

   CCrreeaattee aann IInntteerrppoollaattiioonn SSpplliinnee

        interpSpline(obj1, obj2, bSpline, period, na.action)

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

       obj1: Either a numeric vector of `x' values or a for-
             mula.

       obj2: If `obj1' is numeric this should be a numeric vec-
             tor of the same length.  If `obj1' is a formula
             this can be an optional data frame in which to
             evaluate the names in the formula.

    bSpline: If `TRUE' the b-spline representation is returned,
             otherwise the piecewise polynomial representation
             is returned.  Defaults to `FALSE'.

     period: An optional positive numeric value giving a period
             for a periodic interpolation spline.

   na.action: a optional function which indicates what should
             happen when the data contain `NA's.  The default
             action (`na.omit') is to omit any incomplete
             observations.  The alternative action `na.fail'
             causes `interpSpline' to print an error message
             and terminate if there are any incomplete observa-
             tions.

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

        Create an interpolation spline, either from `x' and `y'
        vectors, or from a formula/data.frame combination.

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

        An object that inherits from class `spline'. The object
        can be in the B-spline representation, in which case it
        will be of class `nbSpline' for natural B-spline, or in
        the piecewise polynomial representation, in which case
        it will be of class `npolySpline'.

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

        Douglas Bates and Bill Venables

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

        `splineKnots', `splineOrder', `periodicSpline'

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

        data( women )
        ispl <- interpSpline( women$height, women$weight )
        ispl2 <- interpSpline( weight ~ height,  women )
        # ispl and ispl2 should be the same
        plot( predict( ispl, seq( 55, 75, len = 51 ) ) )
        plot( ispl )    # plots over the range of the knots
        splineKnots( ispl )

