aic                  package:locfit                  R Documentation

_C_o_m_p_u_t_e _A_k_a_i_k_e'_s _I_n_f_o_r_m_a_t_i_o_n _C_r_i_t_e_r_i_o_n.

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

     The calling sequence for 'aic' matches those for the 'locfit' or
     'locfit.raw' functions. The fit is not returned; instead, the
     returned object contains Akaike's information criterion for the
     fit.

     The definition of AIC used here is -2*log-likelihood + pen*(fitted
     d.f.). For quasi-likelihood, and local regression, this assumes
     the scale parameter is one. Other scale parameters can effectively
     be used by changing the penalty.

     The AIC score is exact (up to numerical roundoff) if the
     'ev="data"' argument is provided. Otherwise, the residual
     sum-of-squares and degrees of freedom are computed using locfit's
     standard interpolation based approximations.

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

     aic(x, ..., pen=2)

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

       x: model formula

     ...: other arguments to locfit

     pen: penalty for the degrees of freedom term

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

     'locfit', 'locfit.raw', 'aicplot'

