Crate ndarray_stats
source · [−]Expand description
The ndarray-stats crate exposes statistical routines for ArrayBase,
the n-dimensional array data structure provided by ndarray.
Currently available routines include:
- order statistics (minimum, maximum, median, quantiles, etc.);
- summary statistics (mean, skewness, kurtosis, central moments, etc.)
- partitioning;
- correlation analysis (covariance, pearson correlation);
- measures from information theory (entropy, KL divergence, etc.);
- measures of deviation (count equal, L1, L2 distances, mean squared err etc.)
- histogram computation.
Please feel free to contribute new functionality! A roadmap can be found here.
Our work is inspired by other existing statistical packages such as
NumPy (Python) and StatsBase.jl (Julia) - any contribution bringing us closer to
feature parity is more than welcome!
Modules
Custom errors returned from our methods and functions.
Histogram functionalities.
Interpolation strategies.
Traits
Extension trait for ArrayBase providing functions
to compute different correlation measures.
An extension trait for ArrayBase providing functions
to compute different deviation measures.
Extension trait for ArrayBase providing methods
to compute information theory quantities
(e.g. entropy, Kullback–Leibler divergence, etc.).
Extension trait for ArrayBase providing methods to compute histograms.
A number type that can have not-a-number values.
Extension trait for ArrayBase providing NaN-related functionality.
Quantile methods for 1-D arrays.
Quantile methods for ArrayBase.
Methods for sorting and partitioning 1-D arrays.
Extension trait for ArrayBase providing methods
to compute several summary statistics (e.g. mean, variance, etc.).