Conditional simulation of additive effects and regression coefficients

Simulates from the joint full conditional distribution of (beta,a,b) in a social relations regression model

Usage

rbeta_ab_fc(
  Z,
  Sab,
  rho,
  X = NULL,
  s2 = 1,
  offset = 0,
  iV0 = NULL,
  m0 = NULL,
  g = length(Z)
)

Z: n X n normal relational matrix
Sab: row and column covariance
rho: dyadic correlation
X: n x n x p covariate array
s2: dyadic variance
offset: a matrix of the same dimension as Z. It is assumed that Z-offset follows a SRRM, so the offset should contain any multiplicative effects (such as U%*% t(V) )
iV0: prior precision matrix for regression parameters
m0: prior mean vector for regression parameters
g: prior variance scale for g-prior when iV0 is unspecified

Peter Hoff