CRAN/E | ForeCA

ForeCA

Forecastable Component Analysis

Installation

About

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.

github.com/gmgeorg/ForeCA

Key Metrics

Version 0.2.7
R ≥ 3.5.0
Published 2020-06-29 1369 days ago
Needs compilation? no
License GPL-2
CRAN checks ForeCA results

Downloads

Yesterday 27 0%
Last 7 days 67 -37%
Last 30 days 462 -22%
Last 90 days 1.606 -21%
Last 365 days 8.580 -34%

Maintainer

Maintainer

Georg M. Goerg

im@gmge.org

Authors

Georg M. Goerg

aut / cre

Material

README
Package source

In Views

TimeSeries

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ForeCA archive

Depends

R ≥ 3.5.0

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