Fit Bayesian bivariate normal distributions to each group in each community
This function loops over each community and then loops over each group member, fitting a Bayesian multivariate (bivariate in this case) normal distribution to each group of data. Not intended for direct calling by users.
siberMVN(siber, parms, priors)
a siber object as created by
a list containing four items providing details of the
a list of three items specifying the priors to be passed to the jags model.
A list of length equal to the total number of groups in all
communities. Each entry is named 1.1 1.2... 2.1.. with the first number
designating the community, and the second number the group within that
community. So, 2.3 would be the third group within the second community.
Each list entry is a 6 x n matrix representing the back-transformed posterior
distributions of the bivariate normal distribution, where n is the number of
posterior draws in the saved sample. The first two columns are the back-
transformed means, and the remaining four columns are the covariance matrix
Sigma in vector format. This vector converts to the covariance matrix as
matrix(v[1:4], nrow = 2, ncol = 2).
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