glm.summaries             package:stats             R Documentation

_A_c_c_e_s_s_i_n_g _G_e_n_e_r_a_l_i_z_e_d _L_i_n_e_a_r _M_o_d_e_l _F_i_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     These functions are all 'methods' for class 'glm' or 'summary.glm'
     objects.

_U_s_a_g_e:

     ## S3 method for class 'glm':
     family(object, ...)

     ## S3 method for class 'glm':
     residuals(object, type = c("deviance", "pearson", "working",
                           "response", "partial"), ...)

_A_r_g_u_m_e_n_t_s:

  object: an object of class 'glm', typically the result of a call to
          'glm'.

    type: the type of residuals which should be returned. The
          alternatives are: '"deviance"' (default), '"pearson"',
          '"working"', '"response"', and '"partial"'.

     ...: further arguments passed to or from other methods.

_D_e_t_a_i_l_s:

     The references define the types of residuals: Davison & Snell is a
     good reference for the usages of each.

     The partial residuals are a matrix of working residuals, with each
     column formed by omitting a term from the model.

_R_e_f_e_r_e_n_c_e_s:

     Davison, A. C. and Snell, E. J. (1991) _Residuals and
     diagnostics._  In: Statistical Theory and Modelling. In Honour of
     Sir David Cox, FRS, eds. Hinkley, D. V., Reid, N. and Snell, E.
     J., Chapman & Hall.

     Hastie, T. J. and Pregibon, D. (1992) _Generalized linear models._
     Chapter 6 of _Statistical Models in S_ eds J. M. Chambers and T.
     J. Hastie, Wadsworth & Brooks/Cole.

     McCullagh P. and Nelder, J. A. (1989) _Generalized Linear Models._
     London: Chapman and Hall.

_S_e_e _A_l_s_o:

     'glm' for computing 'glm.obj', 'anova.glm'; the corresponding
     _generic_ functions, 'summary.glm', 'coef', 'deviance',
     'df.residual', 'effects', 'fitted', 'residuals'.

