Statistics Class Reference

#include <Statistics.h>

List of all members.

Public Member Functions
	Statistics ()
	~Statistics ()
Static Public Member Functions
Double_t	MAXIT ()
Double_t	EPS ()
Double_t	EPS1 ()
Double_t	EPS2 ()
Double_t	FPMIN ()
Double_t	Max (Double_t val1, Double_t val2)
Double_t	Max (vector< Double_t > vector)
Double_t	Min (Double_t val1, Double_t val2)
Double_t	Min (vector< Double_t > vector)
Double_t	Mean (vector< Double_t > vector)
	Calculates the mean value of a vector.
Double_t	Average (vector< Double_t > vector)
	Calculates the mean value of a vector.
Double_t	Variance (vector< Double_t > vector)
	Calculates the what we usually call variance of a vector: biased-corrected variance.
Double_t	BiasedVariance (vector< Double_t > vector)
	Calculates the variance of a vector.
Double_t	UnbiasedVariance (vector< Double_t > vector)
	Calculates the unbiased variance of a vector.
Double_t	Covariance (vector< Double_t > v1, vector< Double_t > v2)
Double_t	StandardDeviation (vector< Double_t > vector)
	Calculates the what we usually call variance of a vector: biased-corrected variance.
Double_t	BiasedStandardDeviation (vector< Double_t > vector)
Double_t	UnbiasedStandardDeviation (vector< Double_t > vector)
Double_t	RMS (vector< Double_t > vector)
map< string, Double_t >	ChiSquareTest (vector< Double_t > v1, vector< Double_t > v2, int nbins)
map< string, Double_t >	KSTest (vector< Double_t > v1, vector< Double_t > v2)
map< string, Double_t >	BinnedKSTest (vector< Double_t > v1, vector< Double_t > v2, int nbins)
map< string, Double_t >	BinnedKSTestRoot (vector< Double_t > v1, vector< Double_t > v2, int nbins)
vector< Double_t >	SortBubble (vector< Double_t > vector)
vector< int >	GetSortedIndex (vector< Double_t > vector)
Double_t	CalculateKSProbability (Double_t alam)
Double_t	Entropy (vector< Double_t > vector)
Double_t	MutualEntropy (vector< Double_t > vector1, vector< Double_t > vector2)
	Calculates H(X|Y), where X=vector1 and Y=vector2.
map< string, Double_t >	FTest (vector< Double_t > vector1, vector< Double_t > vector2)
map< string, Double_t >	TTestForEqualVariances (vector< Double_t > vector1, vector< Double_t > vector2)
map< string, Double_t >	TTestForUnequalVariances (vector< Double_t > vector1, vector< Double_t > vector2)
Double_t	IncompleteBetaFunction (Double_t a, Double_t b, Double_t x)
Double_t	IncompleteBetaFunctionContinuedFraction (Double_t a, Double_t b, Double_t x)
	Evaluates continued fraction for incomplete beta function by modified Lentz's method (Numerical Recipes in C, chapter 6.4).
Double_t	IncompleteGammaFunctionQ (Double_t a, Double_t x)
	Returns the incomplete gamma function Q(a,x)=1-P(aa,x) (Numerical Recipes in C, chapter 6.2).
Double_t	IncompleteGammaFunctionQContinuedFraction (Double_t a, Double_t x)
	Returns the incomplete gamma function Q(a,x) evaluated by its continued fraction representation (Numerical Recipes in C, chapter 6.2).
Double_t	IncompleteGammaFunctionPSeries (Double_t a, Double_t x)
	Returns the incomplete gamma function P(a,x) evaluated by its series representation (Numerical Recipes in C, chapter 6.2).
Double_t	LogOfGammaFunction (Double_t x)
	Returns the value of ln[Gamma(x)] for x>0 (Numerical Recipes in C, chapter 6.1).
Double_t	Correlation (vector< Double_t > cv1, vector< Double_t > cv2)
	Calculates correlation coefficient between two vectors.
Double_t	RandomPoisson (Double_t *x, Double_t *par)

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Constructor & Destructor Documentation

Statistics::Statistics (   )

Statistics::~Statistics (   )

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Member Function Documentation

Double_t Statistics::Average (  vector< Double_t >  vector  )  [static]

Calculates the mean value of a vector.

