

   update {base}                                R Documentation

   UUppddaattee aanndd RRee--ffiitt aa MMooddeell CCaallll

   DDeessccrriippttiioon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Ussaaggee::

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

   AArrgguummeenntts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Vaalluuee::

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

   AAuutthhoorr((ss))::

        B.D. Ripley

   SSeeee AAllssoo::

        `update.formula'

   EExxaammpplleess::

        oldcon <- options(contrasts = c("contr.treatment", "contr.poly"))
        ## Annette Dobson (1990) "An Introduction to Statistical Modelling".
        ## 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)

