toSS                  package:dse1                  R Documentation

_C_o_n_v_e_r_t _t_o _S_t_a_t_e _S_p_a_c_e _M_o_d_e_l

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

     Convert a model to state space form.

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

         toSS(model, ...)
         ## S3 method for class 'ARMA':
         toSS(model, ...)
         ## S3 method for class 'SS':
         toSS(model, ...)
         ## S3 method for class 'TSestModel':
         toSS(model, ...)
         
         toSSaugment(model, ...)
         ## S3 method for class 'ARMA':
         toSSaugment(model, fuzz=1e-14, ...)
         ## S3 method for class 'TSestModel':
         toSSaugment(model, ...)
         
         toSSnested(model, ...)
         ## S3 method for class 'ARMA':
         toSSnested(model, n=NULL, Aoki=FALSE, ...)
         ## S3 method for class 'SS':
         toSSnested(model, n=NULL, Aoki=FALSE, ...)
         ## S3 method for class 'TSestModel':
         toSSnested(model, ...)
         
         

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

   model: An object of class TSmodel.

       n: If n is specified then it is used as the state dimension when
          the  markov parameter conversion technique is required.

    Aoki: logical indicating if Aoki's method (which does not work in
          general) should be tried.

    fuzz: if the zero lag term of polynomials A and B are within fuzz
          of the identitity matrix then they are not inverted. (i.e.
          they are assumed to be identity.)

     ...: arguments to be passed to other methods.

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

     If the order of the AR polynomial equals or exceeds the MA 
     polynomial (and the input polynomial) then the model is converted 
     by state augmentation. Otherwise, it is converted by approximating
      the markov coefficients a la Mittnik.  (This may not always work
     very well. Compare the results to check.)

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

     A state space model in an object of class 'SS' 'TSmodel'.

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

     if(is.R()) data("eg1.DSE.data.diff", package="dse1")
     model <- estVARXls(eg1.DSE.data.diff)
     model <- toSS(model)

