update                 package:base                 R Documentation

_U_p_d_a_t_e _a_n_d _R_e-_f_i_t _a _M_o_d_e_l _C_a_l_l

_D_e_s_c_r_i_p_t_i_o_n:

     `update' will update and (by default) re-fit a model. It does this
     by extracting the call stored in the object, updating the call and
     (by default) evaluating that call. Sometimes it is useful to call
     `update' with only one argument, for example if the data frame has
     been corrected.

_U_s_a_g_e:

     update(object, ...)
     update.default(object, formula., ..., evaluate = TRUE)

_A_r_g_u_m_e_n_t_s:

  object: An existing fit from a model function such as `lm', `glm' and
          many others.

formula.: Changes to the formula - see `update.formula' for details.

     ...: Additional arguments to the call, or arguments with changed
          values. Use `name=NULL' to remove the argument `name'.

evaluate: If true evaluate the new call else return the call.

_V_a_l_u_e:

     If `evaluate = TRUE' the fitted object, otherwise the updated
     call.

_A_u_t_h_o_r(_s):

     B.D. Ripley

_S_e_e _A_l_s_o:

     `update.formula'

_E_x_a_m_p_l_e_s:

     oldcon <- options(contrasts = c("contr.treatment", "contr.poly"))
     ## Annette Dobson (1990) "An Introduction to Generalized Linear Models".
     ## Page 9: Plant Weight Data.
     ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
     trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
     group <- gl(2, 10, 20, labels = c("Ctl", "Trt"))
     weight <- c(ctl, trt)
     lm.D9 <- lm(weight ~ group)
     lm.D9
     summary(lm.D90 <- update(lm.D9, . ~ . - 1))
     options(contrasts = c("contr.helmert", "contr.poly"))
     update(lm.D9)
     options(oldcon)

