# MLM

From betafunctions v1.4.0
by Haakon Haakstad

##### Most Likely Mean of the Standard Beta PDD, Given that the Observation is Considered the Most Likely Observation of the Standard Beta PDD (i.e., Mode).

Assuming a prior Standard (two-parameter) Beta Distribution, returns the expected mean of the distribution under the assumption that the observed value is the most likely value of the distribution.

##### Usage

`MLM(alpha, beta, x = NULL, n = NULL)`

##### Arguments

- alpha
Observed alpha value for fitted Standard Beta PDD.

- beta
Observed beta value for fitted Standard Beta PDD.

- x
Observed proportion-correct outcome.

- n
Test-length.

##### Value

The expected mean of the Standard Beta probability density distribution, for which the observed mean is the most likely value.

##### Examples

```
# NOT RUN {
# Assuming a prior Standard (two-parameter) Beta distribution is fit, which
# yield an alpha parameter of 10 and a beta parameter of 8, calculate the
# true-mean most likely to have produced the observations:
MLM(a = 10, b = 8)
# }
```

*Documentation reproduced from package betafunctions, version 1.4.0, License: CC0*

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