

   LLooggiissttiicc mmooddeell

        SSfpl(input, Asym, xmid, scal)

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

      input: a numeric vector of values at which to evaluate
             the model.

       Asym: a numeric parameter representing the asymptote.

       xmid: a numeric parameter representing the `x' value at
             the inflection point of the curve.  The value of
             `SSlogis' will be `Asym/2' at `xmid'.

       scal: a numeric scale parameter on the `input' axis.

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

        This `selfStart' model evaluates the logistic function
        and its gradient.  It has an `initial' attribute that
        will evaluate initial estimates of the parameters
        `Asym', `xmid', and `scal' for a given set of data.

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

        a numeric vector of the same length as `input'.  It is
        the value of the expression `Asym/(1+exp((xmid-
        input)/scal))'.  If all of the arguments `Asym',
        `xmid', and `scal' are names of objects, as opposed to
        expressions or explicit numerical values, the gradient
        matrix with respect to these names is attached as an
        attribute named `gradient'.

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

        Jose Pinheiro and Douglas Bates

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

        `nls', `selfStart'

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

        library( lme )
        data( ChickWeight )
        Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ]
        SSlogis( Chick.1$Time, 368, 14, 6 )  # response only
        Asym <- 368
        xmid <- 14
        scal <- 6
        SSlogis( Chick.1$Time, Asym, xmid, scal ) # response and gradient

