Definition at line 23 of file TRobustEstimator.h.

Public Member Functions
	TRobustEstimator ()
	this constructor should be used in a univariate case: first call this constructor, then - the EvaluateUni(..) function More...

	TRobustEstimator (Int_t nvectors, Int_t nvariables, Int_t hh=0)
	constructor More...

virtual	~TRobustEstimator ()

void	AddColumn (Double_t *col)
	adds a column to the data matrix it is assumed that the column has size fN variable fVarTemp keeps the number of columns l already added More...

void	AddRow (Double_t *row)
	adds a vector to the data matrix it is supposed that the vector is of size fNvar More...

void	Evaluate ()
	Finds the estimate of multivariate mean and variance. More...

void	EvaluateUni (Int_t nvectors, Double_t *data, Double_t &mean, Double_t &sigma, Int_t hh=0)
	for the univariate case estimates of location and scatter are returned in mean and sigma parameters the algorithm works on the same principle as in multivariate case - it finds a subset of size hh with smallest sigma, and then returns mean and sigma of this subset More...

Int_t	GetBDPoint ()
	returns the breakdown point of the algorithm More...

void	GetCovariance (TMatrixDSym &matr)
	returns the covariance matrix More...

const TMatrixDSym *	GetCovariance () const

void	GetCorrelation (TMatrixDSym &matr)
	returns the correlation matrix More...

const TMatrixDSym *	GetCorrelation () const

void	GetHyperplane (TVectorD &vec)
	if the points are on a hyperplane, returns this hyperplane More...

const TVectorD *	GetHyperplane () const
	if the points are on a hyperplane, returns this hyperplane More...

Int_t	GetNHyp ()

void	GetMean (TVectorD &means)
	return the estimate of the mean More...

const TVectorD *	GetMean () const

void	GetRDistances (TVectorD &rdist)
	returns the robust distances (helps to find outliers) More...

const TVectorD *	GetRDistances () const

Int_t	GetNumberObservations () const

Int_t	GetNvar () const

const TArrayI *	GetOuliers () const

Int_t	GetNOut ()
	returns the number of outliers More...

Double_t	GetChiQuant (Int_t i) const
	returns the chi2 quantiles More...

Public Member Functions inherited from TObject
	TObject ()

	TObject (const TObject &object)
	TObject copy ctor. More...

TObject &	operator= (const TObject &rhs)
	TObject assignment operator. More...

virtual	~TObject ()
	TObject destructor. More...

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad. More...

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action. More...

virtual const char *	ClassName () const
	Returns name of class to which the object belongs. More...

virtual void	Clear (Option_t *="")

virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility. More...

virtual Int_t	Compare (const TObject *obj) const
	Compare abstract method. More...

virtual void	Copy (TObject &object) const
	Copy this to obj. More...

virtual void	Delete (Option_t *option="")
	Delete this object. More...

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object. More...

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects. More...

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs. More...

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current pad. More...

virtual void	Dump () const
	Dump contents of object on stdout. More...

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g. More...

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray. More...

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py). More...

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes. More...

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes. More...

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object. More...

virtual UInt_t	GetUniqueID () const
	Return the unique object id. More...

virtual const char *	GetName () const
	Returns name of object. More...

virtual const char *	GetIconName () const
	Returns mime type name of object. More...

virtual Option_t *	GetOption () const

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py). More...

virtual const char *	GetTitle () const
	Returns title of object. More...

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out. More...

virtual ULong_t	Hash () const
	Return hash value for this object. More...

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname". More...

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl. More...

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas. More...

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory). More...

virtual Bool_t	IsSortable () const

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification. More...

virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout. More...

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself. More...

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list. More...

virtual void	Print (Option_t *option="") const
	This method must be overridden when a class wants to print itself. More...

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory. More...

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list. More...

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename. More...

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out". More...

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object. More...

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id. More...

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory. More...

void *	operator new (size_t sz)

void *	operator new[] (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz, void *vp)

void	operator delete (void *ptr)
	Operator delete. More...

void	operator delete[] (void *ptr)
	Operator delete []. More...

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f. More...

void	SetBit (UInt_t f)

void	ResetBit (UInt_t f)

Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

void	InvertBit (UInt_t f)

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message. More...

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message. More...

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message. More...

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message. More...

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message. More...

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete. More...

