inst/CONTRIBUTING.md
In dormancy: Detection and Analysis of Dormant Patterns in Data

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.