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 Philip T Reiss and Biplab Paul (2022) "Continuous-time multivariate analysis";
James O Ramsay, Bernard W Silverman (2005) <ISBN:978-0-387-22751-1> "Functional Data Analysis";
James O Ramsay, Giles Hooker and Spencer Graves (2009) <ISBN:978-0-387-98185-7> "Functional Data Analysis with R and MATLAB".
| Version: |
1.0 |
| Imports: |
fda, polynom |
| Suggests: |
eegkit, corrplot |
| Published: |
2022-08-18 |
| 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 |
Documentation:
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