ForeCA R package

ForeCA implements Forecastable component analysis in R. For details on algorithm & methodology see Forecastable Component Analysis, JMLR, Goerg (2013).

In a nutshell: ForeCA finds linear combinations of multivariate time series that are most forecastable, where forecastability is measured by the spectral entropy of the resulting signal (linear combination of input).

Installation

UPDATE: As of 2020-06-09 ForeCA has been removed from CRAN, because the ifultools / sapa dependecies are no longer maintained. I am working on an update to ForeCA to not rely on these packages, but only rely on astsa for multivariate specturm estimation. See NEWS.md for details.

In the meantime you can install the ForeCA package directly from github as

library(devtools)
devtools::install_github("gmgeorg/ForeCA")

Temporarily not working

You can install the stable version on CRAN:

install.packages('ForeCA')

Usage

The workhorse function is ForeCA::foreca() which works just like the built-in princomp function for PCA.

library(ForeCA)
citation("ForeCA")

For a tutorial on how to use foreca() and the entire ForeCA suite of functions see the introductory vignette on CRAN.

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Install

install.packages('ForeCA')

Monthly Downloads

474

Version

0.2.7

License

GPL-2

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Last Published

June 29th, 2020

Functions in ForeCA (0.2.7)