Should be stable for both nightly and stable Rust
Statrs provides a host of statistical utilities for Rust scientific computing. Included are a number of common distributions that can be sampled (i.e. Normal, Exponential, Student's T, Gamma, Uniform, etc.) plus common statistical functions like the gamma function, beta function, and error function.
This library is a work-in-progress port of the statistical capabilities in the C# Math.NET library. All unit tests in the library borrowed from Math.NET when possible and filled-in when not.
This library is a work-in-progress and not complete. Planned for future releases are continued implementations of distributions (Beta, Dirichlet, etc.) as well as porting over more statistical utilities (population variance, quantile functions on slices / iterables)
Please check out the documentation here
Add the following to your Cargo.toml
Rust
[dependencies]
statrs = "0.1.0"
and this to your crate root
Rust
extern crate statrs;
Statrs v0.1.0 comes with a number of commonly used distributions including Normal, Gamma, Student's T, Exponential, Weibull, etc.
The common use case is to set up the distributions and sample from them which depends on the Rand crate for random number generation
```Rust use rand; use statrs::distribution::{Exponential, Distribution};
let mut r = rand::StdRng::new().unwrap();
let n = Exponential::new(0.5).unwrap();
print!("{}", n.Sample::
Statrs also comes with a number of useful utility traits for more detailed introspection of distributions
```Rust use statrs::distribution::{Exponential, Mean, Variance, Entropy, Skewness, Univariate, Continuous};
let n = Exponential::new(1.0).unwrap(); asserteq!(n.mean(), 1.0); asserteq!(n.variance(), 1.0); asserteq!(n.entropy(), 1.0); asserteq!(n.skewness(), 2.0); asserteq!(n.cdf(1.0), 0.6321205588285576784045); asserteq!(n.pdf(1.0), 0.3678794411714423215955); ```
as well as utility functions including erf, gamma, ln_gamma, beta, etc