simmvp                package:bayesm                R Documentation

_S_i_m_u_l_a_t_e _f_r_o_m _M_u_l_t_i_v_a_r_i_a_t_e _P_r_o_b_i_t _M_o_d_e_l

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

     'simmvp' simulates from the multivariate probit model.

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

     simmvp(X, p, n, beta, sigma)

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

       X: n*p x length(beta) Design matrix 

       p: dimension of the MVP

       n: number of observations 

    beta: coefficient vector 

   sigma: p x p covariance matrix 

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

     a list of  

       y: p*n vector of 0/1 binary outcomes

       X: Design matrix

    beta: coefficients

   sigma: covariance matrix 

_W_a_r_n_i_n_g:

     This routine is a utility routine that does *not* check the input
     arguments for proper dimensions and type.

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

     Peter Rossi, Graduate School of Business, University of Chicago,
     Peter.Rossi@ChicagoGsb.edu.

_R_e_f_e_r_e_n_c_e_s:

     For further discussion, see _Bayesian Statistics and Marketing_ by
     Rossi, Allenby and McCulloch, Chapter 4. 
      <URL:
     http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html>

_S_e_e _A_l_s_o:

     'rmvpGibbs'

