ctmva: Continuous-Time Multivariate Analysis
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, Erjia Cui and Noemi Foa (2025) "Continuous-time multivariate analysis" <doi:10.1080/10618600.2024.2374570>.
| Version: | 1.5.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | fda,polynom,MASS,mgcv,Matrix |
| Suggests: | dplyr,ggplot2,wbwdi |
| Published: | 2025-11-20 |
| DOI: | 10.32614/CRAN.package.ctmva |
| Author: | Biplab Paul [aut, cre], Philip Tzvi Reiss [aut], Noemi Foa [aut], Dror Arbiv [aut] |
| Maintainer: | Biplab Paul <paul.biplab497 at gmail.com> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | ctmva results |
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