mssd: Mean square successive difference

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Calculating the mean square successive difference

Usage

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mssd (x)

Arguments

x

a numeric vector arranged in chronological order

Details

The mean square successive difference, δ^2, is a dimensionless measure of variability over time (von Neumann et al. 1941). It can be used for assessing the volatility of a variable with respect to different subjects/groups.

Value

Single numeric value (the mean square successive difference, δ^2).

Author(s)

Thomas Wieland

References

Von Neumann, J./Kent, R. H./Bellinson, H. R./Hart, B. I. (1941): “The mean square successive difference”. In: The Annals of Mathematical Statistics, 12, 2, p. 153-162.

See Also

var2, sd2, cv

Examples

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data1 <- c(10,10,10,20,20,20,30,30,30)
# stable growth
data2 <- c(20,10,30,10,30,20,30,20,10)
# high variability

# Means:
mean2(data1)
mean2(data2)
# Same means

# Standard deviation:
sd2(data1)
sd2(data2)
# Coefficient of variation:
cv(data1)
cv(data2)
# Measures of statistical dispersion are equal

mssd(data1)
mssd(data2)
# high differences in variability

Example output

[1] 20
[1] 20
[1] 8.660254
[1] 8.660254
[1] 0.4330127
[1] 0.4330127
[1] 25
[1] 212.5

REAT documentation built on Nov. 21, 2019, 5:08 p.m.