robustt              package:LearnBayes              R Documentation

_G_i_b_b_s _s_a_m_p_l_i_n_g _f_o_r _a _r_o_b_u_s_t _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 a robust t sampling model with
     location mu, scale sigma, and degrees of freedom v

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

     robustt(y,v,m)

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

       y: vector of data values

       v: degrees of freedom for t model

       m: the number of cycles of the Gibbs sampler

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

      mu: vector of simulated values of mu

      s2: vector of simulated values of sigma2

     lam: matrix of simulated draws of lambda, where each row
          corresponds to a single draw

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

     Jim Albert

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

     data=c(-67,-48,6,8,14,16,23,24,28,29,41,49,67,60,75)
     fit=robustt(data,4,1000)

