Package: ForeCA
Type: Package
Title: Forecastable Component Analysis
Version: 0.2.7
Date: 2020-06-21
Authors@R: 
    person(given = "Georg M.",
           family = "Goerg",
           role = c("aut", "cre"),
           email = "im@gmge.org")
URL: https://github.com/gmgeorg/ForeCA
Description: Implementation of Forecastable Component Analysis ('ForeCA'),
    including main algorithms and auxiliary function (summary, plotting, etc.) to
    apply 'ForeCA' to multivariate time series data. 'ForeCA' is a novel dimension
    reduction (DR) technique for temporally dependent signals. Contrary to other
    popular DR methods, such as 'PCA' or 'ICA', 'ForeCA' takes time dependency
    explicitly into account and searches for the most ''forecastable'' signal.
    The measure of forecastability is based on the Shannon entropy of the spectral
    density of the transformed signal.
Depends: R (>= 3.5.0)
License: GPL-2
Imports: astsa (>= 1.10), MASS, graphics, reshape2 (>= 1.4.4), utils
Suggests: psd, fBasics, knitr, markdown, mgcv, nlme (>= 3.1-64),
        testthat (>= 2.0.0), rSFA,
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-06-29 01:43:22 UTC; georg
Author: Georg M. Goerg [aut, cre]
Maintainer: Georg M. Goerg <im@gmge.org>
Repository: CRAN
Date/Publication: 2020-06-29 12:40:42 UTC
Built: R 4.6.0; ; 2026-04-26 03:38:18 UTC; unix
