blinreg              package:LearnBayes              R Documentation

_S_i_m_u_l_a_t_i_o_n _f_r_o_m _B_a_y_e_s_i_a_n _l_i_n_e_a_r _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:

     Gives a simulated sample from the joint posterior distribution of
     the regression vector and the error standard deviation for a
     linear regression model with a noninformative prior.

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

     blinreg(y,X,m)

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

       y: vector of responses

       X: design matrix

       m: number of simulations desired

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

    beta: matrix of simulated draws of beta where each row corresponds
          to one draw

   sigma: vector of simulated draws of the error standard deviation

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

     Jim Albert

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

     chirps=c(20,16.0,19.8,18.4,17.1,15.5,14.7,17.1,15.4,16.2,15,17.2,16,17,14.1)
     temp=c(88.6,71.6,93.3,84.3,80.6,75.2,69.7,82,69.4,83.3,78.6,82.6,80.6,83.5,76.3)
     X=cbind(1,chirps)
     m=1000
     s=blinreg(temp,X,m)

