splineBasis1D: Calculate a spline basis decomposition for functional data on...

In MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains

Calculate a spline basis decomposition for functional data on one-dimensional domains

Description

These functions calculate a penalized or unpenalized spline basis decomposition for functional data on one-dimensional domains based on the gam function in the mgcv package.

Usage

splineBasis1D(funDataObject, bs = "ps", m = NA, k = -1)

splineBasis1Dpen(funDataObject, bs = "ps", m = NA, k = -1, parallel = FALSE)

Arguments

funDataObject	An object of class funData containing the observed functional data samples and for which the basis decomposition is calculated.
bs	A character string, specifying the type of basis functions to be used. Defaults to "ps" (B-spline functions). Please refer to smooth.terms for a list of possible basis functions.
m	A numeric, the order of the spline basis. Defaults to NA, i.e. the order is chosen automatically. See s for details.
k	A numeric, the number of basis functions used. Defaults to -1, i.e. the number of basis functions is chosen automatically. See s for details.
parallel	Logical (only for splineBasis1Dpen. If TRUE, the coefficients for the basis functions are calculated in parallel. The implementation is based on the foreach function and requires a parallel backend that must be registered before. See foreach for details.

Value

scores	A matrix of scores (coefficients) with dimension N x K, reflecting the weights for each of the K basis functions and for each of the N observations.
B	A matrix containing the scalar product of all pairs of basis functions.
ortho	Logical, set to FALSE, as basis functions are not orthonormal.
functions	NULL, as basis functions are known
settings	A list with entries bs, m and k, giving the actual parameters used for generating the spline basis functions.

See Also

univDecomp, gam, foreach

MFPCA documentation built on Sept. 15, 2022, 9:07 a.m.