Estimate the functional principal components
Carries out a functional PCA with regularization from the estimate of the covariance surface
pcaPACE(covestimate, nharm, harmfdPar, cross)
covestimate |
a list with the two named entries "cov.estimate" and "meanfd" |
nharm |
the number of harmonics or principal components to compute. |
harmfdPar |
a functional parameter object that defines the harmonic or principal component functions to be estimated. |
cross |
a logical value: if TRUE, take into account the cross covariance for estimating the eigen functions. |
an object of class "pca.fd" with these named entries:
harmonics |
a functional data object for the harmonics or eigenfunctions |
values |
the complete set of eigenvalues |
scores |
NULL. Use "scoresPACE" for estimating the pca scores |
varprop |
a vector giving the proportion of variance explained by each eigenfunction |
meanfd |
a functional data object giving the mean function |
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