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CROPS — the full penalty path of a penalised changepoint method

Source: R/crops.R
cpt_crops.Rd

Runs PELT once per distinct optimal segmentation as the penalty ranges over [pen_min, pen_max], using the CROPS algorithm of Haynes, Eckley and Fearnhead (2017) as implemented by the changepoint package. Instead of committing to one penalty, the analyst sees every segmentation the data admits along the path, together with its cost, and picks the elbow.

Usage

cpt_crops(
  x,
  change_in = c("mean", "var", "meanvar"),
  pen_min = NULL,
  pen_max = NULL,
  ...
)

# S3 method for class 'ggcpt_path'
autoplot(
  object,
  type = c("elbow", "path", "segmentations"),
  max_facets = 12,
  ...
)

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

# S3 method for class 'ggcpt_path'
tidy(x, ...)

Arguments

x

For cpt_crops(), a numeric vector; for the print() and tidy() methods, a ggcpt_path object.

change_in

What to detect change in: "mean", "var", or "meanvar". Defaults to "mean".

pen_min, pen_max

The penalty interval to sweep. Default to log(n) and 10 * log(n).

...

Additional arguments passed to the underlying changepoint::cpt.mean(), cpt.var(), or cpt.meanvar() call.

object

A ggcpt_path object (for autoplot()).

type

Plot type for autoplot(): "elbow" (cost against number of changepoints, the classic CROPS diagnostic), "path" (number of changepoints against penalty), or "segmentations" (the data faceted by solution, with that solution's changepoints drawn).

max_facets

Maximum number of solutions shown by type = "segmentations". Defaults to 12.

Value

A ggcpt_path object: a list with a solutions tibble (one row per distinct segmentation: penalty, n_cpts, cost, and a cpts list-column), the data, and metadata. Methods: print(), tidy(), and autoplot() (elbow plot by default; type = "path" for penalty vs. number of changepoints; type = "segmentations" for the faceted segmentations).

References

Haynes K, Eckley IA, Fearnhead P (2017). “Computationally efficient changepoint detection for a range of penalties.” Journal of Computational and Graphical Statistics, 26(1), 134–143.

Killick R, Eckley I (2014). “changepoint: An R package for changepoint analysis.” Journal of statistical software, 58(3), 1–19.

Examples

set.seed(2026)
x <- c(rnorm(100), rnorm(100, 3), rnorm(100, -1))
path <- cpt_crops(x)
path
#> ggcpt_path (CROPS penalty path)
#>   Change in:       mean 
#>   Penalty range:  [5.704, 57.04]
#>   Series length:   300 
#>   Distinct segmentations: 2 
#> 
#> # A tibble: 2 × 3
#>   penalty n_cpts  cost
#>     <dbl>  <int> <dbl>
#> 1    6.11      2  268.
#> 2    5.70      4  255.
ggplot2::autoplot(path)

ggplot2::autoplot(path, type = "segmentations")