

   EEssttiimmaattee lloogg TTrraannssffoorrmmaattiioonn PPaarraammeetteerr

        logtrans(object, ..., alpha = seq(0.5, 6, by = 0.25) - min(y),
                 plotit = <<see below>>, interp = <<see below>>,
              xlab="alpha", ylab="log Likelihood")

   AArrgguummeennttss::

     object: Fitted linear model object, or formula defining
             the untransformed model that is `y ~ x1 + x2 +
             ...{}'.  The function is generic.

        ...: If `object' is a formula, this argument may spec-
             ify a data frame as for `lm'.

      alpha: Set of values for the transformation parameter,
             alpha.

     plotit: Should plotting be done?  (Default is `T' if a
             non-null device is currently active, else `F'.)

     interp: Should the marginal log-likelihood be interpolated
             with a spline approximation?   (Default is `T' if
             plotting is to be done and the number of real
             points is less than 100.)

       xlab: as for `plot'.

       ylab: as for `plot'.

   DDeessccrriippttiioonn::

        Find and optionally plot the marginal likelihood for
        alpha for a transformation model of the form `log(y +
        alpha) ~ x1 + x2 + ...{}'.

   VVaalluuee::

        List with components `x' (for alpha) and `y' (for the
        marginal log-likelihood values).

   SSiiddee EEffffeeccttss::

        A plot of the marginal log-likelihood is produced, if
        requested, together with an approximate mle and 95%
        confidence interval.

   RReeffeerreenncceess::

        Venables  Ripley, Chapter 6.

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

        `boxcox'

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

        data(quine)
        logtrans(Days ~ Age*Sex*Eth*Lrn, data = quine)

