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Functional mean changepoints

Source: R/wrap-functional.R
fmean_wrapper.Rd

Wraps fChange::fchange() for changes in the mean function of a functional time series: each observation is a curve, and the question is when the average curve shape changes. The binary-segmentation ("segmentation") mode finds multiple changes; the "single" mode runs the one-change test and reports its p-value.

Usage

fmean_wrapper(
  x,
  statistic = c("Tn", "Mn"),
  critical = c("simulation", "resample", "welch"),
  type = c("segmentation", "single"),
  alpha = 0.05,
  robust = FALSE,
  ...
)

Arguments

x

A numeric matrix or data frame with one row per time point and one column per grid location (the curve's resolution).

statistic

Test statistic: "Tn" (integrated, the default) or "Mn" (maximum).

critical

How critical values are obtained: "simulation" (default), "resample" or "welch".

type

"segmentation" (default, multiple changes) or "single" (one change).

alpha

Significance level. Defaults to 0.05.

robust

Use the robust ("robustmean") statistic instead of the classical mean one? Defaults to FALSE.

...

Additional arguments passed to fChange::fchange().

Value

A ggcpt object; the changepoints tibble carries the engine's p_value for each location.

References

Aue A, Rice G, Sönmez O (2018). “Detecting and dating structural breaks in functional data without dimension reduction.” Journal of the Royal Statistical Society: Series B, 80(3), 509–529. doi:10.1111/rssb.12257 .

See also

Other changepoint engines: bcp_wrapper(), beast_wrapper(), bfast_wrapper(), binsegrcpp_wrapper(), bocpd_wrapper(), cpm_wrapper(), cpop_wrapper(), cpt_wrapper(), decafs_wrapper(), ecp_wrapper(), envcpt_wrapper(), esac_wrapper(), fabisearch_wrapper(), fastcpd_wrapper(), fcov_wrapper(), fpop_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

# \donttest{
set.seed(2026)
X <- matrix(rnorm(60 * 20), nrow = 60)
X[31:60, ] <- X[31:60, ] + 2
fmean_wrapper(X, M = 200)
#> ggcpt (changepoint detection result)
#>   Method:         fmean
#>   Change in:       mean 
#>   Changepoints found: 1 
#>   CP convention:   left 
#>   Penalty:         alpha = 0.05 
#>   Series length:   60 
#> 
#> Changepoints:
#> # A tibble: 1 × 3
#>      cp cp_value p_value
#>   <int>    <dbl>   <dbl>
#> 1    30    0.380       0
# }