C# Class ImsInformed.Statistics.FitLine

The fit FitLine.

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Méthodes publiques

Méthode	Description
AddPoint ( ContinuousXYPoint point ) : void
AddPoints ( IEnumerable points ) : void
DiagnoseRegression ( double>.Func weightFunc = null ) : void
FitLine ( ) : System	Initializes a new instance of the FitLine class.
FitLine ( IEnumerable initialPoints ) : System
ModelPredictX2Y ( double x ) : double	Return the predicted Y at given X
ModelPredictY2X ( double y ) : double	Return the predicted Y at given X
PerformRegression ( ) : void	Using current fits points stored in the fitline to initiate regression
PerformRegression ( IEnumerable xyPoints ) : void	Refit a group of points to the fit line.
RemoveOutlierWithHighestCookDistance ( int minFitPoints ) : int	The remove outlier with highest cook distance.
RemoveOutliersAboveThreshold ( double CooksDThreshold, int minFitPoints ) : int	The remove outliers above threshold.
RemovePoint ( ContinuousXYPoint point ) : void
ResetPoints ( IEnumerable points ) : void

Méthodes protégées

Méthode	Description
CalculateMSE ( ) : double
CalculateRSquared ( ) : double	Calculate R-square(Coefficient of determination)
ComputeResidual ( ContinuousXYPoint point ) : double	Compute the residual of a fit point.
CooksDistance ( ContinuousXYPoint point, double ssh, double meanX, int pointsCount, double &leverage ) : double	The cooks distance.
DiagnosePoints ( double>.Func weightFunc ) : void	Calculate Cook's distance for all points
LeastSquaresFitLinear ( IEnumerable xyPoints, double &gain, double &offset ) : void	Computes fit FitLine for potential voltage group and writes
LeastSquaresFitdLinear ( IEnumerable xyPoints ) : void	wrapper for updating gain and offset using LeastSquaresFitLinear

Private Methods

Méthode	Description
CalculatedRSquaredVanilla ( ) : double

Method Details

AddPoint() public méthode

public AddPoint ( ContinuousXYPoint point ) : void
point	ContinuousXYPoint
Résultat	void

AddPoints() public méthode

public AddPoints ( IEnumerable points ) : void
points	IEnumerable
Résultat	void

CalculateMSE() protected méthode

protected CalculateMSE ( ) : double
Résultat	double

CalculateRSquared() protected méthode

Calculate R-square(Coefficient of determination)

protected CalculateRSquared ( ) : double
Résultat	double

ComputeResidual() protected méthode

Compute the residual of a fit point.

///

protected ComputeResidual ( ContinuousXYPoint point ) : double
point	ContinuousXYPoint	/// The point. ///
Résultat	double

CooksDistance() protected méthode

The cooks distance.

protected CooksDistance ( ContinuousXYPoint point, double ssh, double meanX, int pointsCount, double &leverage ) : double
point	ContinuousXYPoint	/// The point. ///
ssh	double	/// The ssh. ///
meanX	double	/// The mean X. ///
pointsCount	int	/// The points count. ///
leverage	double
Résultat	double

DiagnosePoints() protected méthode

Calculate Cook's distance for all points

A delegate callback throws an exception.

protected DiagnosePoints ( double>.Func weightFunc ) : void
weightFunc	double>.Func
Résultat	void

DiagnoseRegression() public méthode

A delegate callback throws an exception.

public DiagnoseRegression ( double>.Func weightFunc = null ) : void
weightFunc	double>.Func
Résultat	void

FitLine() public méthode

Initializes a new instance of the FitLine class.

public FitLine ( ) : System
Résultat	System

FitLine() public méthode

public FitLine ( IEnumerable initialPoints ) : System
initialPoints	IEnumerable
Résultat	System

LeastSquaresFitLinear() protected abstract méthode

Computes fit FitLine for potential voltage group and writes

protected abstract LeastSquaresFitLinear ( IEnumerable xyPoints, double &gain, double &offset ) : void
xyPoints	IEnumerable	/// The xy points. ///
gain	double
offset	double
Résultat	void

LeastSquaresFitdLinear() protected méthode

wrapper for updating gain and offset using LeastSquaresFitLinear

protected LeastSquaresFitdLinear ( IEnumerable xyPoints ) : void
xyPoints	IEnumerable
Résultat	void

ModelPredictX2Y() public méthode

Return the predicted Y at given X

public ModelPredictX2Y ( double x ) : double
x	double	/// The X. ///
Résultat	double

ModelPredictY2X() public méthode

Return the predicted Y at given X

Cannot predict value with model, please run linear regression first.

public ModelPredictY2X ( double y ) : double
y	double
Résultat	double

PerformRegression() public méthode

Using current fits points stored in the fitline to initiate regression

public PerformRegression ( ) : void
Résultat	void

PerformRegression() public méthode

Refit a group of points to the fit line.

public PerformRegression ( IEnumerable xyPoints ) : void
xyPoints	IEnumerable	/// The xy points. ///
Résultat	void

RemoveOutlierWithHighestCookDistance() public méthode

The remove outlier with highest cook distance.

public RemoveOutlierWithHighestCookDistance ( int minFitPoints ) : int
minFitPoints	int
Résultat	int

RemoveOutliersAboveThreshold() public méthode

The remove outliers above threshold.

///

public RemoveOutliersAboveThreshold ( double CooksDThreshold, int minFitPoints ) : int
CooksDThreshold	double	/// The cooks d threshold. ///
minFitPoints	int	/// The min fit points. ///
Résultat	int

RemovePoint() public méthode

public RemovePoint ( ContinuousXYPoint point ) : void
point	ContinuousXYPoint
Résultat	void

ResetPoints() public méthode

public ResetPoints ( IEnumerable points ) : void
points	IEnumerable
Résultat	void