smooth.bibasis: Smooth a discrete surface over a rectangular lattice

In fda: Functional Data Analysis

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.

References

Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.

See Also

smooth.basis

fda documentation built on Sept. 30, 2024, 9:19 a.m.