itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample > Class Template Reference

calculates the goodness-of-fit statstics for multivarate mixture model. More...

#include <itkGoodnessOfFitMixtureModelCostFunction.h>

Inheritance diagram for itk::Statistics::GoodnessOfFitMixtureModelCostFunction:

[legend]Collaboration diagram for itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >:

[legend]List of all members.

Public Types
typedef GoodnessOfFitMixtureModelCostFunction	Self
typedef SingleValuedCostFunction	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef TInputSample	InputSampleType
typedef TInputSample::MeasurementType	MeasurementType
typedef TInputSample::MeasurementVectorType	MeasurementVectorType
typedef SingleValuedCostFunction::ParametersType	ParamtersType
typedef SingleValuedCostFunction::MeasureType	MeasureType
typedef GoodnessOfFitComponentBase< TInputSample >	ComponentType
typedef std::vector< ComponentType * >	ComponentVectorType
typedef GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >	FunctionType
Public Methods
virtual const char *	GetClassName () const
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TInputSample::MeasurementVectorSize)
void	AddComponent (ComponentType *component)
void	SetFunction (FunctionType *core)
FunctionType *	GetFunction ()
virtual unsigned int	GetNumberOfParameters () const
virtual MeasureType	GetValue (const ParametersType &parameters) const
virtual void	GetDerivative (const ParametersType &parameters, DerivativeType &derivative) const
Static Public Methods
Pointer	New ()
Protected Methods
	GoodnessOfFitMixtureModelCostFunction ()
virtual	~GoodnessOfFitMixtureModelCostFunction ()
virtual void	PrintSelf (std::ostream &os, Indent indent) const

---

Detailed Description

template<class TInputSample>
class itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >

calculates the goodness-of-fit statstics for multivarate mixture model.

The goodness-of-fit statistics for a single model is discrepancy between the observed frequency and the expected frequency. To reduce computational load of multivariate case, this class uses projective method.

The projective multivariate goodness-of-fit statistics calculation follows the following steps:

1) creates a subsample that includes the measurement vectors that fall in a spherical kernel. 2) finds the base axes determined by the eigen vectors of the covariance matrix. 3) project the subsample on to one of the base axes (from step 2) 4) calculates the observed frequencies (in an 1D Histogram object) after projection (step 3) and the expected frequencies (in an 1D Histogram object) 5) calculates the discrepancy between the observed histogram and the expected histogram using a goodness-of-fit statistics 6) repeat step 3) - 5) and sum the goodness-of-fit values

For a mixture model, the above procedure is applied independently for each model (module). The sum of the goodness-of-fit values of models is the goodness-of-fit statistics for the mixture model.

The step 1) - 4) is done by the subclasses of GoodnessOfFitComponentBase, and the step 5) is done by the subclasses of GoodnessOfFitFunctionBase.

To see how this class interacts GoodnessOfFitComponentBase objects and GoodnessOfFitFunctionBase objects, please look at the implementation of the GetValue method of this class.

Better fit means smaller goodness-of-fit value in this implementation. This class is following the SingleValuedCostFunction interfaces so that users can uses this function with any subclasses of SingleValuedNonLinearOptimizer class as long as they do not use GetDerivative and GetValueAndDerivative methods.

See also:

GoodnessOfFitFunctionBase, GoodnessOfFitComponentBase, SingleValuedCostFunction, SingleValuedNonLinearOptimizer

Definition at line 75 of file itkGoodnessOfFitMixtureModelCostFunction.h.

---

Member Typedef Documentation

template<class TInputSample> typedef GoodnessOfFitComponentBase< TInputSample > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ComponentType

Definition at line 105 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef std::vector< ComponentType* > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ComponentVectorType

Definition at line 106 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SmartPointer< const Self > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ConstPointer

Reimplemented from itk::SingleValuedCostFunction. Definition at line 83 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef GoodnessOfFitFunctionBase< typename ComponentType::HistogramType > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::FunctionType

Definition at line 109 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef TInputSample itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::InputSampleType

Definition at line 91 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef TInputSample::MeasurementType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::MeasurementType

Definition at line 94 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef TInputSample::MeasurementVectorType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::MeasurementVectorType

Definition at line 95 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction::MeasureType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::MeasureType

MeasureType typedef. It defines a type used to return the cost function value. Reimplemented from itk::SingleValuedCostFunction. Definition at line 103 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction::ParametersType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ParamtersType

ParametersType typedef. It defines a position in the optimization search space. Definition at line 99 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SmartPointer< Self > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::Pointer

Reimplemented from itk::SingleValuedCostFunction. Definition at line 82 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef GoodnessOfFitMixtureModelCostFunction itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::Self

Standard class typedefs Reimplemented from itk::SingleValuedCostFunction. Definition at line 80 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::Superclass

Reimplemented from itk::SingleValuedCostFunction. Definition at line 81 of file itkGoodnessOfFitMixtureModelCostFunction.h.

---

Constructor & Destructor Documentation

template<class TInputSample> itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GoodnessOfFitMixtureModelCostFunction (    )  [protected]

template<class TInputSample> virtual itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::~GoodnessOfFitMixtureModelCostFunction (    )  [protected, virtual]

---

Member Function Documentation

template<class TInputSample> void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::AddComponent (  ComponentType *    component )

aceesing methods for the sample manipulator

template<class TInputSample> virtual const char* itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetClassName (    )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::SingleValuedCostFunction.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetDerivative (  const ParametersType &    parameters, DerivativeType &    derivative )  const [inline, virtual]

This method returns the derivative of the cost function corresponding to the specified parameters. Implements itk::SingleValuedCostFunction. Definition at line 128 of file itkGoodnessOfFitMixtureModelCostFunction.h. References itk::DerivativeType, and itk::ParametersType.

template<class TInputSample> FunctionType* itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetFunction (    )  [inline]

Definition at line 117 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> virtual unsigned int itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetNumberOfParameters (    )  const [virtual]

Return the number of parameters required to compute this cost function. This method MUST be overloaded by derived classes. Implements itk::CostFunction.

template<class TInputSample> virtual MeasureType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetValue (  const ParametersType &    parameters )  const [virtual]

This method returns the value of the cost function corresponding to the specified parameters. Implements itk::SingleValuedCostFunction.

template<class TInputSample> itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::itkStaticConstMacro (  MeasurementVectorSize   , unsigned    int, TInputSample::MeasurementVectorSize    )

template<class TInputSample> Pointer itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::New (    )  [static]

Method for creation through the object factory. Reimplemented from itk::Object.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::PrintSelf (  std::ostream &    os, Indent    indent )  const [protected, virtual]

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::CostFunction.

template<class TInputSample> void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::SetFunction (  FunctionType *    core )

aceesing methods for the expected probability histogram

---

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

• itkGoodnessOfFitMixtureModelCostFunction.h

---