Two other possibilities:
The 'DierckxSpline' package includes a function 'percur' for
fitting periodic splines. Unfortunately, it has a known bug that kills
R with a segmentation fault, though it not affect your application.
The 'fda' package supports the use of finite Fourier series for
fitting periodic functions. Below please find code for this that I just
posted to R-devel in response to a report of the 'percur' bug.
Hope this helps.
Spencer Graves
# problem
x <- seq(0.2, 0.8, 0.01)
y <- cos(2*pi*x2) + 0.1*rnorm(length(x))
plot(x, y, xlim=0:1)
# simple solution
library(fda)
Fourier1 <- create.fourier.basis()
FourierFit <- Data2fd(x, y, Fourier1)
plotfit.fd(y, x, FourierFit)
# Allow more flexibility
Fourier9 <- create.fourier.basis(nbasis=2*9+1)
# constant + 9 cosine & sine terms
# Naive initial solution
FourierSmooth0 <- smooth.basisPar(x, y, Fourier9)
plotfit.fd(y, x, FourierSmooth0$fd)
# Oops: Need some smoothing
# Try again.
FourierSmooth1 <- smooth.basisPar(x, y, Fourier9, lambda=1)
plotfit.fd(y, x, FourierSmooth1$fd)
# Much better.
######################################
Simon Wood wrote:
The "cc" and "cp" bases in package `mgcv' provide periodic splines,
[e.g. gam(y~s(x,bs="cc"))], but this may not be exactly the functionality you
want.
best,
Simon
On Friday 16 January 2009 08:42, cmr.p...@gmail.com wrote:
Hello group!
Is there a package that allows to fit smooth *periodic* splines to
data? I'm interested in a function which combines the functionality of
smooth.spline and splines::periodicSpline.
Thanks,
Andrey
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