Method ao/mve


  MVE: Minimum Volume Ellipsoid estimator
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  DESCRIPTION: Minimum Volume Ellipsoid estimator 
               for robust outlier detection.
 
  CALL:        ao_out = mve(ao_in);
               ao_out = mve(ao_in, pl);
  
  The ao_out is the weighted covariance matrix of the data. Other
  information, like the weighted mean, the volume and the center of 
  the ellipsoid are stored in ao_out.procinfo.
 
  Uses the method described in P. Rousseeuw "Robust Regresion and outlier
  Detection, 1987" in pages 258-261. 
 
  **Also in http://www.kimvdlinde.com/professional/pcamve.html
 
  NK 2013  
 
  Parameters Description
 
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Method Details
Access public
Defining Class ao
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
PCA 0
  • 0
  • 1
Set to true to perform Principal Component Analysis.
M 100 none Number 'm' of random sub-samples to be drawn from the data. If set to zero, the method will attempt to proceed taking into acount all possible sub-samples. ATTENTION: If the data-set is too large, this computation is practically unfeasible!
DISCARD 0 none Discard the first number of samples.
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Some information of the method ao/mve are listed below:
Class name ao
Method name mve
Category Signal Processing
Package name ltpda
VCS Version 8ab8cbbc4bccf7543491a24448f4aae0b1be1c43
Min input args 1
Max input args -1
Min output args 1
Max output args -1




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