basis.osplines: A function to decompose multivariate data on an orthogonal...

In multisensi: Multivariate Sensitivity Analysis

A function to decompose multivariate data on an orthogonal B-spline basis (O-spline)

Description

The basis.osplines function decomposes a multivariate data set on an orthogonalised B-spline (or O-spline) basis defined by its knots and mdegree parameters.

Usage

basis.osplines(simuls, basis.args = list(knots = 5, mdegree = 3))

Arguments

simuls	a data.frame of size N x T, typically a set of N simulation outputs of length T.
basis.args	a list of arguments for the O-spline decomposition. The knots argument is the number of knots or the vector of knot positions. The mdegree argument is the polynomial degree. For the optional x.coord argument, see the Details section.

Details

The optional x.coord element of the list in basis.args can be used to specify the support of the O-spline decomposition, if different from 1:T. It must be a vector of length T.

Value

H	a data.frame of size N x d, where d is the dimension of the O-spline decomposition. It contains the coefficients of the decomposition for each row of the simuls data.frame.
L	a matrix of size T x d. It contains the vectors of the O-spline basis.
call.info	list with the element reduction="o-splines"

See Also

bspline, sesBsplinesORTHONORM

Examples

data(biomasseY)

res <- basis.osplines(biomasseY,basis.args=list(knots=7,mdegree=3))

multisensi documentation built on Aug. 20, 2026, 1:08 a.m.