lm.summaries              package:base              R Documentation

_A_c_c_e_s_s_i_n_g _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:

     All these functions are `methods' for class `"lm"'  objects.

_U_s_a_g_e:

     coefficients(object, ...) ; \method

_A_r_g_u_m_e_n_t_s:

object, x: an object of class `lm', usually, a result of a call to
          `lm'.

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

_D_e_t_a_i_l_s:

     The generic accessor functions `coefficients', `effects',
     `fitted.values' and `residuals' can be used to extract various
     useful features of the value returned by `lm'.

_S_e_e _A_l_s_o:

     The model fitting function `lm', `anova.lm'.

     `coefficients', `deviance', `df.residual', `effects',
     `fitted.values', `glm' for generalized linear models,
     `lm.influence' for regression diagnostics, `weighted.residuals',
     `residuals', `residuals.glm', `summary.lm'.

_E_x_a_m_p_l_e_s:

     ##-- Continuing the  lm(.) example:
     coef(lm.D90)# the bare coefficients

     ## The 2 basic regression diagnostic plots [plot.lm(.) is preferred]
     plot(resid(lm.D90), fitted(lm.D90))# Tukey-Anscombe's
     abline(h=0, lty=2, col = 'gray')

     qqnorm(residuals(lm.D90))

