# mssd: Mean square successive difference In REAT: Regional Economic Analysis Toolbox

## Description

Calculating the mean square successive difference

## Usage

 `1` ```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).

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.

`var2`, `sd2`, `cv`

## Examples

 ``` 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 ```

### Example output

``` 20
 20
 8.660254
 8.660254
 0.4330127
 0.4330127
 25
 212.5
```

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