Label error as a function of the penalty

Runs one detector across a penalty grid and counts label errors at each setting — the curve penalty learning is fitted to, and the honest way to see whether any penalty can satisfy the labels.

Usage

cpt_label_error_curve(
  x,
  labels,
  method = "pelt",
  penalties = NULL,
  change_in = "mean",
  ...
)

# S3 method for class 'ggcpt_label_curve'
print(x, ...)

# S3 method for class 'ggcpt_label_curve'
autoplot(object, ...)

Arguments

x

A ggcpt_label_curve object (for print()).

labels

A cpt_labels tibble.

method

Detection method. Defaults to "pelt".

penalties

Numeric vector of penalties to try. When NULL (the default) the grid is chosen adaptively: it starts below log(n), where the segmentation shatters, and the top end is found by doubling until the detector reports no changepoints at all. A fixed grid cannot do this — on a series with a large change, a grid that stops at a few hundred never produces a false negative, the error curve never turns back up, and the target interval comes out unbounded above, which is useless to cpt_learn_penalty(). The probe costs at most a dozen extra detector fits; pass penalties explicitly for an expensive engine.

change_in

Passed to the detector.

...

Additional arguments passed to cpt_detect().

object

A ggcpt_label_curve object (for autoplot()).

Value

A ggcpt_label_curve object: a tibble with penalty, n_cp, errors, false_positive, false_negative, plus print() and autoplot(). The target attribute holds the interval of log(penalty) achieving the minimum error, which is what cpt_learn_penalty() regresses on.

See also

cpt_learn_penalty(), cpt_select().

Examples

set.seed(2026)
x <- c(rnorm(60), rnorm(60, 4))
labs <- as_cpt_labels(60, n = 120)
curve <- cpt_label_error_curve(x, labs, penalties = c(2, 8, 32, 128))
curve
#> ggcpt_label_curve (method: pelt, 4 penalties)
#>   Minimum label errors: 0
#>   Target log-penalty interval: (2.079, Inf)
#> 
#> # A tibble: 4 × 5
#>   penalty  n_cp errors false_positive false_negative
#>     <dbl> <int>  <int>          <int>          <int>
#> 1       2    24      3              3              0
#> 2       8     1      0              0              0
#> 3      32     1      0              0              0
#> 4     128     1      0              0              0