Crate ndarray_stats

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!

Re-exports

• pub use crate::histogram::HistogramExt;

Modules

• errors
  Custom errors returned from our methods and functions.
• histogram
  Histogram functionalities.
• interpolate
  Interpolation strategies.

Traits

• CorrelationExt
  Extension trait for ArrayBase providing functions to compute different correlation measures.
• DeviationExt
  An extension trait for ArrayBase providing functions to compute different deviation measures.
• EntropyExt
  Extension trait for ArrayBase providing methods to compute information theory quantities (e.g. entropy, Kullback–Leibler divergence, etc.).
• MaybeNan
  A number type that can have not-a-number values.
• MaybeNanExt
  Extension trait for ArrayBase providing NaN-related functionality.
• Quantile1dExt
  Quantile methods for 1-D arrays.
• QuantileExt
  Quantile methods for ArrayBase.
• Sort1dExt
  Methods for sorting and partitioning 1-D arrays.
• SummaryStatisticsExt
  Extension trait for ArrayBase providing methods to compute several summary statistics (e.g. mean, variance, etc.).