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Bayesian Online Change Point Detection

Source: R/hcp_bocpd.R
hcp_bocpd.Rd

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.