predict-methods             package:aod             R Documentation

_M_e_t_h_o_d_s _f_o_r _F_u_n_c_t_i_o_n "_p_r_e_d_i_c_t" _i_n _P_a_c_k_a_g_e "_a_o_d"

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

     "predict" methods for fitted models generated by functions in
     package 'aod'.

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

       ## S4 method for signature 'glimML':
       predict(object, newdata = NULL, 
         type = c("response", "link"), se.fit = FALSE, ...)
       ## S4 method for signature 'glimQL':
       predict(object, newdata = NULL, 
         type = c("response", "link"), se.fit = FALSE, ...)
       

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

  object: A fitted model of formal class "glimML" (functions 'betabin'
          or 'negbin') or  "glimQL" (functions 'quasibin' or
          'quasipois').

 newdata: A data.frame providing all the explanatory variables
          necessary for predictions.

    type: A character string indicating the scale on which predictions
          are made: either "response" for  predictions on the
          observation scale, or "link" for predictions on the scale of
          the link (logit, cloglog  or log, depending on the call of
          the fitting function).

  se.fit: A logical scalar indicating whether pointwise standard errors
          should be computed for the predictions.

     ...: Other arguments passed to methods.

_M_e_t_h_o_d_s:

     _o_b_j_e_c_t = "_A_N_Y" Generic function: see 'predict'.

     _o_b_j_e_c_t = "_g_l_i_m_M_L" Compute predictions for models of formal class
          "glimML", presently generated  by functions 'betabin'
          (maximum-likelihood beta-binomial regression) and 'negbin' 
          (maximum-likelihood negative-binomial regression). See the
          examples for these functions. 

     _o_b_j_e_c_t = "_g_l_i_m_Q_L" Compute predictions for models of formal class
          "glimQL", presently generated  by functions 'quasibin'
          (quasi-likelihood binomial regression) and 'quasibin' 
          (quasi-likelihood Poisson regression). See the examples for
          these functions. 

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

     'predict.glm'

