1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
|
/*=========================================================================
Program: Visualization Toolkit
Module: vtkPCAStatisticsGnuR.h
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
/*-------------------------------------------------------------------------
Copyright 2010 Sandia Corporation.
Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
the U.S. Government retains certain rights in this software.
-------------------------------------------------------------------------*/
/**
* @class vtkPCAStatisticsGnuR
* @brief A class for multivariate principal component analysis
* using R to calculate p-values.
*
*
* This class derives from the multi-correlative statistics algorithm and
* uses the covariance matrix and Cholesky decomposition computed by it.
* However, when it finalizes the statistics in learn operation, the PCA class
* computes the SVD of the covariance matrix in order to obtain its eigenvectors.
*
* In the assess operation, the input data are
* - projected into the basis defined by the eigenvectors,
* - the energy associated with each datum is computed,
* - or some combination thereof.
* Additionally, the user may specify some threshold energy or
* eigenvector entry below which the basis is truncated. This allows
* projection into a lower-dimensional state while minimizing (in a
* least squares sense) the projection error.
*
* In the test operation, a Jarque-Bera-Srivastava test of n-d normality is performed.
*
* @par Thanks:
* Thanks to David Thompson, Philippe Pebay and Jackson Mayo from
* Sandia National Laboratories for implementing this class.
* Updated by Philippe Pebay, Kitware SAS 2012
*/
#ifndef vtkPCAStatisticsGnuR_h
#define vtkPCAStatisticsGnuR_h
#include "vtkFiltersStatisticsGnuRModule.h" // For export macro
#include "vtkPCAStatistics.h"
class vtkDoubleArray;
class VTKFILTERSSTATISTICSGNUR_EXPORT vtkPCAStatisticsGnuR : public vtkPCAStatistics
{
public:
vtkTypeMacro(vtkPCAStatisticsGnuR,vtkPCAStatistics);
virtual void PrintSelf( ostream& os, vtkIndent indent );
static vtkPCAStatisticsGnuR* New();
protected:
vtkPCAStatisticsGnuR();
~vtkPCAStatisticsGnuR();
virtual vtkDoubleArray* CalculatePValues(vtkIdTypeArray*, vtkDoubleArray*);
private:
vtkPCAStatisticsGnuR(const vtkPCAStatisticsGnuR&) VTK_DELETE_FUNCTION;
void operator=(const vtkPCAStatisticsGnuR&) VTK_DELETE_FUNCTION;
};
#endif // vtkPCAStatisticsGnuR_h
|
