Whoever would wish to contribute to this pkg, please find here the implementatioin structure of the package:
dormancy/
├── R/
│ ├── dormancy_detect.R # Core detection (4 methods)
│ ├── dormancy_trigger.R # Identify trigger conditions
│ ├── dormancy_depth.R # Measure dormancy depth
│ ├── dormancy_risk.R # Risk assessment
│ ├── dormancy_scout.R # Terrain mapping
│ ├── awaken.R # Activation simulation
│ ├── hibernate.R # Temporal dormancy detection
│ └── plot.R # Visualization
├── src/
│ └── dormancy.cpp # Rcpp performance layer
├── tests/
├── vignettes/
└── [CRAN-ready metadata]I’ve created dormancy R package, after seamlessly searching for a tools that could find dormant patterns in data, however I couldn’t find one that is completely ready to use with a user-friendly implementation. As there is never existed an R package before, the idea of create one came into mind, and i hope, it could help others that will want to use it.
Here’s what makes it unique:
The Novel Concept:
Dormant patterns are statistical relationships that exist in your data but are currently inactive - they only emerge when specific trigger conditions are met. This concept is inspired by:
- Seed dormancy in botany (seeds wait for right conditions)
- Fault dormancy in geology (earthquakes after years of silence)
- Latent infections in epidemiology (viruses that activate under stress)
No existing R package addresses this problem. Traditional correlation analysis misses dormant patterns because they’re hidden in aggregate statistics.