extract_cor_cov_samps.RdBecause of the decomposition of the beta covariance matrix into scale and
correlation, it can be hard to interpret the posteriors. This function will
return an array which is a T-by-T-by-Samples array (where T is the number of
coefficients). It is then easy to use apply to get posterior means for each
cell in the matrix (e.g., apply(Sigma_Array, c(1, 2), mean)).
extract_cor_cov_samps(splt_fit, par_subscript = "ep")
| splt_fit | a fit of class stanfit |
|---|---|
| par_subscript | the subscript for the L_Omega_subscript and tau_subscript parameters |
a list with both Omega (correlation matrix) and Sigma (covariance matrix) sample arrays.