nlar                  package:tsDyn                  R Documentation

_N_o_n-_l_i_n_e_a_r _t_i_m_e _s_e_r_i_e_s _m_o_d_e_l, _b_a_s_e _c_l_a_s_s _d_e_f_i_n_i_t_i_o_n

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

     Generic non-linear autogregressive model class constructor.

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

     nlar(str, coefficients, fitted.values, residuals, k, model.specific=NULL, ...)

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

     str: a 'nlar.struct' object, i.e. the result of a call to
          'nlar.struct'

coefficients, fitted.values, residuals, k, model.specific: internal
          structure 

     ...: further model specific fields 

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

     Constructor for the generic 'nlar' model class. On a fitted object
     you can call some generic methods. For a list of them, see
     'nlar-methods'.

     An object of the 'nlar' class is a list of (at least) components:

     _s_t_r 'nlar.struct' object, encapsulating general infos such as time
          series length, embedding parameters, forecasting steps, model
          design matrix 

     _c_o_e_f_f_i_c_i_e_n_t_s a named vector of model estimated/fixed coefficients  

     _k total number of estimated coefficients 

     _f_i_t_t_e_d._v_a_l_u_e_s model fitted values 

     _r_e_s_i_d_u_a_l_s model residuals 

     _m_o_d_e_l._s_p_e_c_i_f_i_c (optional) model specific additional infos

     A 'nlar' object normally should also have a model-specific
     subclass (i.e., 'nlar' is a virtual class).

     Each subclass should define at least a 'print'  and, hopefully, a
     'oneStep' method, which is used by 'predict.nlar' to iteratively
     extend ahead the time series.

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

     An object of class 'nlar'. nlar-methods for a list of available
     methods.

_A_u_t_h_o_r(_s):

     Antonio, Fabio Di Narzo

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

     Non-linear time series models in empirical finance, Philip Hans
     Franses and Dick van Dijk, Cambridge: Cambridge University Press
     (2000).

     Non-Linear Time Series: A Dynamical Systems Approach, Tong, H.,
     Oxford: Oxford University Press (1990).

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

     'availableModels' for currently available built-in models.
     nlar-methods for available 'nlar' methods.

