ITK
4.2.0
Insight Segmentation and Registration Toolkit
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#include <itkProbabilityDistribution.h>
Public Types | |
typedef SmartPointer< const Self > | ConstPointer |
typedef Array< double > | ParametersType |
typedef SmartPointer< Self > | Pointer |
typedef ProbabilityDistribution | Self |
typedef Object | Superclass |
Public Types inherited from itk::Object | |
Public Types inherited from itk::LightObject |
Public Member Functions | |
virtual double | EvaluateCDF (double x) const =0 |
virtual double | EvaluateCDF (double x, const ParametersType &) const =0 |
virtual double | EvaluateInverseCDF (double p) const =0 |
virtual double | EvaluateInverseCDF (double p, const ParametersType &) const =0 |
virtual double | EvaluatePDF (double x) const =0 |
virtual double | EvaluatePDF (double x, const ParametersType &) const =0 |
virtual double | GetMean () const =0 |
virtual const char * | GetNameOfClass () const |
virtual SizeValueType | GetNumberOfParameters () const =0 |
virtual const ParametersType & | GetParameters () |
virtual double | GetVariance () const =0 |
virtual bool | HasMean () const =0 |
virtual bool | HasVariance () const =0 |
virtual void | SetParameters (const ParametersType ¶ms) |
Public Member Functions inherited from itk::Object | |
unsigned long | AddObserver (const EventObject &event, Command *) |
unsigned long | AddObserver (const EventObject &event, Command *) const |
virtual LightObject::Pointer | CreateAnother () const |
virtual void | DebugOff () const |
virtual void | DebugOn () const |
Command * | GetCommand (unsigned long tag) |
bool | GetDebug () const |
MetaDataDictionary & | GetMetaDataDictionary (void) |
const MetaDataDictionary & | GetMetaDataDictionary (void) const |
virtual unsigned long | GetMTime () const |
virtual const TimeStamp & | GetTimeStamp () const |
bool | HasObserver (const EventObject &event) const |
void | InvokeEvent (const EventObject &) |
void | InvokeEvent (const EventObject &) const |
virtual void | Modified () const |
virtual void | Register () const |
void | RemoveAllObservers () |
void | RemoveObserver (unsigned long tag) |
void | SetDebug (bool debugFlag) const |
void | SetMetaDataDictionary (const MetaDataDictionary &rhs) |
virtual void | SetReferenceCount (int) |
virtual void | UnRegister () const |
Public Member Functions inherited from itk::LightObject | |
virtual void | Delete () |
virtual int | GetReferenceCount () const |
itkCloneMacro (Self) | |
void | Print (std::ostream &os, Indent indent=0) const |
Protected Member Functions | |
void | PrintSelf (std::ostream &os, Indent indent) const |
ProbabilityDistribution (void) | |
virtual | ~ProbabilityDistribution (void) |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &time) |
virtual | ~Object () |
Protected Member Functions inherited from itk::LightObject | |
virtual LightObject::Pointer | InternalClone () const |
LightObject () | |
virtual void | PrintHeader (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
Protected Attributes | |
ParametersType | m_Parameters |
Private Member Functions | |
void | operator= (const Self &) |
ProbabilityDistribution (const Self &) |
Additional Inherited Members | |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool flag) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
ProbabilityDistribution class defines common interface for statistical distributions (pdfs, cdfs, etc.).
ProbabilityDistribution defines a common interface for parameteric and non-parametric distributions. ProbabilityDistribution provides access to the probability density function (pdf), the cumulative distribution function (cdf), and the inverse cumulative distribution function.
ProbabilityDistribution also defines an abstract interface for setting parameters of distribution (mean/variance for a Gaussian, degrees of freedom for Student-t, etc.).
Note that nonparametric subclasses of ProbabilityDistribution are possible. For instance, a nonparametric implementation may use a histogram or kernel density function to model the distribution.
The EvaluatePDF(), EvaluateCDF, EvaluateInverseCDF() methods are all virtual, allowing algorithms to be written with an abstract interface to a distribution (with said distribution provided to the algorithm at run-time). Static methods, not requiring an instance of the distribution, are also allowed. The static methods allow for optimized access to distributions when the distribution is known a priori to the algorithm.
