fda: smooth.bibasis – R documentation

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smooth.bibasis

Smooth a discrete surface over a rectangular lattice

Estimate a smoothing function f(s, t) over a rectangular lattice

smooth.bibasis(sarg, targ, y, fdPars, fdPart, fdnames=NULL, returnMatrix=FALSE)

`sarg, targ`	vectors of argument values for the first and second dimensions, respectively, of the surface function.
`y`	an array containing surface values measured with noise
`fdPars, fdPart`	functional parameter objects for `sarg` and `targ`, respectively
`fdnames`	a list of length 3 containing character vectors of names for `sarg`, `targ`, and the surface function f(s, t).
`returnMatrix`	logical: If TRUE, a two-dimensional is returned using a special class from the Matrix package.

a list with the following components:

`fdobj`	a functional data object containing a smooth of the data.
`df`	a degrees of freedom measure of the smooth
`gcv`	the value of the generalized cross-validation or GCV criterion. If the function is univariate, GCV is a vector containing the error sum of squares for each function, and if the function is multivariate, GCV is a NVAR by NCURVES matrix.
`coef`	the coefficient matrix for the basis function expansion of the smoothing function
`SSE`	the error sums of squares. SSE is a vector or a matrix of the same size as GCV.
`penmat`	the penalty matrix.
`y2cMap`	the matrix mapping the data to the coefficients.