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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | CausalLoopAnalytics_1.0.0.tar.gz |
83.7 KiB |
1.0.0 |
rolling linux/noble R-4.5 | CausalLoopAnalytics_1.0.0.tar.gz |
83.4 KiB |
1.0.0 |
rolling source/ R- | CausalLoopAnalytics_1.0.0.tar.gz |
17.8 KiB |
1.0.0 |
latest linux/jammy R-4.5 | CausalLoopAnalytics_1.0.0.tar.gz |
83.7 KiB |
1.0.0 |
latest linux/noble R-4.5 | CausalLoopAnalytics_1.0.0.tar.gz |
83.4 KiB |
1.0.0 |
latest source/ R- | CausalLoopAnalytics_1.0.0.tar.gz |
17.8 KiB |
1.0.0 |
2026-04-23 source/ R- | CausalLoopAnalytics_1.0.0.tar.gz |
0 B |