Description Usage Arguments Details Value Author(s) References See Also Examples
Calculating the mean square successive difference
1 | mssd (x)
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x |
a |
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.
Single numeric value (the mean square successive difference, δ^2).
Thomas Wieland
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | 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
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[1] 20
[1] 20
[1] 8.660254
[1] 8.660254
[1] 0.4330127
[1] 0.4330127
[1] 25
[1] 212.5
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