ForeCA
0.2.7Forecastable Component Analysis
Overview
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.
Install
Health
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- NOTE2026-03-300 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-03-100 OK · 13 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Documentation
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Repository
Repository practices
Checks run against github.com/gmgeorg/foreca on 2026-07-19.
No development-tooling practices detected in the upstream repository.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
9 releases. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.2.7Latest
- unarchivedReturned to CRAN2020-06-29
- archivedRemoved from CRAN2020-06-09required 'ifultools' Which was orphaned and is now archived
- 0.2.62020-05-11 · diff ↗
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 0.2.42016-03-30 · diff ↗
Package metadata
- First published
- 2012-05-21
- Total releases
- 9 / 14 yrs
- License
- GPL-2 OSI
- Download size
- 310 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet