momMix                package:bayesm                R Documentation

_C_o_m_p_u_t_e _P_o_s_t_e_r_i_o_r _E_x_p_e_c_t_a_t_i_o_n _o_f _N_o_r_m_a_l _M_i_x_t_u_r_e _M_o_d_e_l _M_o_m_e_n_t_s

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

     'momMix' averages the moments of a normal mixture model over MCMC
     draws.

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

     momMix(probdraw, compdraw)

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

probdraw: R x ncomp list of draws of mixture probs 

compdraw: list of length R of draws of mixture component moments 

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

     R is the number of MCMC draws in argument list above. 
      ncomp is the number of mixture components fitted.
      compdraw is a list of lists of lists with mixture components.  
      compdraw[[i]] is ith draw. 
      compdraw[[i]][[j]][[1]] is the mean parameter vector for the jth
     component, ith MCMC draw. 
      compdraw[[i]][[j]][[2]] is the UL decomposition of Sigma^{-1} for
     the jth component, ith MCMC draw.

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

     a list of the following items ... 

     mu : Posterior Expectation of Mean

  sigma : Posterior Expecation of Covariance Matrix

     sd : Posterior Expectation of Vector of Standard Deviations

   corr : Posterior Expectation of Correlation 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 5. 
      <URL:
     http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html>

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

     'rmixGibbs'

