Estimate a smoothing function f(s, t) over a rectangular lattice
smooth.bibasis(sarg, targ, y, fdPars, fdPart, fdnames=NULL, returnMatrix=FALSE)
vectors of argument values for the first and second dimensions, respectively, of the surface function.
an array containing surface values measured with noise
functional parameter objects for sarg
and targ
,
respectively
a list of length 3 containing character vectors of names for
sarg
, targ
, and the surface function f(s, t).
logical: If TRUE, a two-dimensional is returned using a special class from the Matrix package.
a list with the following components:
a functional data object containing a smooth of the data.
a degrees of freedom measure of the smooth
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.
the coefficient matrix for the basis function expansion of the smoothing function
the error sums of squares. SSE is a vector or a matrix of the same size as GCV.
the penalty matrix.
the matrix mapping the data to the coefficients.