Module correlation 

Correlation analysis.

Pearson, Spearman, and Kendall correlation coefficients with p-values, correlation matrices, and Fisher z-transformation confidence intervals.

Examples

use u_analytics::correlation::{pearson, spearman, kendall_tau_b};

let x = [1.0, 2.0, 3.0, 4.0, 5.0];
let y = [2.0, 4.0, 5.0, 4.0, 5.0];

let p = pearson(&x, &y).unwrap();
assert!(p.r > 0.7);
assert!(p.p_value < 0.2);

let s = spearman(&x, &y).unwrap();
assert!(s.r > 0.7);

let k = kendall_tau_b(&x, &y).unwrap();
assert!(k.r > 0.5);

Structs

AcfResult

Result of autocorrelation analysis.

CorrelationCI

Confidence interval for a correlation coefficient.

CorrelationResult

Result of a correlation computation.

PacfResult

Result of partial autocorrelation analysis.

Functions

acf

Compute the sample autocorrelation function (ACF).

correlation_ci

Computes confidence interval for a Pearson correlation coefficient using Fisher z-transformation.

correlation_matrix

Computes a pairwise Pearson correlation matrix.

fisher_z

Computes Fisher z-transformation: z = arctanh(r).

fisher_z_inv

Inverse Fisher z-transformation: r = tanh(z).

kendall_tau_b

Computes Kendall’s tau-b correlation coefficient with tie correction.

pacf

Compute the sample partial autocorrelation function (PACF) via Durbin-Levinson recursion.

pearson

Computes Pearson product-moment correlation coefficient and p-value.

spearman

Computes Spearman rank correlation coefficient and p-value.

spearman_matrix

Computes a pairwise Spearman rank correlation matrix.