hdreg_wrapper: High-dimensional regression changepoints

In ggchangepoint: Combines Changepoint Analysis with 'ggplot2'

High-dimensional regression changepoints

Description

Wraps changepoints::CV.search.DP.regression() (Rinaldo, Wang, Wen, Willett and Yu): dynamic programming with an \ell_0 penalty for changes in the coefficient vector of a high-dimensional sparse regression, with the two tuning parameters chosen by cross-validation. Where strucchange_wrapper() dates breaks in a low-dimensional regression by dynamic programming on the residual sum of squares, this handles the case where there are more covariates than the segments have observations to fit them with.

Usage

hdreg_wrapper(
  x,
  response = NULL,
  gamma_set = NULL,
  lambda_set = NULL,
  delta = NULL,
  ...
)

Arguments

x	A numeric matrix or data frame of covariates, rows as time points.
response	A numeric vector of responses, one per row of x. Required. Reachable through cpt_detect() as cpt_detect(X, method = "hdreg", response = y).
gamma_set	Candidate values of the \ell_0 tuning parameter. Defaults to a small grid scaled by the series length.
lambda_set	Candidate lasso penalties. Defaults to c(0.01, 0.1, 1).
delta	Minimum spacing. Defaults to max(5, floor(n / 20)).
...	Additional arguments passed to the engine.

Value

A ggcpt object with change_in = "regression". The plotted series is the response, which is what a reader of a regression-break plot expects to see.

References

\insertRef

rinaldo2021hdregggchangepoint

See Also

var_wrapper(), strucchange_wrapper().

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(), fpop_wrapper(), geomcp_wrapper(), hdcov_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)
p <- 10
n <- 80
X <- matrix(stats::rnorm(n * p), n, p)
beta1 <- c(rep(2, 3), rep(0, p - 3))
beta2 <- c(rep(0, p - 3), rep(2, 3))
y <- c(X[1:40, ] %*% beta1, X[41:n, ] %*% beta2) + stats::rnorm(n)
hdreg_wrapper(X, response = y, gamma_set = c(1, 10),
              lambda_set = c(0.1, 1))

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