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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< TInputSample >:

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Collaboration diagram for itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >:

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List of all members.

Public Types

typedef GoodnessOfFitMixtureModelCostFunction Self
typedef SingleValuedCostFunction Superclass
typedef SmartPointer< SelfPointer
typedef SmartPointer< const
Self
ConstPointer
typedef TInputSample InputSampleType
typedef TInputSample::MeasurementType MeasurementType
typedef TInputSample::MeasurementVectorType MeasurementVectorType
typedef TInputSample::MeasurementVectorSizeType MeasurementVectorSizeType
typedef SingleValuedCostFunction::ParametersType ParamtersType
typedef SingleValuedCostFunction::MeasureType MeasureType
typedef GoodnessOfFitComponentBase<
TInputSample > 
ComponentType
typedef std::vector< ComponentType * > ComponentVectorType
typedef GoodnessOfFitFunctionBase<
typename ComponentType::HistogramType
FunctionType

Public Member Functions

virtual const char * GetNameOfClass () const
void AddComponent (ComponentType *component)
void SetFunction (FunctionType *core)
FunctionTypeGetFunction ()
virtual unsigned int GetNumberOfParameters () const
virtual MeasureType GetValue (const ParametersType &parameters) const
virtual void GetDerivative (const ParametersType &, DerivativeType &) const

Static Public Member Functions

Pointer New ()

Protected Member Functions

 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.

Recent API changes: The static const macro to get the length of a measurement vector, 'MeasurementVectorSize' has been removed to allow the length of a measurement vector to be specified at run time.

See also:
GoodnessOfFitFunctionBase, GoodnessOfFitComponentBase, SingleValuedCostFunction, SingleValuedNonLinearOptimizer

Definition at line 80 of file itkGoodnessOfFitMixtureModelCostFunction.h.


Member Typedef Documentation

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

Definition at line 109 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 110 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Reimplemented from itk::SingleValuedCostFunction.

Definition at line 88 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 113 of file itkGoodnessOfFitMixtureModelCostFunction.h.

Referenced by itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetFunction().

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

Definition at line 96 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 97 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 99 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 98 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 107 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 103 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Reimplemented from itk::SingleValuedCostFunction.

Definition at line 87 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Standard class typedefs

Reimplemented from itk::SingleValuedCostFunction.

Definition at line 85 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Reimplemented from itk::SingleValuedCostFunction.

Definition at line 86 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 void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetDerivative const ParametersType ,
DerivativeType
const [inline, virtual]
 

This method returns the derivative of the cost function corresponding to the specified parameters.

Implements itk::SingleValuedCostFunction.

Definition at line 132 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 121 of file itkGoodnessOfFitMixtureModelCostFunction.h.

References itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::FunctionType.

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedCostFunction.

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>
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:
Generated at Thu May 25 03:04:59 2006 for ITK by doxygen 1.3.5 written by Dimitri van Heesch, © 1997-2000