Draws the covariance matrix of the stacked multiplicative row/column effects \([U, V]\) from its full conditional inverse-Wishart distribution in the AME model.
rSuv_fc(U, V, Suv0=NULL, kappa0=NULL)The sampled 2R x 2R covariance matrix for \([U, V]\): the leading R x R block is the covariance of U, the trailing R x R block is the covariance of V, and the off-diagonal blocks are the U-V cross-covariances.
matrix of multiplicative row effects (n x R).
matrix of multiplicative column effects (n x R).
prior scale matrix (2R x 2R). Defaults to the identity, a weakly informative choice.
prior degrees of freedom. Defaults to 2 + 2R, the smallest value giving a proper prior for a 2R x 2R covariance.
lame authors
Stacking the effects columnwise as \(W = [U, V]\), the conjugate
inverse-Wishart update combines the prior scale kappa0 * Suv0
with the residual cross-product crossprod(W) and adds the n
observed rows to the degrees of freedom. A draw from the inverse
Wishart is obtained by drawing from the Wishart with the inverted
scale matrix (via rwish) and inverting the result.