# msd

mean squared deviation This function is obsolete.

## 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`.

This function is obsolete. It is better to use stdev instead of `msd`. `msd(x) => stdev(x, "*", %nan)`, `msd(x, "r") => stdev(x, "r", %nan)`, `msd(x, "c") => stdev(x, "c", %nan)`.

## 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.

## History

5.5.0
Function tagged as obsolete. Will be removed in 5.5.1. Please use stdev instead.