featherForecasts            package:dse2            R Documentation

_M_u_l_t_i_p_l_e _H_o_r_i_z_o_n-_S_t_e_p _A_h_e_a_d _F_o_r_e_c_a_s_t_s

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

     Calculate multiple horizon-step ahead forecasts.

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

         featherForecasts(obj, ...)
         ## S3 method for class 'TSestModel':
         featherForecasts(obj, data=NULL, ...)
         ## S3 method for class 'TSdata':
         featherForecasts(obj, model, ...)
         ## S3 method for class 'TSmodel':
         featherForecasts(obj, data, horizon=36,
                  from.periods =NULL, ...)
         is.featherForecasts(obj)

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

     obj: an object of class TSmodel.

    data: an object of class TSdata.

   model: an object of class TSmodel.

from.periods: the starting points to use for forecasts.

 horizon: the number of periods to forecast.

     ...: for a TSmodel additional arguments are passed to 'l()'

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

     Calculate multiple horizon-step ahead forecasts  ie. use the
     samples indicated by from.periods to calculate forecasts for 
     horizon periods. Thus, for example, the result of
     featherForecasts(model, data, from.periods=c(200,250,300)) would
     be forecasts for 1 through 36 steps ahead (the default), starting
     at the 200th,250th, and 300th point of outputData(data). This
     function assumes that inputData(data) (the exogenous  variable) is
     as long as necessary for the most future forecast.

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

     The result is a list of class featherForecasts with elements
     'model' (a  TSestModel), 'data', 'from.periods',
     'featherForecasts'. The element 'featherForecasts' is a list with
     length(from.periods) elements, each of which is a tframed matrix.
     There is a plot method for this class.

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

     'forecast', 'horizonForecasts'

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

     if(is.R()) data("egJofF.1dec93.data", package="dse1")
     model <- estVARXls(egJofF.1dec93.data)
     pr <- featherForecasts(model, egJofF.1dec93.data)
     tfplot(pr)

