estBlackBox2              package:dse1              R Documentation

_E_s_t_i_m_a_t_e _a _T_S_m_o_d_e_l

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

     Estimate a TSmodel.

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

         estBlackBox2(data, estimation='estVARXls', 
               lag.weight=.9, 
               reduction='MittnikReduction', 
               criterion='taic', 
               trend=FALSE, 
               subtract.means=FALSE,  re.add.means=TRUE, 
               standardize=FALSE, verbose=TRUE, max.lag=12)

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

    data: a TSdata object.

estimation: a character string indicating the estimation method to use.

lag.weight: weighting to apply to lagged observations. 

reduction: character string indicating reduction procedure to use. 

criterion: criterion to be used for model  selection. see
          'informationTestsCalculations'.

   trend: if TRUE include a trend in the model. 

subtract.means: if TRUE the mean is subtracted from the data before
          estimation.

re.add.means: if subtract.means is TRUE then if re.add.means is TRUE 
          the estimated model is converted back to a model for data
          without the mean subtracted.

standardize: if TRUE the data is transformed so that all variables have
          the same variance.

 verbose: if TRUE then additional information from the estimation and 
          reduction procedures is printed.

 max.lag: The number of lags to include in the VAR estimation.

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

     A model is estimated and then a reduction procedure applied. The
     default estimation procedure is least squares estimation of a VAR
     model with lagged values weighted. This procedure is discussed in
     Gilbert (1995).

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

     A TSestModel.

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

     Gilbert, P.D. (1995) "Combining VAR Estimation and State Space 
     Model Reduction for Simple Good Predictions" _J. of Forecasting: 
     Special Issue on VAR Modelling_. 14:229-250.

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

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

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

     if(is.R()) data("eg1.DSE.data.diff", package="dse1")
     z <-  estBlackBox2(eg1.DSE.data.diff)

