project                 package:gss                 R Documentation

_P_r_o_j_e_c_t_i_n_g _S_m_o_o_t_h_i_n_g _S_p_l_i_n_e _A_N_O_V_A _F_i_t_s _f_o_r _M_o_d_e_l _D_i_a_g_n_o_s_t_i_c_s

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

     Calculate Kullback-Leibler projection of smoothing spline ANOVA
     fits for model diagnostics.

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

     project(object, ...)
     project.ssanova(object, include, ...)
     project.gssanova(object, include, ...)
     project.ssden(object, include, mesh=FALSE, ...)
     project.sshzd(object, include, mesh=FALSE, ...)

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

  object: Object of class '"ssanova"', '"gssanova"', '"ssden"', or
          '"sshzd"'.

     ...: Additional arguments.  Ignored in 'project.x'.

 include: List of model terms to be included in the reduced model
          space.  The 'partial' and 'offset' terms, if present, are to
          be specified by '"partial"' and '"offset"', respectively.

    mesh: Flag indicating whether to return evaluations of the
          projection.

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

     The entropy KL(fit0,null) can be decomposed as the sum of
     KL(fit0,fit1) and KL(fit1,null), where fit0 is the fit to be
     projected, fit1 is the projection in the reduced model space, and
     null is the constant fit.  The ratio KL(fit0,fit1)/KL(fit0,null)
     serves as a diagnostic of the feasibility of the reduced model.

     For regression fits, smoothness safe-guard is used to prevent
     interpolation, and KL(fit0,fit1)+KL(fit1,null) may not match
     KL(fit0,null) perfectly.

     For mixed-effect models from 'ssanova' and 'gssanova', the
     estimated random effects are treated as offset.

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

     The functions return a list consisting of the following
     components. 

   ratio: KL(fit0,fit1)/KL(fit0,null); the smaller the value, the more
          feasible the reduced model is.

      kl: KL(fit0,fit1).

   check: KL(fit0,fit1)/KL(fit0,null)+KL(fit1,null)/KL(fit0,null); a
          value closer to 1 is preferred.

    mesh: The evaluations of the projection.

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

     Chong Gu, chong@stat.purdue.edu

_R_e_f_e_r_e_n_c_e_s:

     Gu, C. (2004), Model diagnostics for smoothing spline ANOVA
     models. _The Canadian Journal of Statistics_, *32*, 347-358.

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

     Fitting functions 'ssanova', 'gssanova', 'ssden', and 'sshzd'.

