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)