msd - Mean squared deviation (original) (raw)
Scilab 5.3.3
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Scilab help >> Statistics > msd
Calling Sequence
y=msd(x) y=msd(x,'r') or m=msd(x,1) y=msd(x,'c') or m=msd(x,2)
Arguments
x
real or complex vector or matrix
Description
This function computes the mean squared deviation of the values of a vector or matrix x.
For a vector or a matrix x, y=msd(x) returns in the scalar y the mean squared deviation of all the entries of x.
y=msd(x,'r') (or, equivalently, y=msd(x,1)) is the rowwise mean squared deviation. It returns in each entry of the row vector y the mean squared deviation of each column of x.
y=msd(x,'c') (or, equivalently, m=msd(x,2)) is the columnwise mean squared deviation. It returns in each entry of the column vector y the mean squared deviation of each row of x.
Examples
x=[0.2113249 0.0002211 0.6653811;0.7560439 0.3303271 0.6283918] m=msd(x) m=msd(x,'r') m=msd(x,'c')
Bibliography
Wonacott, T.H. & Wonacott, R.J.; Introductory Statistics, fifth edition, J.Wiley & Sons, 1990.