A comprehensive statistical computation library for Rust, providing distributions, functions, and utilities for scientific computing.
Statrs is a statistical computation library for Rust that provides a wide range of utilities for scientific computing. It includes probability distributions for sampling and common statistical functions, addressing the need for reliable and precise statistical analysis in Rust applications. The library emphasizes numerical accuracy and is tested against established reference data.
Rust developers working on scientific computing, data analysis, or statistical modeling projects who need robust and precise statistical tools.
Developers choose Statrs for its comprehensive set of statistical distributions and functions, strong focus on floating-point precision, and reliability through extensive testing against standards like NIST data.
Statistical computation library for Rust
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Implements a wide range of common distributions like Normal, Exponential, and Gamma for sampling, as detailed in the key features, providing robust tools for statistical analysis in Rust.
Emphasizes numerical accuracy with standardized precision checks and constants, documented in the prec module, ensuring reliable computations for scientific applications.
Validates against NIST reference data with provided scripts, as mentioned in the testing section, ensuring correctness and adherence to established standards.
Ported from the C# Math.NET library with borrowed unit tests, reducing implementation errors and providing a reliable base, as noted in the README.
The README admits planned future releases for more utilities, indicating current implementations are limited compared to mature libraries like SciPy, with gaps in advanced statistical methods.
Requires downloading external NIST data via a script for comprehensive testing, adding complexity and dependency management for developers, as per the testing instructions.
Changes like making the prec module private in v0.19.0 show potential breaking changes, which could affect long-term maintenance and customization, as highlighted in the precision section.