
 Usage

Given a selection of columns of interest in an input data
table, this class provides the following functionalities,
depending on the execution mode it is executed in: Learn:
calculate extremal values, arithmetic mean, unbiased
variance estimator, skewness estimator, and both sample and
G2 estimation of the kurtosis excess. More precisely, Learn
calculates the sums; if finalize is set to true (default),
the final statistics are calculated with CalculateFromSums.
Otherwise, only raw sums are output; this option is made for
efficient parallel calculations. Note that CalculateFromSums
is a static function, so that it can be used directly with
no need to instantiate a vtkDescriptiveStatistics object.
Assess: given an input data set in port INPUT_DATA, and a
reference value x along with an acceptable deviation d>0,
assess all entries in the data set which are outside of [x-
d,x+d].
.SECTION Thanks Thanks to Philippe Pebay and David Thompson
from Sandia National Laboratories for implementing this
class.
To create an instance of class vtkDescriptiveStatistics,
simply invoke its constructor as follows

    obj = vtkDescriptiveStatistics



 Methods

The class vtkDescriptiveStatistics 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 vtkDescriptiveStatistics class.

* string = obj.GetClassName ()
* int = obj.IsA (string name)
* vtkDescriptiveStatistics = obj.NewInstance ()
* vtkDescriptiveStatistics = obj.SafeDownCast (vtkObject o)
* obj.SetUnbiasedVariance (int ) - Set/get whether the
  unbiased estimator for the variance should be used, or if
  the population variance will be calculated. The default is
  that the unbiased estimator will be used.
* int = obj.GetUnbiasedVariance () - Set/get whether the
  unbiased estimator for the variance should be used, or if
  the population variance will be calculated. The default is
  that the unbiased estimator will be used.
* obj.UnbiasedVarianceOn () - Set/get whether the unbiased
  estimator for the variance should be used, or if the
  population variance will be calculated. The default is
  that the unbiased estimator will be used.
* obj.UnbiasedVarianceOff () - Set/get whether the unbiased
  estimator for the variance should be used, or if the
  population variance will be calculated. The default is
  that the unbiased estimator will be used.
* obj.SetSignedDeviations (int ) - Set/get whether the
  deviations returned should be signed, or should only have
  their magnitude reported. The default is that signed
  deviations will be computed.
* int = obj.GetSignedDeviations () - Set/get whether the
  deviations returned should be signed, or should only have
  their magnitude reported. The default is that signed
  deviations will be computed.
* obj.SignedDeviationsOn () - Set/get whether the deviations
  returned should be signed, or should only have their
  magnitude reported. The default is that signed deviations
  will be computed.
* obj.SignedDeviationsOff () - Set/get whether the
  deviations returned should be signed, or should only have
  their magnitude reported. The default is that signed
  deviations will be computed.
* obj.SetNominalParameter (string name) - A convenience
  method (in particular for UI wrapping) to set the name of
  the column that contains the nominal value for the Assess
  option.
* obj.SetDeviationParameter (string name) - A convenience
  method (in particular for UI wrapping) to set the name of
  the column that contains the deviation for the Assess
  option.
* 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
  doxygen_ 1.8.1.1

