Expand description
Kendall’s tau rank correlation. At this point this is basically a copy-paste from Apache Commons Math library with some additions taken from scipy and R cor.test function
Example usage:
let (tau_b, significance) = kendalls::tau_b(&[1, 2, 3], &[3, 4, 5]).unwrap();
assert_eq!(tau_b, 1.0);
assert_eq!(significance, 1.5666989036012806);
If you want to compute correlation, let’s say, for f64
type, then you will have to
provide either a custom comparator function or declare Ord
trait for your custom floating point
numbers type (see float crate).
use std::cmp::Ordering;
let (tau_b, _significance) = kendalls::tau_b_with_comparator(
&[1.0, 2.0],
&[3.0, 4.0],
|a: &f64, b: &f64| a.partial_cmp(&b).unwrap_or(Ordering::Greater),
).unwrap();
assert_eq!(tau_b, 1.0);
The function will return an error if you pass empty arrays into it or x
and y
arrays’
dimensions are not equal.
Enums
Functions
Implementation of Kendall’s Tau-b rank correlation between two arrays.
The same as tau_b
but also allow to specify custom comparator for numbers for
which Ord trait is not defined.