https://github.com/usace-rmc/numerics
Numerics is a free and open-source library for .NET developed by USACE-RMC, providing a comprehensive set of methods and algorithms for numerical computations and statistical analysis.
https://github.com/usace-rmc/numerics
machine-learning mcmc-sampling optimization probability-distribution statistics
Last synced: 2 months ago
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Numerics is a free and open-source library for .NET developed by USACE-RMC, providing a comprehensive set of methods and algorithms for numerical computations and statistical analysis.
- Host: GitHub
- URL: https://github.com/usace-rmc/numerics
- Owner: USACE-RMC
- License: other
- Created: 2023-09-27T18:43:19.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-04-06T17:08:14.000Z (2 months ago)
- Last Synced: 2026-04-06T18:15:37.271Z (2 months ago)
- Topics: machine-learning, mcmc-sampling, optimization, probability-distribution, statistics
- Language: C#
- Homepage:
- Size: 16.7 MB
- Stars: 30
- Watchers: 4
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Codemeta: codemeta.json
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README
# Numerics
[](https://github.com/USACE-RMC/Numerics/actions/workflows/Integration.yml)
[](https://www.nuget.org/packages/RMC.Numerics/)
[](https://doi.org/10.5281/zenodo.19444369)
[](LICENSE)
***Numerics*** is a free and open-source numerical computing library for .NET developed by the U.S. Army Corps of Engineers Risk Management Center (USACE-RMC). It provides methods and algorithms for probability distributions, statistical analysis, numerical methods, optimization, machine learning, and Bayesian MCMC sampling — with a focus on hydrological and risk assessment applications.
## Supported Frameworks
| Framework | Version |
|-----------|---------|
| .NET | 10.0, 9.0, 8.0 |
| .NET Framework | 4.8.1 |
Install via NuGet:
```
dotnet add package RMC.Numerics
```
Or search for [RMC.Numerics](https://www.nuget.org/packages/RMC.Numerics/) in the NuGet Package Manager.
## Documentation
**[User Guide and API Documentation](docs/index.md)** — Comprehensive documentation with code examples and mathematical explanations.
| Section | Topics |
|---------|--------|
| [Mathematics](docs/mathematics/integration.md) | Integration, differentiation, optimization, root finding, linear algebra, ODE solvers, special functions |
| [Data](docs/data/interpolation.md) | Interpolation, linear regression, time series analysis |
| [Statistics](docs/statistics/descriptive.md) | Descriptive statistics, goodness-of-fit metrics, hypothesis tests |
| [Distributions](docs/distributions/univariate.md) | 40+ univariate distributions, parameter estimation, uncertainty analysis, copulas, multivariate distributions |
| [Machine Learning](docs/machine-learning/machine-learning.md) | GLM, decision trees, random forests, KNN, naive Bayes, k-means, GMM |
| [Sampling](docs/sampling/mcmc.md) | MCMC (RWMH, ARWMH, DE-MCz, HMC, NUTS, Gibbs), random generation, convergence diagnostics |
| [References](docs/references.md) | Consolidated bibliography |
## Support
USACE-RMC is committed to maintaining and supporting the library with regular updates, bug fixes, and enhancements.
The repository includes a unit testing library with over 1,000 tests that also serve as usage examples for the classes and methods in the library.
## Contributing
Contributions are welcome. Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on bug reports, feature requests, and pull requests.
## License
See [LICENSE](LICENSE) for details.