u_analytics/detection/mod.rs
1//! Change-point and shift detection.
2//!
3//! Algorithms for detecting process mean shifts and trend changes, covering
4//! both **online** (sequential surveillance) and **offline** (retrospective)
5//! approaches.
6//!
7//! # Online Detection (Sequential Surveillance)
8//!
9//! - [`Cusum`] — Cumulative Sum chart (Page, 1954) for detecting small persistent shifts
10//! - [`Ewma`] — Exponentially Weighted Moving Average chart (Roberts, 1959)
11//!
12//! # Offline Detection (Retrospective Changepoint Analysis)
13//!
14//! - [`Pelt`] — Pruned Exact Linear Time algorithm (Killick et al., 2012) for
15//! detecting multiple changepoints with O(n) expected complexity
16//!
17//! # References
18//!
19//! - Page, E.S. (1954). "Continuous Inspection Schemes",
20//! *Biometrika* 41(1/2), pp. 100-115.
21//! - Roberts, S.W. (1959). "Control Chart Tests Based on Geometric Moving Averages",
22//! *Technometrics* 1(3), pp. 239-250.
23//! - Killick, R., Fearnhead, P., & Eckley, I.A. (2012). "Optimal Detection of
24//! Changepoints with a Linear Computational Cost", *JASA* 107(500), pp. 1590-1598.
25
26mod cusum;
27mod ewma;
28mod pelt;
29
30pub use cusum::{Cusum, CusumResult};
31pub use ewma::{Ewma, EwmaResult};
32pub use pelt::{CostFunction, MultiPeltResult, Pelt, PeltResult, Penalty};