ForeCA (0.2.0)

Forecastable Component Analysis.

Forecastable Component Analysis (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. This R package provides the main algorithms and auxiliary function (summary, plotting, etc.) to apply ForeCA to multivariate time series data.

Maintainer: Georg M. Goerg
Author(s): Georg M. Goerg <>

License: GPL-2

Uses: Does not use any package
Reverse suggests: feasts

Released over 5 years ago.