class ROOT::Math::GoFTest

Function Members (Methods)

public:

virtual	~GoFTest()
Double_t	AndersonDarling2SamplesTest(const Char_t* option = "p") const
void	AndersonDarling2SamplesTest(Double_t& pvalue, Double_t& testStat) const
Double_t	AndersonDarlingTest(const Char_t* option = "p") const
void	AndersonDarlingTest(Double_t& pvalue, Double_t& testStat) const
ROOT::Math::GoFTest	GoFTest(UInt_t sampleSize, const Double_t* sample, ROOT::Math::GoFTest::EDistribution dist = kUndefined)
ROOT::Math::GoFTest	GoFTest(UInt_t sample1Size, const Double_t* sample1, UInt_t sample2Size, const Double_t* sample2)
ROOT::Math::GoFTest	GoFTest(UInt_t sampleSize, const Double_t* sample, const ROOT::Math::IGenFunction& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)
Double_t	KolmogorovSmirnov2SamplesTest(const Char_t* option = "p") const
void	KolmogorovSmirnov2SamplesTest(Double_t& pvalue, Double_t& testStat) const
Double_t	KolmogorovSmirnovTest(const Char_t* option = "p") const
void	KolmogorovSmirnovTest(Double_t& pvalue, Double_t& testStat) const
Double_t	operator()(ROOT::Math::GoFTest::ETestType test = kAD, const Char_t* option = "p") const
void	operator()(ROOT::Math::GoFTest::ETestType test, Double_t& pvalue, Double_t& testStat) const
void	SetDistribution(ROOT::Math::GoFTest::EDistribution dist)
void	SetUserCDF(const ROOT::Math::IGenFunction& cdf, Double_t xmin = 1, Double_t xmax = 0)
void	SetUserDistribution(const ROOT::Math::IGenFunction& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)
void	SetUserDistribution<const ROOT::Math::IBaseFunctionOneDim>(ROOT::Math::const IBaseFunctionOneDim& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)
void	SetUserPDF(const ROOT::Math::IGenFunction& pdf, Double_t xmin = 1, Double_t xmax = 0)

private:

Double_t	ExponentialCDF(Double_t x) const
Double_t	GaussianCDF(Double_t x) const
Double_t	GetSigmaN(UInt_t N) const
ROOT::Math::GoFTest	GoFTest()
ROOT::Math::GoFTest	GoFTest(ROOT::Math::GoFTest& gof)
void	Instantiate(const Double_t* sample, UInt_t sampleSize)
Double_t	InterpolatePValues(Double_t dA2, Int_t bin) const
Double_t	LogNormalCDF(Double_t x) const
void	LogSample()
ROOT::Math::GoFTest	operator=(ROOT::Math::GoFTest& gof)
Double_t	PValueAD1Sample(Double_t A2) const
Double_t	PValueAD2Samples(Double_t& A2, UInt_t N) const
void	SetCDF()
void	SetDistributionFunction(const ROOT::Math::IGenFunction& cdf, Bool_t isPDF, Double_t xmin, Double_t xmax)
void	SetParameters()
void	SetSamples(vector<const Double_t*> samples, const vector<UInt_t> samplesSizes)

Data Members

public:

static ROOT::Math::GoFTest::ETestType	kAD
static ROOT::Math::GoFTest::ETestType	kAD2s
static ROOT::Math::GoFTest::EUserDistribution	kCDF
static ROOT::Math::GoFTest::EDistribution	kExponential
static ROOT::Math::GoFTest::EDistribution	kGaussian
static ROOT::Math::GoFTest::ETestType	kKS
static ROOT::Math::GoFTest::ETestType	kKS2s
static ROOT::Math::GoFTest::EDistribution	kLogNormal
static ROOT::Math::GoFTest::EUserDistribution	kPDF
static ROOT::Math::GoFTest::EDistribution	kUndefined
static ROOT::Math::GoFTest::EDistribution	kUserDefined

private:

auto_ptr<ROOT::Math::IGenFunction>	fCDF
vector<Double_t>	fCombinedSamples
ROOT::Math::GoFTest::EDistribution	fDist
Double_t	fMean
vector<vector<Double_t> >	fSamples
Double_t	fSigma
Bool_t	fTestSampleFromH0

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

GoFTest(UInt_t sample1Size, const Double_t* sample1, UInt_t sample2Size, const Double_t* sample2)

Constructor for using only with 2-samples tests

GoFTest(UInt_t sampleSize, const Double_t* sample, ROOT::Math::GoFTest::EDistribution dist = kUndefined)

