Crate stats_claw 

stats-claw — in-process, zero-dependency statistical computing for Rust.

Probability distributions, hypothesis tests, resampling, optimizers, streaming summaries, likelihood estimation, and supporting algorithms. Each distribution is a plain parameter struct over which the behaviour traits (Pdf/Cdf/Quantile/Sample/Moments) are implemented by hand.

Modules

algorithms

Machine-learning algorithms (unsupervised and supervised).

distributions

Probability distributions as plain parameter structs with behaviour traits.

error

Typed error and Result alias for the framework’s fallible numerics.

likelihood

Maximum-likelihood estimation: the generic MLE framework plus the concrete per-distribution likelihood models built on top of it.

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.