selectHyperParms            package:tsDyn            R Documentation

_A_u_t_o_m_a_t_i_c _s_e_l_e_c_t_i_o_n _o_f _m_o_d_e_l _h_y_p_e_r-_p_a_r_a_m_e_t_e_r_s

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

     Automatic selection of model hyper-parameters

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

     selectLSTAR(x, m, d=1, steps=d, mL = 1:m, mH = 1:m, thDelay=0:(m-1))
     selectNNET(x, m, d=1, steps=d, size=1:(m+1), maxit=1e3)

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

       x: time series 

m, d, steps: embedding parameters. For their meanings, see help about
          'nlar' 

   mL,mH: Vector of 'low' and 'high' regimes autoregressive orders

 thDelay: Vector of 'threshold delay' values

    size: Vector of numbers of hidden units in the nnet model 

   maxit: Max. number of iterations for each model estimation 

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

     Functions for automatic selection of LSTAR and NNET models hyper
     parameters. An exhaustive search over all possible combinations of
     values of specified hyper-parameters is performed. Embedding
     parameters 'm,d,steps' are kept fixed.

     Selection criterion is the usual AIC.

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

     A data-frame, with columns giving hyper-parameter values and the
     computed AIC for each row (only the best 10s are returned)

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

     Antonio, Fabio Di Narzo

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

     llynx <- log10(lynx)
     selectLSTAR(llynx, m=2)
     selectNNET(llynx, m=3, size=1:5)