Constructor for using only with 1-sample tests with a specified distribution

GoFTest(UInt_t sampleSize, const Double_t* sample, const ROOT::Math::IGenFunction& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)

Templated constructor for using only with 1-sample tests with a user specified distribution

Instantiate(const Double_t* sample, UInt_t sampleSize)

GoFTest(UInt_t sampleSize, const Double_t* sample, const ROOT::Math::IGenFunction& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)

Specialization using IGenFunction interface

SetUserDistribution(const ROOT::Math::IGenFunction& dist, ROOT::Math::GoFTest::EUserDistribution userDist = kPDF, Double_t xmin = 1, Double_t xmax = 0)

SetDistributionFunction(const ROOT::Math::IGenFunction& cdf, Bool_t isPDF, Double_t xmin, Double_t xmax)

void SetUserPDF(const ROOT::Math::IGenFunction& pdf, Double_t xmin = 1, Double_t xmax = 0)

Sets the user input distribution as a probability density function for 1-sample tests

void SetUserCDF(const ROOT::Math::IGenFunction& cdf, Double_t xmin = 1, Double_t xmax = 0)

 Sets the user input distribution as a cumulative distribution function for 1-sample tests
      The CDF must return zero

void SetDistribution(ROOT::Math::GoFTest::EDistribution dist)

Sets the distribution for the predefined distribution types

virtual ~GoFTest()

Double_t AndersonDarling2SamplesTest(const Char_t* option = "p") const

  The Anderson-Darling K-Sample Test algorithm is described and taken from
  http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/andeksam.htm
  and described and taken from (1)
  Scholz F.W., Stephens M.A. (1987), K-sample Anderson-Darling Tests, Journal of the American Statistical Association, 82, 918–924. (2-samples variant implemented)
*/ void AndersonDarling2SamplesTest(Double_t& pvalue, Double_t& testStat) const;

Double_t AndersonDarlingTest(const Char_t* option = "p") const

  The Anderson-Darling 1-Sample Test algorithm for a specific distribution is described at
  http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/andedarl.htm
  and described and taken from (2)
  Marsaglia J.C.W., Marsaglia G. (2004), Evaluating the Anderson-Darling Distribution, Journal of Statistical Software, Volume 09, Issue i02.
  and described and taken from (3)
  Lewis P.A.W. (1961), The Annals of Mathematical Statistics, Distribution of the Anderson-Darling Statistic, Volume 32, Number 4, 1118-1124.
*/ void AndersonDarlingTest(Double_t& pvalue, Double_t& testStat) const;

Double_t KolmogorovSmirnov2SamplesTest(const Char_t* option = "p") const

  The Kolmogorov-Smirnov 2-Samples Test algorithm is described at
  http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/ks2samp.htm
  and described and taken from
  http://root.cern.ch/root/html/TMath.html#TMath:KolmogorovTest
*/ void KolmogorovSmirnov2SamplesTest(Double_t& pvalue, Double_t& testStat) const;

Double_t KolmogorovSmirnovTest(const Char_t* option = "p") const

  The Kolmogorov-Smirnov 1-Sample Test algorithm for a specific distribution is described at
  http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/kstest.htm
  and described and taken from (4)
  Press W. H., Teukolsky S.A., Vetterling W.T., Flannery B.P. (2007), Numerical Recipes - The Art of Scientific Computing (Third Edition), Cambridge Univerdity Press
*/ void KolmogorovSmirnovTest(Double_t& pvalue, Double_t& testStat) const;

void operator()(ROOT::Math::GoFTest::ETestType test, Double_t& pvalue, Double_t& testStat) const

 The class's unary functions

Double_t operator()(ROOT::Math::GoFTest::ETestType test = kAD, const Char_t* option = "p") const

GoFTest()

GoFTest operator=(ROOT::Math::GoFTest& gof)

void SetCDF()

Double_t LogNormalCDF(Double_t x) const

Double_t GaussianCDF(Double_t x) const

Double_t ExponentialCDF(Double_t x) const

Double_t GetSigmaN(UInt_t N) const

Double_t InterpolatePValues(Double_t dA2, Int_t bin) const

Double_t PValueAD2Samples(Double_t& A2, UInt_t N) const

Double_t PValueAD1Sample(Double_t A2) const

void LogSample()

void SetSamples(vector<const Double_t*> samples, const vector<UInt_t> samplesSizes)

void SetParameters()