v2.0.1 — Zenodo Archival

Patch release for Zenodo DOI archival. For the full v2.0.0 release notes, see: https://github.com/USACE-RMC/Numerics/releases/tag/v2.0.0

v2.0.0 — Major Update

v2.0.0 — Major Update

This is a major update to Numerics with 274 files changed since v1.0.0. Highlights include new distributions, improved MCMC inference, enhanced numerical methods, and comprehensive documentation.

New Distributions

• Dirichlet distribution (multivariate)
• Multinomial distribution (multivariate)
• Multivariate Student-t distribution
• Student-t copula
• Von Mises distribution for circular data
• Enhanced Competing Risks distribution

Bayesian Inference & MCMC

• Added No-U-Turn sampler (NUTS) with adaptive tuning parameters
• Improved Gelman-Rubin convergence diagnostics
• Enhanced MCMC sampler reliability and convergence

Numerical Methods

• Bessel functions of the first and second kind
• Linear algebra enhancements
• Root-finding improvements
• ODE solver improvements
• Improved adaptive integration

Functions

• Link function framework (Identity, Logit, Log, Probit, Complementary Log-Log)

Data & Statistics

• Bootstrap analysis overhaul with new BootstrapResults class
• Time series download improvements
• Hypothesis test enhancements
• Enhanced parameter estimation methods
• Autocorrelation and convergence diagnostics improvements

Optimization

• Comprehensive correctness improvements across all optimizers

Machine Learning

• Generalized Linear Model enhanced with full link function support
• Code quality improvements

Infrastructure & Documentation

• Added .NET 10.0 target framework (now targets net8.0, net9.0, net10.0, net481)
• Zero runtime dependencies maintained
• 1,700+ unit tests validated against published references
• JOSS paper and metadata (CITATION.cff, codemeta.json)
• CONTRIBUTING.md and CODE_OF_CONDUCT.md
• 25+ documentation files covering all library capabilities
• NuGet publishing workflow for nuget.org

Numerics v1.0.0

We're thrilled to introduce the public release of the USACE-RMC Numerics library. This foundational library serves as the bedrock of the RMC software suite, powering critical tools like RMC-RFA, RMC-BestFit, RMC-TotalRisk, and LifeSim.

Key Features and Improvements:

The Numerics library includes a robust collection of numerical algorithms for tasks such as:

• Interpolation
• Regression
• Statistics
• Time series analysis
• Probability distributions
• Linear algebra
• Numerical integration
• Global and local optimization
• Machine learning
• Bootstrap uncertainty analysis
• Bayesian MCMC

Extensive Documentation

The library includes clear and detailed XML documentation to guide users in effectively leveraging the library's capabilities.

Example Use Cases

• Risk Assessment: Quantifying uncertainties and risks in engineering projects.
• Data Analysis: Exploring and analyzing large datasets to identify trends and patterns.
• Decision Support: Providing valuable insights to inform informed decision-making.

Getting Started

We recommend using NuGet for convenient installation of the RMC.Numerics package.

Join the Community

We invite you to become part of the Numerics community. Share your feedback, contribute to development, and collaborate with other users.

Future Plans

We're committed to the ongoing development and improvement of the Numerics library. Future releases will introduce new features, enhancements, and optimizations to meet the evolving needs of our users.

Thank you for your support!