RMS calculates the root mean square
   can deal with complex data. 

 y = rms(x,DIM,W)

 DIM	dimension
	1 STD of columns
	2 STD of rows
 	N STD of  N-th dimension 
	default or []: first DIMENSION, with more than 1 element
 W	weights to compute weighted s.d. (default: [])
	if W=[], all weights are 1. 
	number of elements in W must match size(x,DIM) 

 y	estimated standard deviation

 features:
 - can deal with NaN's (missing values)
 - weighting of data 
 - dimension argument also in Octave
 - compatible to Matlab and Octave

 see also: SUMSKIPNAN, MEAN

Package: nan