
 Usage

Given a selection of sets of columns of interest, this class
provides the following functionalities, depending on the
execution mode it is executed in: Learn: calculates means,
unbiased variance and covariance estimators of column pairs
coefficient. More precisely, Learn calculates the averages
and centered variance/covariance sums; if finalize is set to
true (default), the final statistics are calculated. The
output metadata on port OUTPUT_MODEL is a multiblock dataset
containing at a minimum one vtkTable holding the raw sums in
a sparse matrix style. If finalize is true, then one
additional vtkTable will be present for each requested set
of column correlations. These additional tables contain
column averages, the upper triangular portion of the
covariance matrix (in the upper right hand portion of the
table) and the Cholesky decomposition of the covariance
matrix (in the lower portion of the table beneath the
covariance triangle). The leftmost column will be a vector
of column averages. The last entry in the column averages
vector is the number of samples. As an example, consider a
request for a 3-column correlation with columns named ColA,
ColB, and ColC. The resulting table will look like this:

        Column  |Mean     |ColA     |ColB     |ColC

  &mdash;&mdash;&ndash;+&mdash;&mdash;&mdash;+&mdash;&mdash;&mdash;+&mdash;&mdash;&mdash;+&mdash;&mdash;&mdash;
        ColA    |avg(A)   |cov(A,A) |cov(A,B) |cov(A,C)
        ColB    |avg(B)   |chol(1,1)|cov(B,B) |cov(B,C)
        ColC    |avg(C)   |chol(2,1)|chol(2,2)|cov(C,C)
        Cholesky|length(A)|chol(3,1)|chol(3,2)|chol(3,3)

Assess: given a set of results matrices as specified above
in input port INPUT_MODEL and tabular data on input port
INPUT_DATA that contains column names matching those of the
tables on input port INPUT_MODEL, the assess mode computes
the relative deviation of each observation in port
INPUT_DATA's table according to the linear correlations
implied by each table in port INPUT_MODEL.
.SECTION Thanks Thanks to Philippe Pebay, Jackson Mayo, and
David Thompson of Sandia National Laboratories for
implementing this class.
To create an instance of class
vtkMultiCorrelativeStatistics, simply invoke its constructor
as follows

    obj = vtkMultiCorrelativeStatistics



 Methods

The class vtkMultiCorrelativeStatistics has several methods
that can be used. They are listed below. Note that the
documentation is translated automatically from the VTK
sources, and may not be completely intelligible. When in
doubt, consult the VTK website. In the methods listed below,
obj is an instance of the vtkMultiCorrelativeStatistics
class.

* string = obj.GetClassName ()
* int = obj.IsA (string name)
* vtkMultiCorrelativeStatistics = obj.NewInstance ()
* vtkMultiCorrelativeStatistics = obj.SafeDownCast
  (vtkObject o)
* obj.Aggregate (vtkDataObjectCollection , vtkDataObject ) -
  Given a collection of models, calculate aggregate model


* FreeMat_Documentation
* Visualization_Toolkit_Infovis_Classes
* Generated on Thu Jul 25 2013 17:18:33 for FreeMat by
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