Protected Member Functions
void	AddToSscp (TMatrixD &sscp, TVectorD &vec)
	update the sscp matrix with vector vec More...

void	ClearSscp (TMatrixD &sscp)
	clear the sscp matrix, used for covariance and mean calculation More...

void	Classic ()
	called when h=n. More...

void	Covar (TMatrixD &sscp, TVectorD &m, TMatrixDSym &cov, TVectorD &sd, Int_t nvec)
	calculates mean and covariance More...

void	Correl ()
	transforms covariance matrix into correlation matrix More...

void	CreateSubset (Int_t ntotal, Int_t htotal, Int_t p, Int_t index, TMatrixD &data, TMatrixD &sscp, Double_t ndist)
	creates a subset of htotal elements from ntotal elements first, p+1 elements are drawn randomly(without repetitions) if their covariance matrix is singular, more elements are added one by one, until their covariance matrix becomes regular or it becomes clear that htotal observations lie on a hyperplane If covariance matrix determinant!=0, distances of all ntotal elements are calculated, using formula d_i=Sqrt((x_i-M)S_inv(x_i-M)), where M is mean and S_inv is the inverse of the covariance matrix htotal points with smallest distances are included in the returned subset. More...

void	CreateOrtSubset (TMatrixD &dat, Int_t index, Int_t hmerged, Int_t nmerged, TMatrixD &sscp, Double_t ndist)
	creates a subset of hmerged vectors with smallest orthogonal distances to the hyperplane hyp[1](x1-mean[1])+...+hyp[nvar](xnvar-mean[nvar])=0 This function is called in case when less than fH samples lie on a hyperplane. More...

Double_t	CStep (Int_t ntotal, Int_t htotal, Int_t index, TMatrixD &data, TMatrixD &sscp, Double_t ndist)
	from the input htotal-subset constructs another htotal subset with lower determinant More...

Int_t	Exact (Double_t *ndist)
	for the exact fit situaions returns number of observations on the hyperplane More...

Int_t	Exact2 (TMatrixD &mstockbig, TMatrixD &cstockbig, TMatrixD &hyperplane, Double_t deti, Int_t nbest, Int_t kgroup, TMatrixD &sscp, Double_t ndist)
	This function is called if determinant of the covariance matrix of a subset=0. More...

Int_t	Partition (Int_t nmini, Int_t *indsubdat)
	divides the elements into approximately equal subgroups number of elements in each subgroup is stored in indsubdat number of subgroups is returned More...

Int_t	RDist (TMatrixD &sscp)
	Calculates robust distances.Then the samples with robust distances greater than a cutoff value (0.975 quantile of chi2 distribution with fNvar degrees of freedom, multiplied by a correction factor), are given weiht=0, and new, reweighted estimates of location and scatter are calculated The function returns the number of outliers. More...

void	RDraw (Int_t subdat, Int_t ngroup, Int_t indsubdat)
	Draws ngroup nonoverlapping subdatasets out of a dataset of size n such that the selected case numbers are uniformly distributed from 1 to n. More...

Double_t	KOrdStat (Int_t ntotal, Double_t arr, Int_t k, Int_t work)
	because I need an Int_t work array More...

Protected Member Functions inherited from TObject
void	MakeZombie ()

virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected). More...

Protected Attributes
Int_t	fNvar

Int_t	fH

Int_t	fN

Int_t	fVarTemp

Int_t	fVecTemp

Int_t	fExact

TVectorD	fMean

TMatrixDSym	fCovariance

TMatrixDSym	fInvcovariance

TMatrixDSym	fCorrelation

TVectorD	fRd

TVectorD	fSd

TArrayI	fOut

TVectorD	fHyperplane

TMatrixD	fData

Additional Inherited Members
Public Types inherited from TObject
enum	EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) }

enum	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }

Static Public Member Functions inherited from TObject
static Long_t	GetDtorOnly ()
	Return destructor only flag. More...

static void	SetDtorOnly (void *obj)
	Set destructor only flag. More...

static Bool_t	GetObjectStat ()
	Get status of object stat flag. More...

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable. More...

#include <TRobustEstimator.h>

Inheritance diagram for TRobustEstimator:

[legend]

Constructor & Destructor Documentation

TRobustEstimator::TRobustEstimator ( )

this constructor should be used in a univariate case: first call this constructor, then - the EvaluateUni(..) function

Definition at line 130 of file TRobustEstimator.cxx.

TRobustEstimator::TRobustEstimator	(	Int_t	nvectors,
		Int_t	nvariables,
		Int_t	hh = `0`
	)

constructor

Definition at line 136 of file TRobustEstimator.cxx.

virtual TRobustEstimator::~TRobustEstimator ( )

inlinevirtual

Definition at line 78 of file TRobustEstimator.h.

