Dispmat: Difference between revisions

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Jeremy
(Importing text file)
imported>Jeremy
(Importing text file)
 
Line 12: Line 12:
Calculates a dispersion matrix, as defined by the options, of datasets x and y.
Calculates a dispersion matrix, as defined by the options, of datasets x and y.


====INPUTS====
====Inputs====


* '''x''' : (2-way array class "double" or "dataset") x-matrix for dispersion matrix.
* '''x''' : (2-way array class "double" or "dataset") x-matrix for dispersion matrix.
Line 18: Line 18:
* '''y''' : (2-way array class "double" or "dataset") y-matrix for dispersion matrix.
* '''y''' : (2-way array class "double" or "dataset") y-matrix for dispersion matrix.


====OUTPUTS====
====Outputs====


* '''c''' : dispersion matrix, as defined by options.
* '''c''' : dispersion matrix, as defined by options.

Latest revision as of 16:33, 3 September 2008

Purpose

Calculates the dispersion matrix of two spectral data sets.

Synopsis

[c,meansx,meansy,stdsx,stdsy] = dispmat(x,y,options);

Description

Calculates a dispersion matrix, as defined by the options, of datasets x and y.

Inputs

  • x : (2-way array class "double" or "dataset") x-matrix for dispersion matrix.
  • y : (2-way array class "double" or "dataset") y-matrix for dispersion matrix.

Outputs

  • c : dispersion matrix, as defined by options.
  • meansx : mean of x.
  • meansy : mean of y.
  • stdsx : standard deviation of x.
  • stdsy : standard deviation of y.

Options

  • offsetx : [0] offset for x.
  • offsety : [0] offset for y.
  • dispersion : [1] dispersion matrix calculated:
  • 1: standardized, offset corrected
  • 2: length sqrt(nrows), offset corrected
  • 3: purity about mean, offset corrected
  • 4: purity about origin, offset corrected
  • 5: asynchronous, offset corrected

See Also

corrspec, corrspecengine, purity