Expand description
stats-claw — data science on the hot path.
An in-process, zero-runtime-dependency statistical computing library for
Rust: probability distributions, hypothesis tests, resampling, optimizers,
streaming summaries, and supporting algorithms. The numerics are validated
against committed scipy.stats golden fixtures within documented tolerances.
Each distribution is a plain parameter struct (in distributions) over
which the behaviour traits (Pdf/Cdf/Quantile/Sample/Moments/
LogCdf) are implemented by hand.
Modules§
- algorithms
- Unsupervised learning algorithms.
- distributions
- Probability distributions: parameter structs plus their behaviour traits.
- error
- Typed error and
Resultalias for the framework’s fallible numerics. - optimizers
- Numerical optimizers minimizing an
Objective. - resampling
- Resampling-based inference: seeded bootstrap, permutation, and CV splits, plus the percentile confidence-interval estimator built on top of them.
- rng
- Deterministic pseudo-random number generation and sampling primitives.
- special
- Special mathematical functions underpinning the distribution numerics.
- streaming
- Online (streaming) estimators that run in bounded memory.
- tests_
stat - Statistical hypothesis tests and their effect-size reporting.