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stepR  

Multiscale Change-Point Inference
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("stepR", "2.1-10")



Attach the package and use:
library("stepR")
Maintained by
Pein Florian
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-03-04
Latest Update: 2023-08-18
Description:
Allows fitting of step-functions to univariate serial data where neither the number of jumps nor their positions is known by implementing the multiscale regression estimators SMUCE, simulataneous multiscale changepoint estimator, (K. Frick, A. Munk and H. Sieling, 2014) <doi:10.1111/rssb.12047> and HSMUCE, heterogeneous SMUCE, (F. Pein, H. Sieling and A. Munk, 2017) <doi:10.1111/rssb.12202>. In addition, confidence intervals for the change-point locations and bands for the unknown signal can be obtained.
How to cite:
Pein Florian (2015). stepR: Multiscale Change-Point Inference. R package version 2.1-10, https://cran.r-project.org/web/packages/stepR. Accessed 07 Nov. 2024.
Previous versions and publish date:
1.0-1 (2015-03-04 12:58), 1.0-2 (2015-04-29 14:57), 1.0-3 (2015-06-18 13:35), 1.0-4 (2016-03-24 23:58), 1.0-5.1 (2016-10-11 20:52), 1.0-5 (2016-10-05 16:36), 1.0-6 (2016-10-17 19:00), 1.0-7 (2017-04-20 17:03), 1.0 (2015-02-16 19:28), 2.0-1 (2017-05-19 23:22), 2.0-2 (2018-04-06 18:26), 2.0-3 (2019-01-27 19:30), 2.0-4 (2019-11-03 22:10), 2.1-0 (2020-08-04 20:40), 2.1-1 (2020-08-26 18:10), 2.1-3 (2022-05-06 01:50), 2.1-4 (2023-01-30 16:30), 2.1-8 (2023-08-18 10:50), 2.1-9 (2023-11-13 22:00)
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