itk::Statistics Namespace Reference

Namespaces
namespace	Algorithm
Classes
class	BackPropagationLayer
	This is the itkBackPropagationLayer class. More...
class	BatchSupervisedTrainingFunction
	This is the itkBatchSupervisedTrainingFunction class. More...
class	ChiSquareDistribution
	ChiSquareDistribution class defines the interface for a univariate Chi-Square distribution (pdfs, cdfs, etc.). More...
class	CompletelyConnectedWeightSet
	This is the itkCompletelyConnectedWeightSet class. More...
class	CovarianceSampleFilter
	Calculates the covariance matrix of the target sample data. More...
class	DecisionRule
	Base class for decision rules that return a class label based on a set of discriminant scores. More...
class	DenseFrequencyContainer2
	This class is a container for frequencies of bins in an histogram. More...
class	DistanceMetric
	this class declares common interfaces for distance functions. More...
class	DistanceToCentroidMembershipFunction
	DistanceToCentroidMembershipFunction models class membership using a distance metric. More...
class	ErrorBackPropagationLearningFunctionBase
	The ErrorBackPropagationLearningFunctionBase is the base class for all the ErrorBackPropagationLearning strategies. More...
class	ErrorBackPropagationLearningWithMomentum
	The ErrorBackPropagationLearningWithMomentum is the base class for all the ErrorBackPropagationLearning strategies. More...
class	ErrorFunctionBase
	This is the itkErrorFunctionBase class. More...
class	EuclideanDistanceMetric
	Euclidean distance function. More...
class	EuclideanSquareDistanceMetric
	Computes Euclidean distance between origin and given measurement vector. More...
class	ExpectationMaximizationMixtureModelEstimator
	This class generates the parameter estimates for a mixture model using expectation maximization strategy. More...
class	GaussianDistribution
	GaussianDistribution class defines the interface for a univariate Gaussian distribution (pdfs, cdfs, etc.). More...
class	GaussianMembershipFunction
	GaussianMembershipFunction models class membership through a multivariate Gaussian function. More...
class	GaussianMixtureModelComponent
	is a component (derived from MixtureModelComponentBase) for Gaussian class. This class is used in ExpectationMaximizationMixtureModelEstimator. More...
class	GaussianRadialBasisFunction
	This is the itkGaussianRadialBasisFunction class. More...
class	GaussianTransferFunction
	This is the itkGaussianTransferFunction class. More...
struct	GetHistogramDimension
class	HardLimitTransferFunction
	This is the itkHardLimitTransferFunction class. More...
class	Histogram
	This class stores measurement vectors in the context of n-dimensional histogram. More...
class	HistogramToRunLengthFeaturesFilter
	This class computes texture feature coefficients from a grey level run-length matrix. More...
class	HistogramToTextureFeaturesFilter
	This class computes texture feature coefficients from a grey level co-occurrence matrix. More...
class	IdentityTransferFunction
	This is the itkIdentityTransferFunction class. More...
class	ImageClassifierFilter
	Image classification class. More...
class	ImageJointDomainTraits
	This class provides the type defintion for the measurement vector in the joint domain (range domain -- pixel values + spatial domain -- pixel's physical coordinates). More...
class	ImageToHistogramFilter
	This class generates an histogram from an image. More...
class	ImageToListSampleAdaptor
	This class provides ListSample interface to ITK Image. More...
class	ImageToListSampleFilter
	The class takes an image as input and generates a list sample as output. More...
class	InputFunctionBase
	This is the itkInputFunctionBase class. More...
class	IterativeSupervisedTrainingFunction
	This is the itkIterativeSupervisedTrainingFunction class. More...
class	JointDomainImageToListSampleAdaptor
	This adaptor returns measurement vectors composed of an image pixel's range domain value (pixel value) and spatial domain value (pixel's physical coordiantes). More...
class	KdTree
	This class provides methods for k-nearest neighbor search and related data structures for a k-d tree. More...
class	KdTreeBasedKmeansEstimator
	fast k-means algorithm implementation using k-d tree structure More...
class	KdTreeGenerator
	This class generates a KdTree object without centroid information. More...
class	KdTreeNode
	This class defines the interface of its derived classes. More...
class	KdTreeNonterminalNode
	This is a subclass of the KdTreeNode. More...
class	KdTreeTerminalNode
	This class is the node that doesn't have any child node. The IsTerminal method returns true for this class. This class stores the instance identifiers belonging to this node, while the nonterminal nodes do not store them. The AddInstanceIdentifier and GetInstanceIdentifier are storing and retrieving the instance identifiers belonging to this node. More...
class	KdTreeWeightedCentroidNonterminalNode
	This is a subclass of the KdTreeNode. More...
class	LayerBase
	This is the itkLayerBase class. More...
class	LearningFunctionBase
	The LearningFunctionBase is the base class for all the learning strategies. More...
class	ListSample
	This class is the native implementation of the a Sample with an STL container. More...
class	LogSigmoidTransferFunction
	This is the itkLogSigmoidTransferFunction class. More...
class	MahalanobisDistanceMembershipFunction
	MahalanobisDistanceMembershipFunction models class membership using Mahalanobis distance. More...
class	MahalanobisDistanceMetric
	MahalanobisDistanceMetric class computes a Mahalanobis distance given a mean and covariance. More...
class	ManhattanDistanceMetric
	Euclidean distance function. More...
class	MaskedImageToHistogramFilter
	This class generates an histogram from an image. More...
class	MaximumDecisionRule
	A decision rule that returns the class label with the largest discriminant score. More...
class	MaximumRatioDecisionRule
	A decision rule that operates as a frequentist's approximation to Bayes rule. More...
