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Design Matrix for B-splines
Usage
splineDesign(knots, x, ord, derivs)
spline.des(knots, x, ord, 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 .
|
Description
Evaluate the design matrix for the B-splines defined by knots
at the values in 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 argument 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 VenablesExamples
splineDesign(knots = 1:10, x = 4:7)