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.
splineBasis1D(funDataObject, bs = "ps", m = NA, k = -1)splineBasis1Dpen(funDataObject, bs = "ps", m = NA, k = -1, parallel = FALSE)
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.
A matrix containing the scalar product of all pairs of basis functions.
Logical, set to FALSE, as basis functions are not
orthonormal.
NULL, as basis functions are known
A list with entries bs, m and k,
giving the actual parameters used for generating the spline basis
functions.
An object of class funData
containing the observed functional data samples and for which the basis
decomposition is calculated.
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.
A numeric, the order of the spline basis. Defaults to NA,
i.e. the order is chosen automatically. See s for
details.
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.
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.