bestTSestModel             package:dse1             R Documentation

_S_e_l_e_c_t _B_e_s_t _M_o_d_e_l

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

     Select the best model.

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

         bestTSestModel(models, sample.start=10, sample.end=NULL,
          criterion='aic', verbose=TRUE)

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

  models: a list of TSestModels.

sample.start: the starting point to use for  calculating  information
          criteria.

sample.end: the end point to use for  calculating  information
          criteria.

criterion: Criterion to be used for model  selection. see
          'informationTestsCalculations'. 'taic' would  be a better
          default but this is not available for VAR and ARMA models.

 verbose: if TRUE then additional information is printed.

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

     Information criteria are calculated and the best model returned.

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

     A TSestModel

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

     'estBlackBox1', 'estBlackBox2' 'estBlackBox3' 'estBlackBox4'
     'informationTestsCalculations'

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

     if(is.R()) data("eg1.DSE.data.diff", package="dse1")
     models <- list(estVARXls(eg1.DSE.data.diff), estVARXar(eg1.DSE.data.diff))
     z <-  bestTSestModel(models)

