# Calculate Layman metrics on Bayesian postrior samples of a community

### Description

This function loops over the posterior distribution of group means within each community and generates the corresponding Bayesian estimate of the 6 Layman metrics.

### Usage

1 | ```
bayesianLayman(mu.post)
``` |

### Arguments

`mu.post` |
a list of length n.communities, with each list element
containing the estimated means of the groups comprising that community. The
typical workflow to generate mu.post follows. The
Bayesian ellipses are fitted using |

### Value

A list of length n.communities, with each element containing a matrix of 6 columns, each representing the Bayesian posterior distribution of the 6 Layman metrics for each of the posterior draws recorded by the fitting process (i.e. which determines the number of rows in this matrix).