ProbabilityDistributions are univariate. Multivariate versions may be provided under a separate superclass (since the parameters to the pdf and cdf would have to be vectors not scalars). Perhaps this class will be named MultivariateProbabilityDistribution.
ProbabilityDistributions can be used for standard statistical tests: Z-scores, t-tests, chi-squared tests, F-tests, etc.
Definition at line 71 of file itkProbabilityDistribution.h.
typedef SmartPointer< const Self > itk::Statistics::ProbabilityDistribution::ConstPointer |
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
Definition at line 79 of file itkProbabilityDistribution.h.
typedef Array< double > itk::Statistics::ProbabilityDistribution::ParametersType |
Type of the parameter vector.
Definition at line 82 of file itkProbabilityDistribution.h.
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
Definition at line 78 of file itkProbabilityDistribution.h.
Standard class typedefs
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
Definition at line 76 of file itkProbabilityDistribution.h.
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
Definition at line 77 of file itkProbabilityDistribution.h.
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inlineprotected |
Definition at line 157 of file itkProbabilityDistribution.h.
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inlineprotectedvirtual |
Definition at line 158 of file itkProbabilityDistribution.h.
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private |
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pure virtual |
Evaluate the cumulative distribution function (cdf). The parameters of the distribution are assigned via SetParameters(). See concrete subclasses for the ordering of parameters.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Evaluate the cumulative distribution function (cdf). The parameters for the distribution are passed as a parameters vector. See concrete subclasses for the ordering of parameters.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Evaluate the inverse cumulative distribution function (inverse cdf). Parameter p must be between 0.0 and 1.0. The parameters of the distribution are assigned via SetParameters(). See concrete subclasses for the ordering of parameters.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Evaluate the inverse cumulative distribution function (inverse cdf). Parameter p must be between 0.0 and 1.0. The parameters for the distribution are passed as a parameters vector. See concrete subclasses for the ordering of parameters.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Evaluate the probability density function (pdf). The parameters of the distribution are assigned via SetParameters().
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Evaluate the probability density function (pdf). The parameters for the distribution are passed as a parameters vector. See concrete subclasses for the ordering of parameters.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Get the mean of the distribution. If the mean does not exist, then quiet_NaN may is returned.
Implemented in itk::Statistics::ChiSquareDistribution, itk::Statistics::TDistribution, and itk::Statistics::GaussianDistribution.
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virtual |
Standard macros
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Return the number of parameters that describe the distribution. For nonparametric distributions, this will be a function of the number of samples.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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virtual |
Get the parameters of the distribution. See concrete subclasses for the order of parameters. Subclasses may provide convenience methods for setting parameters, i.e. SetDegreesOfFreedom(), etc.
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pure virtual |
Get the variance of the distribution. If the variance does not exist, then quiet_NaN is returned.
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::TDistribution, and itk::Statistics::ChiSquareDistribution.
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pure virtual |
Does this distribution have a mean?
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::ChiSquareDistribution, and itk::Statistics::TDistribution.
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pure virtual |
Does this distribution have a variance?
Implemented in itk::Statistics::GaussianDistribution, itk::Statistics::TDistribution, and itk::Statistics::ChiSquareDistribution.
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private |
Mutex lock to protect modification to the reference count
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::TDistribution, and itk::Statistics::ChiSquareDistribution.
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inlineprotectedvirtual |
Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::Object.
Reimplemented in itk::Statistics::GaussianDistribution, itk::Statistics::TDistribution, and itk::Statistics::ChiSquareDistribution.
Definition at line 159 of file itkProbabilityDistribution.h.
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inlinevirtual |
Set the parameters of the distribution. See concrete subclasses for the order of the parameters. Subclasses may provide convenience methods for setting parameters, i.e. SetDegreesOfFreedom(), etc.
Definition at line 100 of file itkProbabilityDistribution.h.
References itk::Array< TValueType >::GetSize().
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protected |
Definition at line 165 of file itkProbabilityDistribution.h.