cpplot                package:locfit                R Documentation

_C_o_m_p_u_t_e _a _C_p _p_l_o_t.

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

     The 'cpplot' function loops through calls to the 'cp' function
     (and hence to 'link{locfit}'), using a different smoothing
     parameter for each call. The returned structure contains the Cp
     statistic for each fit, and can be used to produce an AIC plot.

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

     cpplot(..., alpha, sig2)

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

     ...: arguments to the 'cp', 'locfit' functions.

   alpha: Matrix of smoothing parameters. The 'cpplot' function loops
          through calls to 'cp', using each row of 'alpha' as the
          smoothing parameter in turn. If 'alpha' is provided as a
          vector, it will be converted to a one-column matrix, thus
          interpreting each component as a nearest neighbor smoothing
          parameter.

    sig2: Residual variance. If not specified, the residual variance is
          computed using the fitted model with the fewest residual
          degrees of freedom.

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

     An object with class '"gcvplot"', containing the smoothing
     parameters and CP scores. The actual plot is produced using
     'plot.gcvplot'.

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

     'locfit', 'locfit.raw', 'gcv', 'aic', 'plot.gcvplot'

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

     data(ethanol)
     plot(cpplot(NOx~E,data=ethanol,alpha=seq(0.2,1.0,by=0.05)))

