


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