# AMS

From betafunctions v1.2.2
by Haakon Haakstad

##### Alpha Shape Parameter Given Mean and Variance of a Standard Beta PDD.

Calculates the Alpha value required to produce a Standard (two-parameter) Beta probability density distribution with defined mean and variance or standard deviation.

##### Usage

`AMS(mean, var, sd = NULL)`

##### Arguments

- mean
The mean of the target Standard Beta probability density distribution.

- var
The variance of the target Standard Beta probability density distribution.

- sd
The standard deviation of the target Standard Beta probability density distribution.

##### Value

A numeric value representing the required value for the Alpha shape-parameter in order to produce a Standard Beta probability density distribution with the target mean and variance.

##### Examples

```
# NOT RUN {
# Generate some fictional data. Say, 100 individuals take a test with a
# maximum score of 100 and a minimum score of 0, rescaled to proportion
# of maximum.
set.seed(1234)
testdata <- rbinom(100, 100, rBeta.4P(100, .25, .75, 5, 3)) / 100
hist(testdata, xlim = c(0, 100))
# To find the alpha shape-parameter of a Standard (two-parameter) Beta
# distribution with the same mean and variance as the observed-score
# distribution using AMS():
AMS(mean(testdata), var(testdata))
# }
```

*Documentation reproduced from package betafunctions, version 1.2.2, License: CC0*

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