Description Usage Arguments Value Warning See Also Examples
This function calculates a univariate functional principal components
analysis by smoothed covariance based on code from
fpca.sc
in package refund.
1 2 3 4 5 6 7 8 9 
funDataObject 
An object of class 
predData 
An object of class 
nbasis 
An integer, representing the number of Bspline basis
functions used for estimation of the mean function and bivariate smoothing
of the covariance surface. Defaults to 
pve 
A numeric value between 0 and 1, the proportion of variance
explained: used to choose the number of principal components. Defaults to

npc 
An integer, giving a prespecified value for the number of
principal components. Defaults to 
makePD 
Logical: should positive definiteness be enforced for the
covariance surface estimate? Defaults to 
cov.weight.type 
The type of weighting used for the smooth covariance
estimate. Defaults to 
mu 
A 
values 
A vector containing the estimated eigenvalues. 
functions 
A

scores 
An matrix of estimated scores for the
observations in 
fit 
A 
npc 
The number of functional
principal components: either the supplied 
sigma2 
The estimated measurement error variance (cf.

estVar 
The estimated smooth variance function of the data. 
This function works only for univariate functional data observed on onedimensional domains.
funData
,
fpcaBasis
, univDecomp
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  oldPar < par(no.readonly = TRUE)
# simulate data
sim < simFunData(argvals = seq(1,1,0.01), M = 5, eFunType = "Poly",
eValType = "exponential", N = 100)
# calculate univariate FPCA
pca < PACE(sim$simData, npc = 5)
# Plot the results
par(mfrow = c(1,2))
plot(sim$trueFuns, lwd = 2, main = "Eigenfunctions")
# flip estimated functions for correct signs
plot(flipFuns(sim$trueFuns,pca$functions), lty = 2, add = TRUE)
legend("bottomright", c("True", "Estimate"), lwd = c(2,1), lty = c(1,2))
plot(sim$simData, lwd = 2, main = "Some Observations", obs = 1:7)
plot(pca$fit, lty = 2, obs = 1:7, add = TRUE) # estimates are almost equal to true values
legend("bottomright", c("True", "Estimate"), lwd = c(2,1), lty = c(1,2))
par(oldPar)

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