Joint Gibbs update of the social-relations additive row effects a
and the additive-effect covariance Sab under a probit (binary)
likelihood. Given the latent normal scores Z and the observed 0/1
matrix Y, each row effect is redrawn from its Gaussian full
conditional (conditioned on the column effects b through Sab)
truncated to the interval that keeps every latent score sign-compatible with
the observed responses. The covariance Sab is then refreshed from its
inverse-Wishart full conditional.
raSab_bin_fc(
Z,
Y,
a,
b,
Sab,
Sab0 = NULL,
eta0 = NULL,
SS = round(sqrt(nrow(Z)))
)list with the updated Z, a and Sab
square matrix of current latent normal scores
square binary relational matrix (NA entries allowed)
current value of the row effects
current value of the column effects
current 2x2 covariance of the additive effects
prior inverse-scale matrix (defaults to the 2x2 identity)
prior degrees of freedom (defaults to 4)
number of inner Gibbs sweeps
lame authors