hcp_bocpd: Bayesian Online Change Point Detection

In harbinger: A Unified Time Series Event Detection Framework

Bayesian Online Change Point Detection

Description

Online Bayesian change-point detection using the ocp package.

This implementation follows the Adams & MacKay formulation and uses the ocp backend to infer changepoint evidence over the full series.

Usage

hcp_bocpd(
  hazard = 100,
  dist = c("gaussian", "poisson"),
  threshold = NULL,
  min_distance = 5,
  burn_in = 5
)

Arguments

hazard	Positive scalar controlling the constant hazard function.
dist	Probability model used by ocp; one of "gaussian" or "poisson".
threshold	Numeric threshold for changepoint evidence.
min_distance	Minimum distance between selected changepoints.
burn_in	Number of initial observations to ignore.

Value

An hcp_bocpd object.

References

• Adams RP, MacKay DJC (2007). Bayesian Online Changepoint Detection. arXiv:0710.3742

• Pagotto A (2019). ocp: Bayesian Online Changepoint Detection. R package.

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