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# 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**This function is obsolete.**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This function is obsolete.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

Version | Description |

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

## Comments

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