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".

Package details

AuthorBiplab Paul [aut, cre], Philip Tzvi Reiss [aut]
MaintainerBiplab Paul <paul.biplab497@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the ctmva package in your browser

Any scripts or data that you put into this service are public.

ctmva documentation built on Aug. 18, 2022, 9:07 a.m.