gcv                  package:locfit                  R Documentation

_C_o_m_p_u_t_e _g_e_n_e_r_a_l_i_z_e_d _c_r_o_s_s-_v_a_l_i_d_a_t_i_o_n _s_t_a_t_i_s_t_i_c.

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

     The calling sequence for `gcv' matches those for the `locfit' or
     `locfit.raw' functions. The fit is not returned; instead, the
     returned object contains Wahba's generalized cross-validation
     score for the fit.

     The GCV 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.

     For likelihood models, GCV is computed using -2 times the
     log-likelihood in place of the residual sum of squares; I know of
     no results validating this interpretation.

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

     gcv(x, ...)

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

     `locfit', `locfit.raw', `gcvplot'

