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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