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robcp  

Robust Change-Point Tests
View on CRAN: Click here


Download and install robcp package within the R console
Install from CRAN:
install.packages("robcp")

Install from Github:
library("remotes")
install_github("cran/robcp")

Install by package version:
library("remotes")
install_version("robcp", "0.3.7")



Attach the package and use:
library("robcp")
Maintained by
Sheila Goerz
[Scholar Profile | Author Map]
First Published: 2019-06-04
Latest Update: 2022-09-16
Description:
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) , and 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) and Dehling, Fried and Wendler (2020) . Furthermore, the packages provides tests on changes in the scale or the correlation as proposed in Gerstenberger, Vogel and Wendler (2020) , Dehling et al. (2017) , and Wied et al. (2014) .
How to cite:
Sheila Goerz (2019). robcp: Robust Change-Point Tests. R package version 0.3.7, https://cran.r-project.org/web/packages/robcp. Accessed 13 Apr. 2025.
Previous versions and publish date:
0.2.4 (2019-06-04 01:50), 0.2.5 (2020-01-24 16:00), 0.3.0 (2021-03-31 02:20), 0.3.1 (2021-09-12 01:50), 0.3.2 (2021-09-20 16:00), 0.3.3 (2021-10-30 00:50), 0.3.4 (2022-03-23 14:20), 0.3.5 (2022-03-30 13:00), 0.3.6 (2022-05-03 15:20), 0.3.7 (2022-09-16 15:36)
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