Double_t Statistics::BiasedStandardDeviation (  vector< Double_t >  vector  )  [static]

Double_t Statistics::BiasedVariance (  vector< Double_t >  vector  )  [static]

Calculates the variance of a vector.

map< string, Double_t > Statistics::BinnedKSTest (  vector< Double_t >  v1, vector< Double_t >  v2, int  nbins )  [static]

map< string, Double_t > Statistics::BinnedKSTestRoot (  vector< Double_t >  v1, vector< Double_t >  v2, int  nbins )  [static]

Double_t Statistics::CalculateKSProbability (  Double_t  alam  )  [static]

map< string, Double_t > Statistics::ChiSquareTest (  vector< Double_t >  v1, vector< Double_t >  v2, int  nbins )  [static]

Double_t Statistics::Correlation (  vector< Double_t >  cv1, vector< Double_t >  cv2 )  [static]

Calculates correlation coefficient between two vectors.

Double_t Statistics::Covariance (  vector< Double_t >  v1, vector< Double_t >  v2 )  [static]

Double_t Statistics::Entropy (  vector< Double_t >  vector  )  [static]

Double_t Statistics::EPS (   )  [inline, static]

Double_t Statistics::EPS1 (   )  [inline, static]

Double_t Statistics::EPS2 (   )  [inline, static]

Double_t Statistics::FPMIN (   )  [inline, static]

map< string, Double_t > Statistics::FTest (  vector< Double_t >  vector1, vector< Double_t >  vector2 )  [static]

vector< int > Statistics::GetSortedIndex (  vector< Double_t >  vec  )  [static]

Double_t Statistics::IncompleteBetaFunction (  Double_t  a, Double_t  b, Double_t  x )  [static]

Double_t Statistics::IncompleteBetaFunctionContinuedFraction (  Double_t  a, Double_t  b, Double_t  x )  [static]

Evaluates continued fraction for incomplete beta function by modified Lentz's method (Numerical Recipes in C, chapter 6.4).

Double_t Statistics::IncompleteGammaFunctionPSeries (  Double_t  a, Double_t  x )  [static]

Returns the incomplete gamma function P(a,x) evaluated by its series representation (Numerical Recipes in C, chapter 6.2).

Double_t Statistics::IncompleteGammaFunctionQ (  Double_t  a, Double_t  x )  [static]

Returns the incomplete gamma function Q(a,x)=1-P(aa,x) (Numerical Recipes in C, chapter 6.2).

Double_t Statistics::IncompleteGammaFunctionQContinuedFraction (  Double_t  a, Double_t  x )  [static]

Returns the incomplete gamma function Q(a,x) evaluated by its continued fraction representation (Numerical Recipes in C, chapter 6.2).

map< string, Double_t > Statistics::KSTest (  vector< Double_t >  v1, vector< Double_t >  v2 )  [static]

Double_t Statistics::LogOfGammaFunction (  Double_t  x  )  [static]

Returns the value of ln[Gamma(x)] for x>0 (Numerical Recipes in C, chapter 6.1).

Double_t Statistics::Max (  vector< Double_t >  vector  )  [static]

Double_t Statistics::Max (  Double_t  val1, Double_t  val2 )  [static]

Double_t Statistics::MAXIT (   )  [inline, static]

Double_t Statistics::Mean (  vector< Double_t >  vector  )  [static]

Calculates the mean value of a vector.

Double_t Statistics::Min (  vector< Double_t >  vector  )  [static]

Double_t Statistics::Min (  Double_t  val1, Double_t  val2 )  [static]

Double_t Statistics::MutualEntropy (  vector< Double_t >  vector1, vector< Double_t >  vector2 )  [static]

Calculates H(X|Y), where X=vector1 and Y=vector2.

Double_t Statistics::RandomPoisson (  Double_t *  x, Double_t *  par )  [static]

Double_t Statistics::RMS (  vector< Double_t >  vector  )  [static]

vector< Double_t > Statistics::SortBubble (  vector< Double_t >  vec  )  [static]

Double_t Statistics::StandardDeviation (  vector< Double_t >  vector  )  [static]

Calculates the what we usually call variance of a vector: biased-corrected variance.

map< string, Double_t > Statistics::TTestForEqualVariances (  vector< Double_t >  vector1, vector< Double_t >  vector2 )  [static]

map< string, Double_t > Statistics::TTestForUnequalVariances (  vector< Double_t >  vector1, vector< Double_t >  vector2 )  [static]

Double_t Statistics::UnbiasedStandardDeviation (  vector< Double_t >  vector  )  [static]

Double_t Statistics::UnbiasedVariance (  vector< Double_t >  vector  )  [static]

Calculates the unbiased variance of a vector.

Double_t Statistics::Variance (  vector< Double_t >  vector  )  [static]

Calculates the what we usually call variance of a vector: biased-corrected variance.

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

• Statistics.h
• Statistics.cxx

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