

   SSmicmen {nls}                               R Documentation

   MMiicchhaaeelliiss--MMeenntteenn MMooddeell

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

        This `selfStart' model evaluates the Michaelis-Menten
        model and its gradient.  It has an `initial' attribute
        that will evaluate initial estimates of the parameters
        `Vm' and `K'

   UUssaaggee::

        SSmicmen(input, Vm, K)

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

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

         Vm: a numeric parameter representing the maximum value
             of the response.

          K: a numeric parameter representing the `input' value
             at which half the maximum response is attained.
             In the field of enzyme kinetics this is called the
             Michaelis parameter.

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

        a numeric vector of the same length as `input'.  It is
        the value of the expression `Vm*input/(K+input)'.  If
        both the arguments `Vm' and `K' are names of objects,
        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( nls )
        data( Puromycin )
        PurTrt <- Puromycin[ Puromycin$state == "treated", ]
        SSmicmen( PurTrt$conc, 200, 0.05 )  # response only
        Vm <- 200; K <- 0.05
        SSmicmen( PurTrt$conc, Vm, K ) # response and gradient
        getInitial(rate ~ SSmicmen(conc, Vm, K), data = PurTrt)
        ## Initial values are in fact the converged values
        fm1 <- nls(rate ~ SSmicmen(conc, Vm, K), data = PurTrt)
        summary( fm1 )
        ## Alternative call using the subset argument
        fm2 <- nls(rate ~ SSmicmen(conc, Vm, K), data = Puromycin,
                   subset = state == "treated")
        summary(fm2)

