Gibbs update of the latent sociomatrix Z for a fixed-rank-nomination
(FRN) outcome. Each row's latent values are drawn from truncated normals
whose bounds encode three rank constraints: nominated ties outrank
non-nominations, higher observed ranks map to larger latents, and a
non-nomination made with spare out-degree capacity must stay negative.
rZ_frn_fc(Z, EZ, rho, Y, YL, odmax, odobs)the updated square latent matrix Z.
current latent sociomatrix (square).
conditional mean matrix for Z.
within-dyad correlation.
square matrix of observed ranked nominations (0 = no tie, NA on the diagonal / missing).
matrix whose r-th column gives, per row, the column index
of the individual holding rank r (ascending preference).
scalar or per-row maximum number of nominations allowed.
per-row observed out-degree.
lame authors
The constraints realised are (1) Y[i,j] > Y[i,k] implies
Z[i,j] > Z[i,k], (2) Y[i,j] > 0 implies Z[i,j] > 0,
and (3) Y[i,j] == 0 with odobs[i] < odmax[i] implies
Z[i,j] < 0.