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

- sumskipnan SUMSKIPNAN adds all non-NaN values.

- naninsttest NANINSTTEST checks whether the functions from NaN-toolbox have been

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