

_C_r_e_a_t_e _a_n _I_n_t_e_r_p_o_l_a_t_i_o_n _S_p_l_i_n_e

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

_A_r_g_u_m_e_n_t_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_e_s_c_r_i_p_t_i_o_n:

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

_V_a_l_u_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_u_t_h_o_r(_s):

     Douglas Bates and Bill Venables

_S_e_e _A_l_s_o:

     `splineKnots', `splineOrder', `periodicSpline'

_E_x_a_m_p_l_e_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 )

