https://github.com/cran/fda
Tip revision: 4ff0009dbd255f45aec89054867b85d65c6f951f authored by J. O. Ramsay on 03 November 2009, 00:00:00 UTC
version 2.2.7
version 2.2.7
Tip revision: 4ff0009
bsplineS.Rd
\name{bsplineS}
\alias{bsplineS}
\title{
B-spline Basis Function Values
}
\description{
Evaluates a set of B-spline basis functions, or a derivative of these
functions, at a set of arguments.
}
\usage{
bsplineS(x, breaks, norder=4, nderiv=0)
}
\arguments{
\item{x}{
A vector of argument values at which the B-spline basis functions
are to be evaluated.
}
\item{breaks}{
A strictly increasing set of break values defining the B-spline
basis. The argument values \code{x} should be within the interval
spanned by the break values.
}
\item{norder}{
The order of the B-spline basis functions. The order less one is
the degree of the piece-wise polynomials that make up any B-spline
function. The default is order 4, meaning piece-wise cubic.
}
\item{nderiv}{
A nonnegative integer specifying the order of derivative to be
evaluated. The derivative must not exceed the order. The default
derivative is 0, meaning that the basis functions themselves are
evaluated.
}
}
\value{
a matrix of function values. The number of rows equals the number of
arguments, and the number of columns equals the number of basis
functions.
}
\examples{
# Minimal example: A B-spline of order 1 (i.e., a step function)
# with 0 interior knots:
bsplineS(seq(0, 1, .2), 0:1, 1, 0)
# set up break values at 0.0, 0.2,..., 0.8, 1.0.
breaks <- seq(0,1,0.2)
# set up a set of 11 argument values
x <- seq(0,1,0.1)
# the order willl be 4, and the number of basis functions
# is equal to the number of interior break values (4 here)
# plus the order, for a total here of 8.
norder <- 4
# compute the 11 by 8 matrix of basis function values
basismat <- bsplineS(x, breaks, norder)
}
\keyword{smooth}