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Confidence intervals for changepoint locations

Source: R/inference.R
cpt_confint.Rd

Answers "where could this changepoint be?" for any result, and says which of four routes it used. show_ci = TRUE in autoplot() works only for the handful of engines that ship intervals of their own; this generic covers the rest, and — because the four routes mean genuinely different things — reports the provenance in a source column rather than presenting them as interchangeable.

Usage

cpt_confint(
  object,
  level = 0.95,
  method = c("auto", "native", "nsp", "bootstrap", "posterior"),
  B = 200,
  seed = NULL,
  ...
)

Arguments

object

A ggcpt object.

level

Confidence/credible level. Defaults to 0.95. Ignored by method = "native", which reports the interval the engine already computed at whatever level it was asked for.

method

Which route to use:

"auto"

(default) native if the engine supplied intervals, else posterior if it supplied one, else bootstrap.

"native"

the engine's own ci_lower/ci_upper (SMUCE/HSMUCE simultaneous confidence sets, strucchange break-date intervals, segmented breakpoint intervals).

"nsp"

Narrowest Significance Pursuit regions computed on the same series and matched to the changepoints. These are not intervals around an estimate — see nsp_wrapper() — but they are the strongest guarantee available, so the mapping is reported as source = "nsp_region" and a changepoint in no region gets NA.

"bootstrap"

within-segment residual resampling (the cpt_stability() scheme), re-running the detector and taking quantiles of the re-detected location. Model-agnostic and available for every engine; it measures the sampling variability of the procedure, conditional on the fitted segmentation, and it is not exact.

"posterior"

a credible interval from the engine's posterior changepoint-probability profile (bcp, beast).

B

Bootstrap replicates for method = "bootstrap". Defaults to 200.

seed

Optional seed (bootstrap and NSP are both random).

...

Passed to cpt_detect() on the bootstrap replicates, or to nsp_wrapper().

Value

A tibble with one row per changepoint: cp, ci_lower, ci_upper, level, source, plus cp_index/ci_lower_index/ci_upper_index on the original scale when the result carries a time index, and n_replicates for method = "bootstrap" (how many replicates actually contributed a draw for that changepoint). method = "nsp" returns NA bounds for a changepoint that falls in no region, which is a finding rather than a failure.

See also

cpt_test(), cpt_stability(), nsp_wrapper().

Examples

set.seed(2026)
x <- c(rnorm(80), rnorm(80, 4))
fit <- cpt_detect(x, method = "pelt")
cpt_confint(fit, method = "bootstrap", B = 25, seed = 1)
#> # A tibble: 1 × 6
#>      cp ci_lower ci_upper level source    n_replicates
#>   <int>    <int>    <int> <dbl> <chr>            <int>
#> 1    80       80       80  0.95 bootstrap           25