glm.summaries              package:base              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'
     and `anova.glm' objects.

     `anova.glmlist' is called from `anova.glm' for comparison of
     several `glm' models.

_U_s_a_g_e:

     summary(object, dispersion = NULL, correlation = FALSE, ...)
     anova(object, dispersion = NULL, ..., test = NULL)
     anova.glmlist(object, dispersion = NULL, test = NULL, ...)
     coefficients(x) ; coef(x)
     df.residual(x)
     family(x)
     fitted.values(x) ; fitted(x)
     residuals(x, type = c("deviance", "pearson", "working",
                           "response", "partial"), ...)
     print.summary(summary.glm.obj, digits = max(3, getOption("digits") - 3),
                   na.print = "", symbolic.cor = p > 4,
                   signif.stars = getOption("show.signif.stars"), ...)

_A_r_g_u_m_e_n_t_s:

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

dispersion: the dispersion parameter for the fitting family. By default
          it is obtained from `glm.obj'.

correlation: logical; if `TRUE', the correlation matrix of the
          estimated parameters is returned and printed.

    test: a character string, matching one of `"Chisq"', `"F"' or
          `"Cp"'. See `stat.anova'.

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

_V_a_l_u_e:

     The function `summary' can be used to obtain or print a summary of
     the results and the function `anova' and be used to produce and
     analysis of variance table.

_W_a_r_n_i_n_g:

     The comparison between two or more models by `anova' or
     `anova.glmlist' will only be valid if they are fitted to the same
     dataset. This may be a problem if there are missing values and R's
     default of `na.action = na.omit' is used.

_S_e_e _A_l_s_o:

     `glm' for computing `glm.obj'; the corresponding generic
     functions, `summary', `anova', `coefficients', `deviance',
     `effects', `fitted.values', `residuals'.

_E_x_a_m_p_l_e_s:

     ## --- Continuing the Example from  ``?glm'':

     summary(glm.D93)
     anova(glm.D93)
     anova(glm.D93, test = "Cp")
     anova(glm.D93, test = "Chisq")

