R: Smooth a discrete surface over a rectangular lattice

smooth.bibasis {fda} | R Documentation

## Smooth a discrete surface over a rectangular lattice

### Description

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

### Usage

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

### Arguments

`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.

### Value

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.

### See Also

`smooth.basis`

[Package fda version 2.4.8 Index]