Rstats - Rust Stats

Rstats is a lean minimalistic library that only depends on anyhow (for its error handling). Trait RStats is carefully checked and will report all kinds of errors, such as empty input. Trait Vectors is unchecked to achieve speed, so some caution is advisable.

Basic statistical measures and vector algebra are implemented for self-sufficiency. Beyond that, this package is particularly useful for analysis of multidimensional sets of points, with applications in Machine Learning.

Trait RStats

Statistical measures implemented for &[i64] and &[f64] slices. All these methods operate on one vector of data and take no arguments. For example, s.amean() computes the arithmetic mean of slice s of either type.

Included are:

• means (arithmetic, geometric and harmonic),
• standard deviations,
• linearly weighted means (useful for time dependent data analysis),
• median and quartiles.

Trait Vectors

Vector algebra implemented for &[f64] slices of any length (dimensions of space). First there are functions applying to just one and two vectors. Then there are functions expressing the relationships of one vector to a whole set of vectors. Should you get errors when applying them to Vec<f64>, just convert the vectors to &[f64] using .as_slice(). See doc examples.

Trait MutVectors

Some of the above basic Vector methods are for memory efficiency reasons reimplemented so that they mutate self in place instead of creating a new Vec. They are useful in vector iterative methods. Beware that some of these methods do not return anything, so they can not be chained.

Releases

• Version 0.4.6 Made eccentricity measure continuous. Added Kendall's Tau (rank) correlation. Moved all correlations to Vectors trait. Improved readme and doc comments.

• Version 0.4.4 Medoid now finds the Outlier as well. Improved tests. Defined and added MOE = median of eccentricities (spread) of multivariate data.

• Version 0.4.3 Introduced computation of nmedian residual errors. Improved tests and benchmarks.

• Version 0.4.2 Added eccentricity measures.

• Version 0.4.1 Tidier testing and benchmarks.

• Version 0.4.0 Cleanup. Changed the implementation types from Vecs to slices everywhere for consistency. You may need more .as_slice() conversions here and there. Made some subsidiary functions private.