bayesianLayman: Calculate Layman metrics on Bayesian postrior samples of a...

Description Usage Arguments Value

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 siberEllipses, then the posterior means (centre of mass of each group) is extracted using extractPosteriorMeans. See the example below.

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).



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