Uses of Class
com.irurueta.numerical.robust.RobustEstimator

Packages that use RobustEstimator

Package	Description
com.irurueta.numerical.robust	This package contains robust estimators that can be used to discard outliers for cases where a model of the data is known (i.e.

Uses of RobustEstimator in com.irurueta.numerical.robust

Subclasses of RobustEstimator in com.irurueta.numerical.robust

Modifier and Type	Class	Description
class	LMedSRobustEstimator<T>	This class implements LMedS (Least Median of Squares) algorithm to robustly estimate a data model.
class	MSACRobustEstimator<T>	This class implements MSAC (Median SAmple Consensus) algorithm to robustly estimate a data model.
class	PROMedSRobustEstimator<T>	This class implements PROMedS (PROgressive least Median Sample) algorithm to robustly estimate a data model.
class	PROSACRobustEstimator<T>	This class implements PROSAC (PROgressive random SAmple Consensus) algorithm to robustly estimate a data model.
class	RANSACRobustEstimator<T>	This class implements RANSAC (RANdom SAmple Consensus) algorithm to robustly estimate a data model.

Methods in com.irurueta.numerical.robust with parameters of type RobustEstimator

Modifier and Type	Method	Description
void	RobustEstimatorListener.onEstimateEnd(RobustEstimator<T> estimator)	Called when estimation ends.
void	RobustEstimatorListener.onEstimateNextIteration(RobustEstimator<T> estimator, int iteration)	Called when estimator iterates to refine a possible solution.
void	RobustEstimatorListener.onEstimateProgressChange(RobustEstimator<T> estimator, float progress)	Called when estimation progress changes significantly.
void	RobustEstimatorListener.onEstimateStart(RobustEstimator<T> estimator)	Called when estimation starts.