hiergibbs             package:LearnBayes             R Documentation

_G_i_b_b_s _s_a_m_p_l_i_n_g _f_o_r _a _h_i_e_r_a_r_c_h_i_c_a_l _r_e_g_r_e_s_s_i_o_n _m_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     Implements Gibbs sampling for estimating a two-way table of means
     under a hierarchical regression model.

_U_s_a_g_e:

     hiergibbs(data,m)

_A_r_g_u_m_e_n_t_s:

    data: data matrix with columns observed sample means, sample sizes,
          and values of two covariates

       m: number of cycles of Gibbs sampling

_V_a_l_u_e:

    beta: matrix of simulated values of regression vector

      mu: matrix of simulated values of cell means

     var: vector of simulated values of second-stage prior variance

_A_u_t_h_o_r(_s):

     Jim Albert

_E_x_a_m_p_l_e_s:

     data(iowagpa)
     m=1000
     s=hiergibbs(iowagpa,m)

