coef.fd | R Documentation |
Obtain the coefficients component from a functional object (functional
data, class fd
, functional parameter, class fdPar
, a
functional smooth, class fdSmooth
, or a Taylor spline
representation, class Taylor
.
## S3 method for class 'fd'
coef(object, ...)
## S3 method for class 'fdPar'
coef(object, ...)
## S3 method for class 'fdSmooth'
coef(object, ...)
## S3 method for class 'fd'
coefficients(object, ...)
## S3 method for class 'fdPar'
coefficients(object, ...)
## S3 method for class 'fdSmooth'
coefficients(object, ...)
object |
An object whose functional coefficients are desired |
... |
other arguments |
Functional representations are evaluated by multiplying a basis
function matrix times a coefficient vector, matrix or 3-dimensional
array. (The basis function matrix contains the basis functions as
columns evaluated at the evalarg
values as rows.)
A numeric vector or array of the coefficients.
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.
coef
fd
fdPar
smooth.basisPar
smooth.basis
##
## coef.fd
##
bspl1.1 <- create.bspline.basis(norder=1, breaks=0:1)
fd.bspl1.1 <- fd(0, basisobj=bspl1.1)
coef(fd.bspl1.1)
##
## coef.basisPar
##
rangeval <- c(-3,3)
# set up some standard normal data
x <- rnorm(50)
# make sure values within the range
x[x < -3] <- -2.99
x[x > 3] <- 2.99
# set up basis for W(x)
basisobj <- create.bspline.basis(rangeval, 11)
# set up initial value for Wfdobj
Wfd0 <- fd(matrix(0,11,1), basisobj)
WfdParobj <- fdPar(Wfd0)
coef(WfdParobj)
##
## coef.fdSmooth
##
girlGrowthSm <- with(growth, smooth.basisPar(argvals=age, y=hgtf,
lambda=0.1)$fd)
coef(girlGrowthSm)
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