fpop_wrapper: FPOP wrapper: Functional Pruning Optimal Partitioning

In ggchangepoint: Combines Changepoint Analysis with 'ggplot2'

FPOP wrapper: Functional Pruning Optimal Partitioning

Description

Wraps the fpop package for optimal changepoint detection via functional pruning.

Usage

fpop_wrapper(x, penalty = NULL, ...)

Arguments

x	A numeric vector.
penalty	Penalty value. Defaults to 2 * log(length(x)) (BIC). This is an absolute penalty on the residual sum of squares, so it is only calibrated for noise of standard deviation 1: on wider data the default under-penalises badly and the segmentation shatters. Standardise the series, or scale the penalty by the noise variance (for example 2 * log(length(x)) * stats::var(diff(x)) / 2). See the scale-sensitivity section of cpt_detect. This default differs from the one cpt_detect applies, which resolves its "MBIC" default to a stronger numeric value, so the two entry points need not agree unless penalty is given.
...	Additional arguments passed to fpop::Fpop().

Details

fpop was archived from CRAN in 2026 at its maintainer's request and is still built on R-Forge, where it is developed. Install it with install.packages("fpop", repos = "https://R-Forge.R-project.org"), or with cpt_install_engines("core").

Value

A ggcpt object.

References

\insertRef

maidstone2017optimalggchangepoint

See Also

Other changepoint engines: bcp_wrapper(), beast_wrapper(), bfast_wrapper(), binsegrcpp_wrapper(), bocpd_wrapper(), capa_wrapper(), cpm_wrapper(), cpop_wrapper(), cpt_wrapper(), decafs_wrapper(), ecp_wrapper(), envcpt_wrapper(), esac_wrapper(), fabisearch_wrapper(), fastcpd_wrapper(), fcov_wrapper(), fmean_wrapper(), geomcp_wrapper(), hdcov_wrapper(), hdreg_wrapper(), idetect_wrapper(), inspect_wrapper(), kcp_wrapper(), kwc_wrapper(), mcp_wrapper(), mosum_wrapper(), network_wrapper(), not_wrapper(), npmojo_wrapper(), nsp_wrapper(), ocd_wrapper(), pilliat_wrapper(), segmented_wrapper(), smuce_wrapper(), sn_wrapper(), strucchange_wrapper(), taylor_wrapper(), tguh_wrapper(), trend_wrapper(), var_wrapper(), wbs2_wrapper(), wbs_wrapper(), wbsts_wrapper()

Examples

set.seed(2026)
x <- c(rnorm(60), rnorm(60, 4))
fpop_wrapper(x)$changepoints
# the default penalty assumes sd 1; scale it for wider noise
y <- 5 * x
fpop_wrapper(y, penalty = log(length(y)) * var(diff(y)))$changepoints

ggchangepoint documentation built on Nov. 5, 2026, 9:06 a.m.