lndMvn                package:bayesm                R Documentation

_C_o_m_p_u_t_e _L_o_g _o_f _M_u_l_t_i_v_a_r_i_a_t_e _N_o_r_m_a_l _D_e_n_s_i_t_y

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

     'lndMvn' computes the log of a Multivariate Normal Density.

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

     lndMvn(x, mu, rooti)

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

       x: density ordinate 

      mu: mu vector 

   rooti: inv of Upper Triangular Cholesky root of Sigma 

_D_e_t_a_i_l_s:

     z ~ N(mu,Sigma)

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

     log density value

_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 2. 
      <URL:
     http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html>

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

     'lndMvst'

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

     ##
     Sigma=matrix(c(1,.5,.5,1),ncol=2)
     lndMvn(x=c(rep(0,2)),mu=c(rep(0,2)),rooti=backsolve(chol(Sigma),diag(2)))

