def update_zeta_j_wrapper(args):
# parse arguments
curr_zeta_j, Y_j, alpha, beta, xi, tau = args
prop_zeta_j = np.empty(curr_zeta_j.shape)
prop_zeta_j[0] = sample_alpha_1_mh(curr_zeta_j[0], Y_j.T[0], alpha[0],
beta[0])
for i in range(1, curr_zeta_j.shape[0]):
prop_zeta_j[i] = sample_alpha_k_mh(
curr_zeta_j[i],
Y_j.T[i],
alpha[i],
beta[i],
xi[i - 1],
tau[i - 1],
)
return prop_zeta_j
def update_xi_l_wrapper(args):
return sample_alpha_k_mh(*args)
