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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.6.0 |
2026-04-09 windows/windows R-4.5 | ctmva_1.6.0.zip |
144.7 KiB |