The model proposes a robust methodology for detecting and reconstructing the hidden structure of dynamic complex systems through short-term forecasts and information embedded in reconstructed state spaces. The approach not only identifies critical components and causal interactions within these systems but also provides a practical tool for optimizing system performance and stability.
Version: | 0.1.2 |
Depends: | R (≥ 4.1.0) |
Imports: | stats |
Suggests: | knitr, rmarkdown, stringr, ggplot2, testthat (≥ 3.0.0) |
Published: | 2024-08-22 |
DOI: | 10.32614/CRAN.package.patterncausality |
Author: | Stavros Stavroglou
|
Maintainer: | Hui Wang <huiw1128 at gmail.com> |
BugReports: | https://github.com/skstavroglou/pattern_causality/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/skstavroglou/pattern_causality/ |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | patterncausality results |
Reference manual: | patterncausality.pdf |
Vignettes: |
Introduction to patterncausality (source, R code) |
Package source: | patterncausality_0.1.2.tar.gz |
Windows binaries: | r-devel: patterncausality_0.1.2.zip, r-release: patterncausality_0.1.2.zip, r-oldrel: patterncausality_0.1.2.zip |
macOS binaries: | r-release (arm64): patterncausality_0.1.2.tgz, r-oldrel (arm64): patterncausality_0.1.0.tgz, r-release (x86_64): patterncausality_0.1.2.tgz, r-oldrel (x86_64): patterncausality_0.1.0.tgz |
Old sources: | patterncausality archive |
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