The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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UPDATE: As of 2020-06-09 ForeCA has been removed from CRAN, because the ifultools / sapa dependecies are no longer maintained.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.

References

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.