| splineDesign {splines} | R Documentation |
Evaluate the design matrix for the B-splines defined by knots
at the values in x.
splineDesign(knots, x, ord = 4, derivs) spline.des(knots, x, ord = 4, derivs)
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. |
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.
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.
Douglas Bates and Bill Venables
splineDesign(knots = 1:10, x = 4:7)