hcp_page_hinkley: Page-Hinkley change-point detector

In harbinger: A Unified Time Series Event Detection Framework

Page-Hinkley change-point detector

Description

Online change-point detection for univariate time series using the classical Page-Hinkley statistic. The detector accumulates deviations from the running mean and raises a changepoint when the cumulative score crosses the configured threshold.

This implementation is restricted to univariate numeric series. It is meant to capture virtual drift on the observed signal directly, without any classifier or multivariate preprocessing.

Usage

hcp_page_hinkley(
  min_instances = 30,
  delta = 0.005,
  threshold = 50,
  alpha = 1 - 1e-04
)

Arguments

min_instances	Minimum number of observations required before a change can be reported.
delta	Slack term subtracted from the deviation score.
threshold	Detection threshold for the cumulative statistic.
alpha	Forgetting factor applied to the cumulative score.

Value

An hcp_page_hinkley object.

References

• Page ES (1954). Continuous Inspection Schemes. Biometrika, 41(1/2), 100-115.

• Raab C, Heusinger M, Schleif FM (2020). Reactive Soft Prototype Computing for Concept Drift Streams. Neurocomputing.

harbinger documentation built on May 8, 2026, 5:07 p.m.