SUMSKIPNAN adds all non-NaN values. 

 All NaN's are skipped; NaN's are considered as missing values. 
 SUMSKIPNAN of NaN's only  gives O; and the number of valid elements is return. 
 SUMSKIPNAN is also the elementary function for calculating 
 various statistics (e.g. MEAN, STD, VAR, RMS, MEANSQ, SKEWNESS, 
 KURTOSIS, MOMENT, STATISTIC etc.) from data with missing values.  
 SUMSKIPNAN implements the DIMENSION-argument for data with missing values.
 Also the second output argument return the number of valid elements (not NaNs) 
 
 Y = sumskipnan(x [,DIM])
 [Y,N,SSQ] = sumskipnan(x [,DIM])
 [...] = sumskipnan(x, DIM, W)
 
 x	input data 	
 DIM	dimension (default: [])
	empty DIM sets DIM to first non singleton dimension	
 W	weight vector for weighted sum, numel(W) must fit size(x,DIM)
 Y	resulting sum
 N	number of valid (not missing) elements
 SSQ	sum of squares

 the function FLAG_NANS_OCCURED() returns whether any value in x
  is a not-a-number (NaN)

 features:
 - can deal with NaN's (missing values)
 - implements dimension argument. 
 - computes weighted sum 
 - compatible with Matlab and Octave

 see also: FLAG_NANS_OCCURED, SUM, NANSUM, MEAN, STD, VAR, RMS, MEANSQ, 
      SSQ, MOMENT, SKEWNESS, KURTOSIS, SEM

Package: nan