AAR                  package:tsDyn                  R Documentation

_A_d_d_i_t_i_v_e _n_o_n_l_i_n_e_a_r _a_u_t_o_r_e_g_r_e_s_s_i_v_e _m_o_d_e_l

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

     Additive nonlinear autoregressive model.

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

     aar(x, m, d=1, steps=d, series)

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

       x: time series 

m, d, steps: embedding dimension, time delay, forecasting steps 

  series: time series name (optional) 

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

     Nonparametric additive autoregressive model of the form:

               x[t+steps] = mu + sum_j s_j(x[t-(j-1)d])


     where s_j are nonparametric univariate functions of lagged time
     series values. They are represented by cubic regression splines.
     s_j are estimated together with their level of smoothing using
     routines in the 'mgcv' package (see references).

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

     An object of class 'nlar', subclass 'aar', i.e. a list with mostly
     internal structures for the fitted 'gam' object.

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

     Antonio, Fabio Di Narzo

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

     Wood, mgcv:GAMs and Generalized Ridge Regression for R. R News
     1(2):20-25 (2001)

     Wood and Augustin, GAMs with integrated model selection using
     penalized regression splines and applications to environmental
     modelling. Ecological Modelling 157:157-177 (2002)

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

     #fit an AAR model:
     mod <- aar(log(lynx), m=3)
     #Summary informations:
     summary(mod)
     #Diagnostic plots:
     plot(mod)

