eval.bifd | R Documentation |
A vector of argument values for the first argument s
of the
functional data object to be evaluated.
eval.bifd(sevalarg, tevalarg, bifd, sLfdobj=0, tLfdobj=0)
sevalarg |
a vector of argument values for the first argument |
tevalarg |
a vector of argument values for the second argument |
bifd |
a two-argument functional data object. |
sLfdobj |
either a nonnegative integer or a linear differential operator
object. If present, the derivative or the value of applying the
operator to the object as a function of the first argument |
tLfdobj |
either a nonnegative integer or a linear differential operator
object. If present, the derivative or the value of applying the
operator to the object as a function of the second argument |
an array of 2, 3, or 4 dimensions containing the function values. The first dimension corresponds to the argument values in sevalarg, the second to argument values in tevalarg, the third if present to replications, and the fourth if present to functions.
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.
# every-other-day basis to save test time
daybasis <- create.fourier.basis(c(0,365), 183)
harmLcoef <- c(0,(2*pi/365)^2,0)
harmLfd <- vec2Lfd(harmLcoef, c(0,365))
templambda <- 1.0
tempfdPar <- fdPar(fd(matrix(0,daybasis$nbasis,1), daybasis), harmLfd,
lambda=1)
tempfd <- smooth.basis(day.5, CanadianWeather$dailyAv[,,"Temperature.C"],
tempfdPar)$fd
# define the variance-covariance bivariate fd object
tempvarbifd <- var.fd(tempfd)
# evaluate the variance-covariance surface and plot
weektime <- seq(0,365,len=53)
tempvarmat <- eval.bifd(weektime,weektime,tempvarbifd)
# make a perspective plot of the variance function
oldpar <- par(no.readonly=TRUE)
persp(tempvarmat)
par(oldpar)
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