fd {fda} | R Documentation |
This is the constructor function for objects of the fd
class.
Each function that sets up an object of this class must call this
function. This includes functions data2fd
,
smooth.basis
, density.fd
, and so forth that estimate
functional data objects that smooth or otherwise represent data.
Ordinarily, users of the functional data analysis software will not
need to call this function directly, but these notes are valuable to
understanding the components of a list
of class fd
.
fd(coef=NULL, basisobj=NULL, fdnames=NULL)
coef |
a vector, matrix, or three-dimensional array of coefficients.
The first dimension (or elements of a vector) corresponds to basis functions. A second dimension corresponds to the number of functional observations, curves or replicates. If coef is a vector, it
represents only a single functional observation.
If coef is an array, the third dimension corresponds to
variables for multivariate functional data objects.
A functional data object is "univariate" if coef is a vector
or matrix and "multivariate" if it is a three-dimensional array.
if(is.null(coef)) coef <- rep(0, basisobj[['nbasis']]) |
basisobj |
a functional basis object defining the basis
if(is.null(basisobj)){
if(is.null(coef)) basisobj <- basisfd()
else {
rc <- range(coef)
if(diff(rc)==0) rc <- rc+0:1
nb <- max(4, nrow(coef))
basisobj <- create.bspline.basis(rc, nbasis = nb)
}
}
|
fdnames |
A list of length 3, each member being a string vector containing labels for the levels of the corresponding dimension of the discrete data. The first dimension is for argument values, and is given the default name "time", the second is for replications, and is given the default name "reps", and the third is for functions, and is given the default name "values". |
To check that an object is of this class, use function
is.fd
.
Normally only developers of new functional data analysis functions will actually need to use this function.
A functional data object (i.e., having class fd
), which is a
list with components named coefs
, basis
, and
fdnames
.
Ramsay, James O., and Silverman, Bernard W. (2006), Functional Data Analysis, 2nd ed., Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York
data2fd
smooth.basis
density.fd
create.bspline.basis
## ## default ## fd() ## ## The simplest b-spline basis: order 1, degree 0, zero interior knots: ## a single step function ## bspl1.1 <- create.bspline.basis(norder=1, breaks=0:1) fd.bspl1.1 <- fd(0, basisobj=bspl1.1) fd.bspl1.1a <- fd(basisobj=bspl1.1) all.equal(fd.bspl1.1, fd.bspl1.1a) # TRUE ## Not run: fd.bspl1.1b <- fd(0) Error in fd(0) : Number of coefficients does not match number of basis functions. ... because fd by default wants to create a cubic spline ## End(Not run) ## ## Cubic spline: 4 basis functions ## bspl4 <- create.bspline.basis(nbasis=4) plot(bspl4) parab4.5 <- fd(c(3, -1, -1, 3)/3, bspl4) # = 4*(x-.5)^2 plot(parab4.5)