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1.2
date	2025.01.30.05.33.49;	author pho;	state Exp;
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1.1
date	2023.11.02.02.47.40;	author pho;	state Exp;
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1.2
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@math/hs-statistics: update to statistics-0.16.3.0

## Changes in 0.16.3.0

 * `S.Sample.correlation`, `S.Sample.covariance`,
   `S.Correlation.pearson` do not allocate temporary arrays.

 * Variants of correlation which take two vectors as input are added:
   `S.Sample.correlation2`, `S.Sample.covariance2`, `S.Correlation.pearson2`,
   `S.Correlation.spearman2`.

 * Contexts for `S.Function.indexed`, `S.Correlation.spearman`, `S.pairedTTest`,
   `S.Sample.correlation`, `S.Sample.covariance`, reduced.

 * Computation of `rSquare` in linear regression has special case for case when
   data variation is 0.

 * Doctests added.

 * Benchmarks using `tasty-bench` and `tasty-papi` added.

 * Spurious test failures fixed.
@
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Size (statistics-0.16.3.0.tar.gz) = 108444 bytes
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1.1
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@math/hs-statistics: import hs-statistics-0.16.2.1

This library provides a number of common functions and types useful in
statistics. We focus on high performance, numerical robustness, and use of
good algorithms. Where possible, we provide references to the statistical
literature.

The library's facilities can be divided into four broad categories:

* Working with widely used discrete and continuous probability
  distributions. (There are dozens of exotic distributions in use; we focus
  on the most common.)

* Computing with sample data: quantile estimation, kernel density
  estimation, histograms, bootstrap methods, significance testing, and
  regression and autocorrelation analysis.

* Random variate generation under several different distributions.

* Common statistical tests for significant differences between samples.
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@