bicEMtrain              package:mclust              R Documentation

_S_e_l_e_c_t _m_o_d_e_l_s _i_n _d_i_s_c_r_i_m_i_n_a_n_t _a_n_a_l_y_s_i_s _u_s_i_n_g _B_I_C

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

     For the ten available discriminant models the BIC is calulated.
     The models for one-dimensional data are "E" and "V"; for higher
     dimensions they are "EII", "VII", "EEI", "VEI", "EVI", "VVI",
     "EEE", "EEV", "VEV" and "VVV". This function is much faster than
     'cv1EMtrain'.

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

     bicEMtrain(data, labels, modelNames)

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

    data: A data matrix

  labels: Labels for each row in the data matrix

modelNames: Vector of model names that should be tested.

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

     Returns a vector where each element is the BIC for the
     corresponding model.

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

     C. Fraley

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

     'cv1EMtrain'

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

     data(lansing)
     odd <- seq(from=1, to=nrow(lansing), by=2)
     round(bicEMtrain(lansing[odd,-3], labels=lansing[odd, 3]), 1)

