FPCA3D-package {FPCA3D} | R Documentation |
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:
Package: | FPCA3D |
Type: | Package |
Title: | Three Dimensional Functional Component Analysis |
Version: | 1.0 |
Date: | 2018-07-09 |
Author: | Nan Lin, Momiao Xiong |
Maintainer: | Nan Lin <edmondlinnan@gmail.com> |
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>. |
License: | GPL-2|GPL-3 |
Depends: | graphics, grDevices, stats, utils |
Index of help topics:
FFT2FS_3D Three dimensional Fourier Series FPCA3D-package Three Dimensional Functional Component Analysis FPCA_3D_score Three Dimensional Functional Component Analysis
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 <edmondlinnan@gmail.com>
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
Examples
data_in = array(runif(4000,0,1),dim=c(10,10,10,4))
test = FPCA_3D_score(data_in,0.8)
[Package FPCA3D version 1.0 Index]