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Справка Scilab >> Statistics > Descriptive Statistics > msd

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mean squared deviation This function is obsolete.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This function is obsolete.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

ВерсияОписание
5.5.0 Function tagged as obsolete. Will be removed in 5.5.1. Please use stdev instead.
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Copyright (c) 1989-2012 (INRIA)
Copyright (c) 1989-2007 (ENPC)
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Last updated:
Thu Oct 02 14:01:07 CEST 2014