smoother                package:dse1                R Documentation

_E_v_a_l_u_a_t_e _a _s_m_o_o_t_h_e_r _w_i_t_h _a _T_S_m_o_d_e_l

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

     Evaluate a state space model.

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

         smoother(model, data, compiled=.DSECOMPILED))

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

   model: An object of class `TSestModel' or 'TSmodel' with a model of 
          class `non.innov' 'SS' 'TSmodel'. If filter informatin is not
          provided  (i.e. in a TSestModel) then smoother runs the
          Kalman filter (l.SS) first.

    data: A TSdata object.

compiled: If T the compiled version of the code is used. Otherwise the
          S version is used.

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

     Smoother takes the filtered state `estimates$state' and produces a
     smoothed  estimate of the state (sometimes called a two sided
     filter).

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

     An object of class TSestModel with an additional element `smooth'.
      `smooth' is a list of `state', the smoothed state, and  `track',
     the smoothed tracking  error. The result will also contain the
     element `filter' with `state' and `track' (which may or may not
     have been in the original arguement).

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

     `l', `l.SS' `TSmodel' `TSestModel.object'

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

     if(is.R()) data("eg1.DSE.data.diff", package="dse1")
     #smoother requires an non-innovations form model
     model <- TSmodel(to.SS.Chol(est.VARX.ls(eg1.DSE.data.diff))) 
     smoothed.model <- smoother(model, eg1.DSE.data.diff, compiled=F)

