CptNonPar-package: CptNonPar: Nonparametric Change Point Detection for...

In CptNonPar: Nonparametric Change Point Detection for Multivariate Time Series

CptNonPar: Nonparametric Change Point Detection for Multivariate Time Series

Description

Implements the nonparametric moving sum procedure for detecting changes in the joint characteristic function (NP-MOJO) for multiple change point detection in multivariate time series. See McGonigle, E. T., Cho, H. (2025) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/biomet/asaf024")} for description of the NP-MOJO methodology.

Author(s)

Maintainer: Euan T. McGonigle [e-mail]

Authors:

• Haeran Cho [e-mail]

See Also

np.mojo, np.mojo.multilag, multilag.cpts.merge

Examples

set.seed(1)
n <- 500
noise <- c(rep(1, 300), rep(0.4, 200)) * stats::arima.sim(model = list(ar = 0.3), n = n)
signal <- c(rep(0, 100), rep(2, 400))
x <- signal + noise
x.c <- np.mojo.multilag(x, G = 83, lags = c(0, 1))
x.c$cpts
x.c$cpt.clusters

CptNonPar documentation built on April 16, 2025, 5:11 p.m.