cv1EMtrain              package:mclust              R Documentation

_S_e_l_e_c_t _d_i_s_c_r_i_m_i_n_a_n_t _m_o_d_e_l_s _u_s_i_n_g _c_r_o_s_s _v_a_l_i_d_a_t_i_o_n

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

     Leave-one-out cross validation given a dataset and labels for
     selected models.

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

     cv1EMtrain(data, labels, modelNames=NULL)

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

    data: A numeric vector or matrix of observations.

  labels: Labels for each element or row in the dataset.

modelNames: Vector of model names that should be tested. The default is
          to select all available model names.

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

     Returns a vector where each element is the the crossvalidated
     error rate for the dataset and labels corresponding to each model.

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

     C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal
     Mixture Modeling and Model-Based Clustering,  Technical Report no.
     504, Department of Statistics, University of Washington.

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

     C. Fraley

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

     'bicEMtrain'

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

     even <- seq(from=2, to=nrow(chickwts), by=2)
     round(cv1EMtrain(chickwts[even,1], labels=chickwts[even,2]), 1)

