FPCA3D-package: Three Dimensional Functional Component Analysis

In FPCA3D: Three Dimensional Functional Component Analysis

Description

Run three dimensional functional principal component analysis and return the three dimensional functional principal component scores. The details of the method are explained in Lin et al.(2015) <doi:10.1371/journal.pone.0132945>.

Details

The DESCRIPTION file: This package was not yet installed at build time.

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data_in = array(runif(4000,0,1),dim=c(10,10,10,4)) test = FPCA_3D_score(data_in,0.8)

Author(s)

Nan Lin, Momiao Xiong

Maintainer: Nan Lin <[e-mail]>

References

Lin N, Jiang J, Guo S, Xiong M. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis. PLOS ONE. 2015;10(7):e0132945.

See Also

FFT2FS_3D, FPCA_3D_score

Examples

data_in = array(runif(4000,0,1),dim=c(10,10,10,4))
test = FPCA_3D_score(data_in,0.8)

FPCA3D documentation built on May 2, 2019, 4:17 a.m.