This function calculates the temporal speckle skewness matrix (S). Use as
  input data a 3D matrix created grouping NTIMES intensity matrices I(k)
  1<=k<=NTIMES

  I(k)=DATA(:,:,k)

  $MU = \frac{1}{NTIMES} \sum\limits_{k=1}^{NTIMES} I(k) \approx E[I(k)]$

  $SIGMA = \sqrt{ \frac{1}{NTIMES} \sum\limits_{k=1}^{NTIMES} (I(k)-MU)^2}$

  $S \approx E[\left(\frac{I(k)-MU}{SIGMA}\right)^3]$

  The function additionally returns the temporal standard deviation matrix 
  and temporal expected matrix.


  After starting the main routine just type the following command at the
  prompt:
  S       = graphskew(DATA);
  [S D]   = graphskew(DATA);
  [S D E] = graphskew(DATA);
    
  Input:
  DATA is the speckle data pack. Where DATA is a 3D matrix created grouping NTIMES 
       intensity matrices with NLIN lines and NCOL columns. When N=size(DATA), then
       N(1,1) represents NLIN and
       N(1,2) represents NCOL and
       N(1,3) represents NTIMES.
  SHOW [Optional] If SHOW is equal to string 'off', then the result will
  not be plotted.

  Output:
  K    returns the temporal speckle skewness matrix of image Data Pack.
  D    [Optional] returns the temporal standard deviation matrix of image Data Pack.
  E    [Optional] returns the temporal expected matrix of image Data Pack.


  For help, bug reports and feature suggestions, please visit:
  http://nongnu.org/bsltl

Package: bsltl