COVM generates covariance matrix
 X and Y can contain missing values encoded with NaN.
 NaN's are skipped, NaN do not result in a NaN output. 
 The output gives NaN only if there are insufficient input data

 COVM(X,Mode);
      calculates the (auto-)correlation matrix of X
 COVM(X,Y,Mode);
      calculates the crosscorrelation between X and Y
 COVM(...,W);
	weighted crosscorrelation 

 Mode = 'M' minimum or standard mode [default]
 	C = X'*X; or X'*Y correlation matrix

 Mode = 'E' extended mode
 	C = [1 X]'*[1 X]; % l is a matching column of 1's
 	C is additive, i.e. it can be applied to subsequent blocks and summed up afterwards
 	the mean (or sum) is stored on the 1st row and column of C

 Mode = 'D' or 'D0' detrended mode
	the mean of X (and Y) is removed. If combined with extended mode (Mode='DE'), 
 	the mean (or sum) is stored in the 1st row and column of C. 
 	The default scaling is factor (N-1). 
 Mode = 'D1' is the same as 'D' but uses N for scaling. 

 C = covm(...); 
 	C is the scaled by N in Mode M and by (N-1) in mode D.
 [C,N] = covm(...);
	C is not scaled, provides the scaling factor N  
	C./N gives the scaled version. 

 see also: DECOVM, XCOVF

Package: nan