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• ImsInformed
• Statistics
• FitLine

C# 클래스 ImsInformed.Statistics.FitLine

파일 보기 프로젝트 열기: PNNL-Comp-Mass-Spec/IMS-Informed-Library 1 사용 예제들

공개 메소드들

메소드	설명
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

보호된 메소드들

메소드	설명
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

비공개 메소드들

메소드	설명
CalculatedRSquaredVanilla ( ) : double

메소드 상세