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.

