nlar methods              package:tsDyn              R Documentation

_n_l_a_r _m_e_t_h_o_d_s

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

     Generic 'nlar' methods

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

     ## S3 method for class 'nlar':
     AIC(object, ...)
     ## S3 method for class 'nlar':
     coef(object, ...)
     ## S3 method for class 'nlar':
     fitted(object, ...)
     ## S3 method for class 'nlar':
     MAPE(object, ...)
     ## S3 method for class 'nlar':
     mse(object, ...)
     ## S3 method for class 'nlar':
     print(x, digits = max(3, getOption("digits") - 3), ...)
     ## S3 method for class 'nlar':
     residuals(object, ...)
     ## S3 method for class 'nlar':
     summary(object, ...)
     ## S3 method for class 'nlar':
     plot(x, ask=interactive(), ...)
     ## S3 method for class 'nlar':
     predict(object, newdata, n.ahead, ...)
     ## S3 method for class 'nlar':
     toLatex(object, ...)

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

x, object: fitted 'nlar' object 

 newdata: data to which to apply the prediction 

 n.ahead: number of steps ahead at which to predict 

     ask: graphical option. See 'par'

  digits: See 'printCoefmat' 

     ...: further arguments to be passed to and from other methods 

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

     _M_A_P_E Mean Absolute Percent Error 

     _m_s_e Mean Square Error 

     _p_l_o_t Diagnostic plots 

     _p_r_e_d_i_c_t Model predictions. For n.ahead>1, the model is simply
          iterated on generated data 

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

     Antonio, Fabio Di Narzo

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

     'availableModels' for listing all currently available models.

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

     x <- log10(lynx)
     mod.setar <- setar(x, m=2, thDelay=1, th=3.25)
     mod.setar
     AIC(mod.setar)
     mse(mod.setar)
     MAPE(mod.setar)
     coef(mod.setar)
     summary(mod.setar)

     e <- residuals(mod.setar)
     e <- e[!is.na(e)]
     plot(e)
     acf(e)

     plot(x)
     lines(fitted(mod.setar), lty=2)
     legend(x=1910, y=3.9,lty=c(1,2), legend=c("observed","fitted"))

     plot(mod.setar)