Member Function Documentation

void TRobustEstimator::AddColumn ( Double_t * col )

adds a column to the data matrix it is assumed that the column has size fN variable fVarTemp keeps the number of columns l already added

Definition at line 176 of file TRobustEstimator.cxx.

void TRobustEstimator::AddRow ( Double_t * row )

adds a vector to the data matrix it is supposed that the vector is of size fNvar

Definition at line 197 of file TRobustEstimator.cxx.

void TRobustEstimator::AddToSscp	(	TMatrixD &	sscp,
		TVectorD &	vec
	)

protected

update the sscp matrix with vector vec

Definition at line 784 of file TRobustEstimator.cxx.

Referenced by Classic(), CreateOrtSubset(), CreateSubset(), CStep(), Evaluate(), Exact2(), and RDist().

void TRobustEstimator::Classic ( )

protected

called when h=n.

Returns classic covariance matrix and mean

Definition at line 814 of file TRobustEstimator.cxx.

Referenced by Evaluate().

void TRobustEstimator::ClearSscp ( TMatrixD & sscp )

protected

clear the sscp matrix, used for covariance and mean calculation

Definition at line 801 of file TRobustEstimator.cxx.

Referenced by Classic(), CreateOrtSubset(), CreateSubset(), CStep(), Evaluate(), Exact2(), and RDist().

void TRobustEstimator::Correl ( )

protected

transforms covariance matrix into correlation matrix

Definition at line 855 of file TRobustEstimator.cxx.

Referenced by Classic().

void TRobustEstimator::Covar	(	TMatrixD &	sscp,
		TVectorD &	m,
		TMatrixDSym &	cov,
		TVectorD &	sd,
		Int_t	nvec
	)

protected

calculates mean and covariance

Definition at line 832 of file TRobustEstimator.cxx.

Referenced by Classic(), CreateOrtSubset(), CreateSubset(), CStep(), Evaluate(), Exact2(), and RDist().

void TRobustEstimator::CreateOrtSubset	(	TMatrixD &	dat,
		Int_t *	index,
		Int_t	hmerged,
		Int_t	nmerged,
		TMatrixD &	sscp,
		Double_t *	ndist
	)

protected

creates a subset of hmerged vectors with smallest orthogonal distances to the hyperplane hyp[1]*(x1-mean[1])+...+hyp[nvar]*(xnvar-mean[nvar])=0 This function is called in case when less than fH samples lie on a hyperplane.

Definition at line 973 of file TRobustEstimator.cxx.

Referenced by Evaluate().

void TRobustEstimator::CreateSubset	(	Int_t	ntotal,
		Int_t	htotal,
		Int_t	p,
		Int_t *	index,
		TMatrixD &	data,
		TMatrixD &	sscp,
		Double_t *	ndist
	)

protected

creates a subset of htotal elements from ntotal elements first, p+1 elements are drawn randomly(without repetitions) if their covariance matrix is singular, more elements are added one by one, until their covariance matrix becomes regular or it becomes clear that htotal observations lie on a hyperplane If covariance matrix determinant!=0, distances of all ntotal elements are calculated, using formula d_i=Sqrt((x_i-M)*S_inv*(x_i-M)), where M is mean and S_inv is the inverse of the covariance matrix htotal points with smallest distances are included in the returned subset.

Definition at line 883 of file TRobustEstimator.cxx.

Referenced by Evaluate().

Double_t TRobustEstimator::CStep	(	Int_t	ntotal,
		Int_t	htotal,
		Int_t *	index,
		TMatrixD &	data,
		TMatrixD &	sscp,
		Double_t *	ndist
	)

protected

from the input htotal-subset constructs another htotal subset with lower determinant

As proven by Peter J.Rousseeuw and Katrien Van Driessen, if distances for all elements are calculated, using the formula:d_i=Sqrt((x_i-M)*S_inv*(x_i-M)), where M is the mean of the input htotal-subset, and S_inv - the inverse of its covariance matrix, then htotal elements with smallest distances will have covariance matrix with determinant less or equal to the determinant of the input subset covariance matrix.

determinant for this htotal-subset with smallest distances is returned

Definition at line 1005 of file TRobustEstimator.cxx.

Referenced by Evaluate().

void TRobustEstimator::Evaluate ( )

Finds the estimate of multivariate mean and variance.

Definition at line 214 of file TRobustEstimator.cxx.

void TRobustEstimator::EvaluateUni	(	Int_t	nvectors,
		Double_t *	data,
		Double_t &	mean,
		Double_t &	sigma,
		Int_t	hh = `0`
	)

for the univariate case estimates of location and scatter are returned in mean and sigma parameters the algorithm works on the same principle as in multivariate case - it finds a subset of size hh with smallest sigma, and then returns mean and sigma of this subset

Definition at line 614 of file TRobustEstimator.cxx.

