#include <CensoredQuantileRegression.hh>

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

Public Member Functions
	CensoredQuantileRegressionOnKDTree (const KDTree< Point, Numeric > &dataTree, const Functor1< double, Point > &regressedValue, const Functor1< CensoringInfo, Point > &censoringInfo, const QuadraticOrthoPolyND &poly, double quantile, double valueLimit)

virtual void	process (const Point &value)

Public Member Functions inherited from npstat::QuantileRegressionOnKDTree< Point, Numeric >
	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 ()

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)

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

Protected Attributes inherited from npstat::QuantileRegressionOnKDTree< Point, Numeric >
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_

Detailed Description

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

Class that facilitates censored quantile regression on data samples arranged into a k-d tree structure

Constructor & Destructor Documentation

◆ CensoredQuantileRegressionOnKDTree()

template<class Point , class Numeric >

npstat::CensoredQuantileRegressionOnKDTree< Point, Numeric >::CensoredQuantileRegressionOnKDTree	(	const KDTree< Point, Numeric > &	dataTree,
		const Functor1< double, Point > &	regressedValue,
		const Functor1< CensoringInfo, Point > &	censoringInfo,
		const QuadraticOrthoPolyND &	poly,
		double	quantile,
		double	valueLimit
	)

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.

censoringInfo – a functor that provides information about censoring for the goven point.

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

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

The "valueLimit" parameter plays the role of a far-away point which for sure lies below all uncut response values if the cut was response > cutoff or above all uncut values if the cut was response < cutoff. This limit should not be chosen extremely far away from the realistically possible response values because such a limit will contribute too much to the loss function and the loss value calculation will suffer excessively from round-off errors.

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

Member Function Documentation

◆ process()

template<class Point , class Numeric >

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

virtual

Method from AbsVisitor that we have to implement

Reimplemented from npstat::QuantileRegressionOnKDTree< Point, Numeric >.

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

stat/CensoredQuantileRegression.hh

Public Member Functions