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


Reference manual: ctmva.pdf


Package source: ctmva_1.0.tar.gz
Windows binaries: r-devel: ctmva_1.0.zip, r-release: ctmva_1.0.zip, r-oldrel: ctmva_1.0.zip
macOS binaries: r-release (arm64): ctmva_1.0.tgz, r-oldrel (arm64): ctmva_1.0.tgz, r-release (x86_64): ctmva_1.0.tgz, r-oldrel (x86_64): ctmva_1.0.tgz


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