Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <doi:10.1080/10618600.2016.1157483>). The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
| Version: | 1.2.0.1 |
| Imports: | Rcpp, RcppParallel |
| LinkingTo: | Rcpp, RcppArmadillo, RcppParallel |
| Published: | 2020-01-09 |
| Author: | Wen-Ting Wang, Hsin-Cheng Huang |
| Maintainer: | Wen-Ting Wang <egpivo at gmail.com> |
| BugReports: | https://github.com/egpivo/SpatPCA/issues |
| License: | GPL-3 |
| URL: | https://github.com/egpivo/SpatPCA |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| CRAN checks: | SpatPCA results |
| Reference manual: | SpatPCA.pdf |
| Package source: | SpatPCA_1.2.0.1.tar.gz |
| Windows binaries: | r-devel: SpatPCA_1.2.0.1.zip, r-release: SpatPCA_1.2.0.1.zip, r-oldrel: SpatPCA_1.2.0.1.zip |
| macOS binaries: | r-release: SpatPCA_1.2.0.1.tgz, r-oldrel: SpatPCA_1.2.0.1.tgz |
| Old sources: | SpatPCA archive |
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