I am trying to set up a hierarchical model. My model needs to derive the site-specific mean and covariance between two variables at N different sites, while they also adhere to the global pattern between sites.
I am using the LKJ prior to sample the covariance matrix per site. However, the hyperparameter of the LKJ prior, eta, is only used to define the shape of the marginal distribution of Ri,j (R is the correlation matrix between my two variables), which is always centered around 0. How can I implement a global hyperparameter, so that the center of the marginal distribution of Ri,j changes, according to the pattern met across sites.