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KFPCA

Kendall Functional Principal Component Analysis

Implementation for Kendall functional principal component analysis. Kendall functional principal component analysis is a robust functional principal component analysis technique for non-Gaussian functional/longitudinal data. The crucial function of this package is KFPCA(). Moreover, least square estimates of functional principal component scores are also provided. Refer to <arXiv:2102.00911>.

Functions (10)

CD4

CD4 cell counts

FPCscoreLSE

Least square estimates of functional principal component scores

GenDataKL

Generate functional/longitudinal data via KL expansion

GetGCVbw1D

Bandwidth selection through GCV for one-dimension cases

GetGCVbw2D

Bandwidth selection through GCV for two-dimension cases

KFPCA

Kendall Functional Principal Component Analysis

MeanEst

Local linear estimates of mean function

SparsePlot

Sparse plot

kernfun

Kernel Functions

predict.KFPCA

Predict FPC scores

KFPCA

Kendall Functional Principal Component Analysis

v1.0
GPL (>= 3)
Authors
Rou Zhong [aut, cre]
Initial release

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