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Implements a basis function or functional data analysis framework for several techniques of multivariate analysis in continuous-time setting. Specifically, we introduced continuous-time analogues of several classical techniques of multivariate analysis, such as principal component analysis, canonical correlation analysis, Fisher linear discriminant analysis, K-means clustering, and so on. Details are in Biplab Paul, Philip T. Reiss and Erjia Cui (2023) "Continuous-time multivariate analysis" <doi:10.48550/arXiv.2307.09404>.
| Version: | 1.4.0 |
| Imports: | fda, polynom |
| Suggests: | eegkit, corrplot |
| Published: | 2024-02-06 |
| Author: | Biplab Paul [aut, cre], Philip Tzvi Reiss [aut] |
| Maintainer: | Biplab Paul <paul.biplab497 at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | ctmva results |
| Reference manual: | ctmva.pdf |
| Package source: | ctmva_1.4.0.tar.gz |
| Windows binaries: | r-devel: ctmva_1.4.0.zip, r-release: ctmva_1.4.0.zip, r-oldrel: ctmva_1.4.0.zip |
| macOS binaries: | r-release (arm64): ctmva_1.4.0.tgz, r-oldrel (arm64): ctmva_1.4.0.tgz, r-release (x86_64): ctmva_1.4.0.tgz, r-oldrel (x86_64): ctmva_1.4.0.tgz |
| Old sources: | ctmva archive |
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