthoPolyND &poly, double quantile)
const KDTree< Point, Numeric > &	getDataTree () const
virtual void	clear ()
virtual double	result ()
virtual void	process (const Point &value)
Public Member Functions inherited from npstat::QuantileRegressionBase< Numeric >
	QuantileRegressionBase (const QuadraticOrthoPolyND &poly, double quantile)
unsigned	dim () const
double	quantile () const
const QuadraticOrthoPolyND &	getPoly () const
const std::vector< double > &	lastCoeffs () const
void	setRegressionBox (const BoxND< Numeric > &box)
void	setLinearMapping (const double *location, const double *scale, unsigned locationAndScaleArraySize)
void	empiricalC0 (double *c0, double *c0Uncertainty, double *npoints)
double	linearLoss (const double *coeffs, unsigned nCoeffs)

Protected Attributes
const KDTree< Point, Numeric > &	dataTree_
const Functor1< double, Point > &	regressedValue_
Protected Attributes inherited from npstat::QuantileRegressionBase< Numeric >
const QuadraticOrthoPolyND &	poly_
BoxND< Numeric >	regressionBox_
std::vector< double >	location_
std::vector< double >	scale_
std::vector< double >	coords_
std::vector< double >	coeffs_
long double	loss_
const double	quantile_
const double	onemq_
const unsigned	mydim_

Additional Inherited Members
Protected Member Functions inherited from npstat::QuantileRegressionBase< Numeric >
void	resetAccumulators ()

Detailed Description

template<class Point, class Numeric>
class npstat::QuantileRegressionOnKDTree< Point, Numeric >

Quantile regression on data samples arranged into k-d trees

Constructor & Destructor Documentation

QuantileRegressionOnKDTree()

template<class Point , class Numeric >

npstat::QuantileRegressionOnKDTree< Point, Numeric >::QuantileRegressionOnKDTree	(	const KDTree< Point, Numeric > &	dataTree,
		const Functor1< double, Point > &	regressedValue,
		const QuadraticOrthoPolyND &	poly,
		double	quantile
	)

Constructor arguments are as follows:

dataTree – the tree of data points.

regressedValue – a functor that provides the observed value for the given input point. Typically, this value will be just one of the Point coordinates not used in k-d tree construction.

poly – the set of orthogonal polynomials used to construct the local regression surface.

quantile – the target quantile (between 0.0 and 1.0).

This object will not own "dataTree", "regressedValue", or "poly" objects. These objects must still exist when the QuantileRegressionOnKDTree object is in use.

Member Function Documentation

clear()

template<class Point , class Numeric >

virtual void npstat::QuantileRegressionOnKDTree< Point, Numeric >::clear ( )

inlinevirtual

Method from AbsVisitor that we have to implement

Implements npstat::AbsVisitor< Point, double >.

getDataTree()

template<class Point , class Numeric >

const KDTree<Point,Numeric>& npstat::QuantileRegressionOnKDTree< Point, Numeric >::getDataTree ( ) const

inline

Examine the data

process()

template<class Point , class Numeric >

virtual void npstat::QuantileRegressionOnKDTree< Point, Numeric >::process ( const Point &  value )

virtual

Process one array point

Implements npstat::AbsVisitor< Point, double >.

Reimplemented in npstat::CensoredQuantileRegressionOnKDTree< Point, Numeric >.

result()

template<class Point , class Numeric >

virtual double npstat::QuantileRegressionOnKDTree< Point, Numeric >::result ( )

inlinevirtual

Return the result at the end of array processing

Implements npstat::AbsVisitor< Point, double >.

---

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

• stat/LocalQuantileRegression.hh