bsplines: B-spline bases

In pomp: Statistical Inference for Partially Observed Markov Processes

B-spline bases

Description

These functions generate B-spline basis functions. bspline_basis gives a basis of spline functions. periodic_bspline_basis gives a basis of periodic spline functions.

Usage

bspline_basis(x, nbasis, degree = 3, deriv = 0, names = NULL, rg = range(x))

periodic_bspline_basis(
  x,
  nbasis,
  degree = 3,
  period = 1,
  deriv = 0,
  names = NULL
)

Arguments

x	Vector at which the spline functions are to be evaluated.
nbasis	The number of basis functions to return.
degree	Degree of requested B-splines.
deriv	The order of the derivative required.
names	optional; the names to be given to the basis functions. These will be the column-names of the matrix returned. If the names are specified as a format string (e.g., "basis%d"), sprintf will be used to generate the names from the column number. If a single non-format string is specified, the names will be generated by paste-ing name to the column number. One can also specify each column name explicitly by giving a length-nbasis string vector. By default, no column-names are given.
rg	numeric of length 2; range of the B-spline basis. To be properly specified, we must have rg[1] < rg[2].
period	The period of the requested periodic B-splines.

Value

bspline_basis	Returns a matrix with length(x) rows and nbasis columns. Each column contains the values one of the spline basis functions.
periodic_bspline_basis	Returns a matrix with length(x) rows and nbasis columns. The basis functions returned are periodic with period period.

If deriv>0, the derivative of that order of each of the corresponding spline basis functions are returned.

C API

Access to the underlying C routines is available: see the pomp C API document. for definition and documentation of the C API.

Author(s)

Aaron A. King

See Also

More on interpolation: covariates, lookup()

Examples

x <- seq(0,2,by=0.01)
y <- bspline_basis(x,degree=3,nbasis=9,names="basis")
matplot(x,y,type='l',ylim=c(0,1.1))
lines(x,apply(y,1,sum),lwd=2)

x <- seq(-1,2,by=0.01)
y <- periodic_bspline_basis(x,nbasis=5,names="spline%d")
matplot(x,y,type='l')

pomp documentation built on Aug. 8, 2023, 1:08 a.m.