transplantpost          package:LearnBayes          R Documentation

_L_o_g _p_o_s_t_e_r_i_o_r _o_f _a _P_a_r_e_t_o _m_o_d_e_l _f_o_r _s_u_r_v_i_v_a_l _d_a_t_a

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

     Computes the log posterior density of (log tau, log lambda, log p)
      for a Pareto model for survival data

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

     transplantpost(theta,data)

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

   theta: matrix of parameter values where each row represents a value
          of (log tau, log lambda, log p)

    data: data matrix with columns survival time, transplant indicator,
          time to transplant, and censoring indicator

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

     vector of values of the log posterior where each value corresponds
     to each row of the parameters in theta

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

     Jim Albert

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

     data(stanfordheart)
     par1=c(0,3,-1)
     par2=c(0,2,0)
     theta=rbind(par1,par2)
     transplantpost(theta,stanfordheart)

