The problem is that omega
in your case is matrix
of dimensions 1 * 1
. You should convert it to a vector if you wish to multiply t(X) %*% X
by a scalar (that is omega
)
In particular, you'll have to replace this line:
omega = rgamma(1,a0,1) / L0
with:
omega = as.vector(rgamma(1,a0,1) / L0)
everywhere in your code. It happens in two places (once inside the loop and once outside). You can substitute as.vector(.)
or c(t(.))
. Both are equivalent.
Here's the modified code that should work:
gibbs = function(data, m01 = 0, m02 = 0, k01 = 0.1, k02 = 0.1,
a0 = 0.1, L0 = 0.1, nburn = 0, ndraw = 5000) {
m0 = c(m01, m02)
C0 = matrix(nrow = 2, ncol = 2)
C0[1,1] = 1 / k01
C0[1,2] = 0
C0[2,1] = 0
C0[2,2] = 1 / k02
beta = mvrnorm(1,m0,C0)
omega = as.vector(rgamma(1,a0,1) / L0)
draws = matrix(ncol = 3,nrow = ndraw)
it = -nburn
while (it < ndraw) {
it = it + 1
C1 = solve(solve(C0) + omega * t(X) %*% X)
m1 = C1 %*% (solve(C0) %*% m0 + omega * t(X) %*% y)
beta = mvrnorm(1, m1, C1)
a1 = a0 + n / 2
L1 = L0 + t(y - X %*% beta) %*% (y - X %*% beta) / 2
omega = as.vector(rgamma(1, a1, 1) / L1)
if (it > 0) {
draws[it,1] = beta[1]
draws[it,2] = beta[2]
draws[it,3] = omega
}
}
return(draws)
}