family                  package:gss                  R Documentation

_U_t_i_l_i_t_y _F_u_n_c_t_i_o_n_s _f_o_r _E_r_r_o_r _F_a_m_i_l_i_e_s

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

     Utility functions for fitting Smoothing Spline ANOVA models with
     non-Gaussian responses.

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

     mkdata.binomial(y, eta, wt, offset)
     dev.resid.binomial(y, eta, wt)
     dev.null.binomial(y, wt, offset)
     cv.binomial(y, eta, wt, hat, alpha)
     y0.binomial(y, eta0, wt)
     proj0.binomial(y0, eta, offset)
     kl.binomial(eta0, eta1, wt)
     cfit.binomial(y, wt, offset)

     mkdata.poisson(y, eta, wt, offset)
     dev.resid.poisson(y, eta, wt)
     dev.null.poisson(y, wt, offset)
     cv.poisson(y, eta, wt, hat, alpha, sr, q)
     y0.poisson(eta0)
     proj0.poisson(y0, eta, wt, offset)
     kl.poisson(eta0, eta1, wt)
     cfit.poisson(y, wt, offset)

     mkdata.Gamma(y, eta, wt, offset)
     dev.resid.Gamma(y, eta, wt)
     dev.null.Gamma(y, wt, offset)
     cv.Gamma(y, eta, wt, hat, rss, alpha)
     y0.Gamma(eta0)
     proj0.Gamma(y0, eta, wt, offset)
     kl.Gamma(eta0, eta1, wt)
     cfit.Gamma(y, wt, offset)

     mkdata.inverse.gaussian(y, eta, wt, offset)
     dev.resid.inverse.gaussian(y, eta, wt)
     dev.null.inverse.gaussian(y, wt, offset)

     mkdata.nbinomial(y, eta, wt, offset, nu)
     dev.resid.nbinomial(y, eta, wt)
     dev.null.nbinomial(y, wt, offset)
     cv.nbinomial(y, eta, wt, hat, alpha)
     y0.nbinomial(y,eta0,nu)
     proj0.nbinomial(y0, eta, wt, offset)
     kl.nbinomial(eta0, eta1, wt, nu)
     cfit.nbinomial(y, wt, offset, nu)

     mkdata.weibull(y, eta, wt, offset, nu)
     dev.resid.weibull(y, eta, wt, nu)
     dev.null.weibull(y, wt, offset, nu)
     cv.weibull(y, eta, wt, hat, nu, alpha)
     y0.weibull(y, eta0, nu)
     proj0.weibull(y0, eta, wt, offset, nu)
     kl.weibull(eta0, eta1, wt, nu, int)
     cfit.weibull(y, wt, offset, nu)

     mkdata.lognorm(y, eta, wt, offset, nu)
     dev.resid.lognorm(y, eta, wt, nu)
     dev0.resid.lognorm(y, eta, wt, nu)
     dev.null.lognorm(y, wt, offset, nu)
     cv.lognorm(y, eta, wt, hat, nu, alpha)
     y0.lognorm(y, eta0, nu)
     proj0.lognorm(y0, eta, wt, offset, nu)
     kl.lognorm(eta0, eta1, wt, nu, y0)
     cfit.lognorm(y, wt, offset, nu)

     mkdata.loglogis(y, eta, wt, offset, nu)
     dev.resid.loglogis(y, eta, wt, nu)
     dev0.resid.loglogis(y, eta, wt, nu)
     dev.null.loglogis(y, wt, offset, nu)
     cv.loglogis(y, eta, wt, hat, nu, alpha)
     y0.loglogis(y, eta0, nu)
     proj0.loglogis(y0, eta, wt, offset, nu)
     kl.loglogis(eta0, eta1, wt, nu, y0)
     cfit.loglogis(y, wt, offset, nu)

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

       y: Model response.

     eta: Fitted values on link scale.

      wt: Model weights.

  offset: Model offset.

      nu: Size for nbinomial.  Inverse scale for log life time.

_N_o_t_e:

     'gssanova0' uses 'mkdata.x', 'dev.resid.x', and 'dev.null.x'. 
     'gssanova' uses the above plus 'dev0.resid.x' and 'cv.x'.

     'y0.x', 'proj0.x', 'kl.x', and 'cfit.x' are used by
     'project.gssanova'.