class	MeanSampleFilter
	Given a sample, this filter computes the sample mean. More...
class	MeanSquaredErrorFunction
class	MeasurementVectorPixelTraits
class	MeasurementVectorTraits
class	MeasurementVectorTraitsTypes
class	MeasurementVectorTraitsTypes< std::vector< T > >
class	MembershipFunctionBase
	MembershipFunctionBase defines common interfaces for membership functions. More...
class	MembershipSample
	Container for storing the instance-identifiers of other sample with their associated class labels. More...
class	MersenneTwisterRandomVariateGenerator
	MersenneTwisterRandom random variate generator. More...
class	MinimumDecisionRule
	A decision rule that returns the class label with the smallest discriminant score. More...
class	MixtureModelComponentBase
	base class for distribution modules that supports analytical way to update the distribution parameters More...
class	MultilayerNeuralNetworkBase
	This is the itkMultilayerNeuralNetworkBase class. More...
class	MultiquadricRadialBasisFunction
	This is the itkMultiquadricRadialBasisFunction class. More...
class	NeighborhoodSampler
	Generates a Subsample out of a Sample, based on a user-provided distance to a MeasurementVector. More...
class	NeuralNetworkObject
	This is the itkNeuralNetworkObject class. More...
class	NNetDistanceMetricBase
	This is the itkNNetDistanceMetricBase class. More...
class	NormalVariateGenerator
	Normal random variate generator. More...
class	OneHiddenLayerBackPropagationNeuralNetwork
	This is the itkOneHiddenLayerBackPropagationNeuralNetwork class. More...
class	PointSetToListSampleAdaptor
	This class provides ListSample interface to ITK PointSet. More...
class	ProbabilityDistribution
	ProbabilityDistribution class defines common interface for statistical distributions (pdfs, cdfs, etc.). More...
class	ProductInputFunction
	This is the itkProductInputFunction class. More...
class	QuickPropLearningRule
	The QuickPropLearningRule is the base class for all the ErrorBackPropagationLearning strategies. More...
class	RadialBasisFunctionBase
	This is the itkRadialBasisFunctionBase class. More...
class	RandomVariateGeneratorBase
	Defines common interfaces for random variate generators. More...
class	RBFBackPropagationLearningFunction
	This is the itkRBFBackPropagationLearningFunction class. More...
class	RBFLayer
	This is the itkRBFLayer class. More...
class	RBFNetwork
	This is the itkRBFNetwork class. More...
class	Sample
	A collection of measurements for statistical analysis. More...
class	SampleClassifierFilter
	Sample classification class. More...
class	SampleToHistogramFilter
	Computes the Histogram corresponding to a Sample. More...
class	SampleToSubsampleFilter
	Base class of filters intended to select subsamples from samples. More...
class	ScalarImageToCooccurrenceListSampleFilter
	Converts pixel data into a list of pairs in order to compute a cooccurrence Histogram. More...
class	ScalarImageToCooccurrenceMatrixFilter
	This class computes a co-occurence matrix (histogram) from a given image and a mask image if provided. Coocurrence matrces are used for image texture description. More...
class	ScalarImageToHistogramGenerator
	TODO. More...
class	ScalarImageToRunLengthFeaturesFilter
	This class computes run length descriptions from an image. More...
class	ScalarImageToRunLengthMatrixFilter
	This class computes a run length matrix (histogram) from a given image and a mask image if provided. Run length matrces are used for image texture description. More...
class	ScalarImageToTextureFeaturesFilter
	This class computes texture descriptions from an image. More...
class	SigmoidTransferFunction
	This is the itkSigmoidTransferFunction class. More...
class	SignedHardLimitTransferFunction
	This is the itkSignedHardLimitTransferFunction class. More...
class	SparseFrequencyContainer2
	his class is a container for an histogram. More...
class	SquaredDifferenceErrorFunction
	This is the itkSquaredDifferenceErrorFunction class. More...
class	StandardDeviationPerComponentSampleFilter
	Calculates the covariance matrix of the target sample data. More...
class	Subsample
	This class stores a subset of instance identifiers from another sample object. You can create a subsample out of another sample object or another subsample object. The class is useful when storing or extracting a portion of a sample object. Note that when the elements of a subsample are sorted, the instance identifiers of the subsample are sorted without changing the original source sample. Most Statistics algorithms (that derive from StatisticsAlgorithmBase accept Subsample objects as inputs). More...
class	SumInputFunction
	This is the itkSumInputFunction class. More...
class	SymmetricSigmoidTransferFunction
	This is the itkSymmetricSigmoidTransferFunction class. More...
class	TanHTransferFunction
	This is the itkTanHTransferFunction class. More...
class	TanSigmoidTransferFunction
	This is the itkTanSigmoidTransferFunction class. More...
class	TDistribution
	TDistribution class defines the interface for a univariate Student-t distribution (pdfs, cdfs, etc.). More...
class	TrainingFunctionBase
	This is the itkTrainingFunctionBase class. More...
class	TransferFunctionBase
	This is the itkTransferFunctionBase class. More...
class	TwoHiddenLayerBackPropagationNeuralNetwork
	This is the itkTwoHiddenLayerBackPropagationNeuralNetwork class. More...
class	VectorContainerToListSampleAdaptor
	This class provides ListSample interface to ITK VectorContainer. More...
class	WeightedCentroidKdTreeGenerator
	This class generates a KdTree object with centroid information. More...
class	WeightedCovarianceSampleFilter
	Calculates the covariance matrix of the target sample data. where each measurement vector has an associated weight value. More...
class	WeightedMeanSampleFilter
	Given a sample where each measurement vector has associated weight value, this filter computes the sample mean. More...
class	WeightSetBase
	This is the itkWeightSetBase class. More...