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CausalLoopAnalytics: Data-Driven Causal Loop and Feedback Network Analysis

Provides tools for constructing signed causal-loop models, discovering directed causal relationships from time-series data using Granger-style tests, identifying and classifying reinforcing and balancing feedback loops, quantifying loop strength, assessing loop stability by bootstrap resampling, calculating network centrality and leverage-point scores, comparing causal-loop models, and producing publication-ready base R visualizations and summaries. The package is domain-agnostic and can be used in human medicine, veterinary medicine, agriculture, epidemiology, ecology, public health, and One Health. Methods are based on Granger (1969) <doi:10.2307/1912791> and Efron (1979) <doi:10.1214/aos/1176344552>.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: stats, graphics
Suggests: testthat (≥ 3.0.0)
Published: 2026-09-21
DOI: 10.32614/CRAN.package.CausalLoopAnalytics (may not be active yet)
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran at gmail.com>
BugReports: https://github.com/vinodhpmd/CausalLoopAnalytics/issues
License: MIT + file LICENSE
URL: https://github.com/vinodhpmd/CausalLoopAnalytics
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: CausalLoopAnalytics results

Documentation:

Reference manual: CausalLoopAnalytics.html , CausalLoopAnalytics.pdf

Downloads:

Package source: CausalLoopAnalytics_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): CausalLoopAnalytics_1.0.0.tgz, r-release (x86_64): CausalLoopAnalytics_1.0.0.tgz, r-oldrel (x86_64): CausalLoopAnalytics_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=CausalLoopAnalytics to link to this page.

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.
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