Int_t TRobustEstimator::Exact ( Double_t * ndist )

protected

for the exact fit situaions returns number of observations on the hyperplane

Definition at line 1042 of file TRobustEstimator.cxx.

Referenced by Evaluate(), and Exact2().

Int_t TRobustEstimator::Exact2	(	TMatrixD &	mstockbig,
		TMatrixD &	cstockbig,
		TMatrixD &	hyperplane,
		Double_t *	deti,
		Int_t	nbest,
		Int_t	kgroup,
		TMatrixD &	sscp,
		Double_t *	ndist
	)

protected

This function is called if determinant of the covariance matrix of a subset=0.

If there are more then fH vectors on a hyperplane, returns this hyperplane and stops else stores the hyperplane coordinates in hyperplane matrix

Definition at line 1077 of file TRobustEstimator.cxx.

Referenced by Evaluate().

Int_t TRobustEstimator::GetBDPoint ( )

returns the breakdown point of the algorithm

Definition at line 680 of file TRobustEstimator.cxx.

Double_t TRobustEstimator::GetChiQuant ( Int_t i ) const

returns the chi2 quantiles

Definition at line 690 of file TRobustEstimator.cxx.

void TRobustEstimator::GetCorrelation ( TMatrixDSym & matr )

returns the correlation matrix

Definition at line 711 of file TRobustEstimator.cxx.

const TMatrixDSym* TRobustEstimator::GetCorrelation ( ) const

inline

Definition at line 91 of file TRobustEstimator.h.

void TRobustEstimator::GetCovariance ( TMatrixDSym & matr )

returns the covariance matrix

Definition at line 699 of file TRobustEstimator.cxx.

const TMatrixDSym* TRobustEstimator::GetCovariance ( ) const

inline

Definition at line 89 of file TRobustEstimator.h.

void TRobustEstimator::GetHyperplane ( TVectorD & vec )

if the points are on a hyperplane, returns this hyperplane

Definition at line 736 of file TRobustEstimator.cxx.

const TVectorD * TRobustEstimator::GetHyperplane ( ) const

if the points are on a hyperplane, returns this hyperplane

Definition at line 723 of file TRobustEstimator.cxx.

void TRobustEstimator::GetMean ( TVectorD & means )

return the estimate of the mean

Definition at line 752 of file TRobustEstimator.cxx.

const TVectorD* TRobustEstimator::GetMean ( ) const

inline

Definition at line 96 of file TRobustEstimator.h.

Int_t TRobustEstimator::GetNHyp ( )

inline

Definition at line 94 of file TRobustEstimator.h.

Int_t TRobustEstimator::GetNOut ( )

returns the number of outliers

Definition at line 776 of file TRobustEstimator.cxx.

Int_t TRobustEstimator::GetNumberObservations ( ) const

inline

Definition at line 99 of file TRobustEstimator.h.

Int_t TRobustEstimator::GetNvar ( ) const

inline

Definition at line 100 of file TRobustEstimator.h.

const TArrayI* TRobustEstimator::GetOuliers ( ) const

inline

Definition at line 101 of file TRobustEstimator.h.

void TRobustEstimator::GetRDistances ( TVectorD & rdist )

returns the robust distances (helps to find outliers)

Definition at line 764 of file TRobustEstimator.cxx.

const TVectorD* TRobustEstimator::GetRDistances ( ) const

inline

Definition at line 98 of file TRobustEstimator.h.

Double_t TRobustEstimator::KOrdStat	(	Int_t	ntotal,
		Double_t *	arr,
		Int_t	k,
		Int_t *	work
	)

protected

because I need an Int_t work array

Definition at line 1273 of file TRobustEstimator.cxx.

Referenced by CreateOrtSubset(), CreateSubset(), and CStep().

Int_t TRobustEstimator::Partition	(	Int_t	nmini,
		Int_t *	indsubdat
	)

protected

divides the elements into approximately equal subgroups number of elements in each subgroup is stored in indsubdat number of subgroups is returned

Definition at line 1124 of file TRobustEstimator.cxx.

Referenced by Evaluate().

Int_t TRobustEstimator::RDist ( TMatrixD & sscp )

protected

Calculates robust distances.Then the samples with robust distances greater than a cutoff value (0.975 quantile of chi2 distribution with fNvar degrees of freedom, multiplied by a correction factor), are given weiht=0, and new, reweighted estimates of location and scatter are calculated The function returns the number of outliers.

Definition at line 1178 of file TRobustEstimator.cxx.

Referenced by Evaluate().