splineDesign             package:splines             R Documentation

Design Matrix for B-splines

Description:

     Evaluate the design matrix for the B-splines defined by `knots' at
     the values in `x'.

Usage:

     splineDesign(knots, x, ord = 4, derivs)
     spline.des(knots, x, ord = 4, derivs)

Arguments:

   knots: a numeric vector of knot positions with non-decreasing
          values.

       x: a numeric vector of values at which to evaluate the B-spline
          functions or derivatives. The values in `x' must be between
          `knots[ord]' and `knots[ length(knots) + 1 - ord ]'.

     ord: a positive integer giving the order of the spline function.
          This is the number of coefficients in each piecewise
          polynomial segment, thus a cubic spline has order 4. 
          Defaults to 4.

  derivs: an integer vector of the same length as `x' and with values
          between `0' and `ord - 1'.  The derivative of the given order
          is evaluated at the `x' positions.  Defaults to a vector of
          zeroes of the same length as `x'.

Value:

     A matrix with `length( x )' rows and `length( knots ) - ord'
     columns.  The i'th row of the matrix contains the coefficients of
     the B-splines (or the indicated derivative of the B-splines)
     defined by the `knot' vector and evaluated at the i'th value of
     `x'. Each B-spline is defined by a set of `ord' successive knots
     so the total number of B-splines is `length(knots)-ord'.

Note:

     The older `spline.des' function takes the same arguments but
     returns a list with several components including `knots', `ord',
     `derivs', and `design'.  The `design' component is the same as the
     value of the `splineDesign' function.

Author(s):

     Douglas Bates and Bill Venables

Examples:

     splineDesign(knots = 1:10, x = 4:7)

