VTK
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions
vtkCorrelativeStatistics Class Reference

A class for linear correlation. More...

#include <vtkCorrelativeStatistics.h>

Inheritance diagram for vtkCorrelativeStatistics:
[legend]
Collaboration diagram for vtkCorrelativeStatistics:
[legend]

List of all members.

Public Types

typedef
vtkBivariateStatisticsAlgorithm 
Superclass

Public Member Functions

virtual const char * GetClassName ()
virtual int IsA (const char *type)
void PrintSelf (ostream &os, vtkIndent indent)
virtual void Aggregate (vtkDataObjectCollection *, vtkMultiBlockDataSet *)

Static Public Member Functions

static int IsTypeOf (const char *type)
static vtkCorrelativeStatisticsSafeDownCast (vtkObject *o)
static vtkCorrelativeStatisticsNew ()

Protected Member Functions

 vtkCorrelativeStatistics ()
 ~vtkCorrelativeStatistics ()
virtual void Derive (vtkMultiBlockDataSet *)
virtual void Learn (vtkTable *inData, vtkTable *inParameters, vtkMultiBlockDataSet *outMeta)
virtual void Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *)
virtual void SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc)

Detailed Description

A class for linear correlation.

Given a selection of pairs of columns of interest, this class provides the following functionalities, depending on the chosen execution options: Learn: calculate extremal values, sample mean, and M2 aggregates (cf. P. Pebay, Formulas for robust, one-pass parallel computation of covariances and Arbitrary-Order Statistical Moments, Sandia Report SAND2008-6212, Sep 2008, http://infoserve.sandia.gov/sand_doc/2008/086212.pdf for details) Derive: calculate unbiased variance and covariance estimators, estimator of standard deviations, linear regressions, and Pearson correlation coefficient. Assess: given an input data set, two means and a 2x2 covariance matrix, mark each datum with corresponding relative deviation (2-dimensional Mahlanobis distance). Test: no statistical tests available yet.

Thanks:
Thanks to Philippe Pebay and David Thompson from Sandia National Laboratories for implementing this class.
Examples:
vtkCorrelativeStatistics (Examples)
Tests:
vtkCorrelativeStatistics (Tests)

Definition at line 58 of file vtkCorrelativeStatistics.h.


Member Typedef Documentation

Reimplemented from vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

Definition at line 61 of file vtkCorrelativeStatistics.h.


Constructor & Destructor Documentation


Member Function Documentation

virtual const char* vtkCorrelativeStatistics::GetClassName ( ) [virtual]

Reimplemented from vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

static int vtkCorrelativeStatistics::IsTypeOf ( const char *  name) [static]

Return 1 if this class type is the same type of (or a subclass of) the named class. Returns 0 otherwise. This method works in combination with vtkTypeMacro found in vtkSetGet.h.

Reimplemented from vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

virtual int vtkCorrelativeStatistics::IsA ( const char *  name) [virtual]

Return 1 if this class is the same type of (or a subclass of) the named class. Returns 0 otherwise. This method works in combination with vtkTypeMacro found in vtkSetGet.h.

Reimplemented from vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

Reimplemented from vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

void vtkCorrelativeStatistics::PrintSelf ( ostream &  os,
vtkIndent  indent 
) [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 vtkBivariateStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

Create an object with Debug turned off, modified time initialized to zero, and reference counting on.

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

Given a collection of models, calculate aggregate model

Implements vtkStatisticsAlgorithm.

virtual void vtkCorrelativeStatistics::Learn ( vtkTable inData,
vtkTable inParameters,
vtkMultiBlockDataSet outMeta 
) [protected, virtual]

Execute the calculations required by the Learn option.

Implements vtkStatisticsAlgorithm.

Reimplemented in vtkPCorrelativeStatistics.

virtual void vtkCorrelativeStatistics::Derive ( vtkMultiBlockDataSet ) [protected, virtual]

Execute the calculations required by the Derive option.

Implements vtkStatisticsAlgorithm.

virtual void vtkCorrelativeStatistics::Test ( vtkTable ,
vtkMultiBlockDataSet ,
vtkTable  
) [protected, virtual]

Execute the calculations required by the Test option.

Implements vtkStatisticsAlgorithm.

virtual void vtkCorrelativeStatistics::SelectAssessFunctor ( vtkTable outData,
vtkDataObject inMeta,
vtkStringArray rowNames,
AssessFunctor *&  dfunc 
) [protected, virtual]

Provide the appropriate assessment functor.

Implements vtkStatisticsAlgorithm.


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