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robcp

R package robcp

Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. Focus is on the detection of abrupt changes in location, but changes scale or dependence structure can be detected as well. This package provides tests for change detection in uni- and multivariate time series based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) arXiv:1905.06201. Furthermore, robcp provides tests for change detection in univariate time series based on 2-sample U-statistics or 2-sample U-quantiles as proposed by Dehling et al. (2015) DOI:10.1007/978-1-4939-3076-0_12 and Dehling, Fried and Wendler (2020) DOI:10.1093/biomet/asaa004.

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Install

install.packages('robcp')

Monthly Downloads

205

Version

0.3.9

License

GPL-3

Maintainer

Sheila Goerz

Last Published

June 25th, 2025

Functions in robcp (0.3.9)

pKSdist

Asymptotic cumulative distribution for the CUSUM Test statistic
psi_cumsum

Cumulative sum of transformed vectors
psi

Transformation of time series
weightedMedian

Weighted Median
scale_cusum

Tests for Scale Changes Based on Pairwise Differences
wmw_test

Wilocxon-Mann-Whitney Test for Change Points
print.cpStat

Print method for change point statistics
wilcox_stat

Wilcoxon-Mann-Whitney Test Statistic for Change Points
zeros

Zero of the Bessel function of first kind
cor_stat

Test statistic to detect Correlation Changes
cor_cusum

A CUSUM-type test to detect changes in the correlation.
hl_test

Hodges-Lehmann Test for Change Points
kthPair

K-th largest element in a sum of sets.
medianDiff

Median of the set X - Y
lrv

Long Run Variance
CUSUM

CUSUM Test Statistic
Qalpha

\(Q^{\alpha}\)
HodgesLehmann

Hodges Lehmann Test Statistic
huber_cusum

Huberized CUSUM test
plot.cpStat

Plot method for change point statistics
scale_stat

Test statistic to detect Scale Changes
robcp-package

robcp: Robust Change-Point Tests
modifChol

Revised Modified Cholesky Factorization