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stepR: Multiscale Change-Point Inference
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.
Getting started
Browse package contents
Package details |
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| Author | Pein Florian [aut, cre], Thomas Hotz [aut], Hannes Sieling [aut], Timo Aspelmeier [ctb] |
| Maintainer | Pein Florian <f.pein@lancaster.ac.uk> |
| License | GPL-3 |
| Version | 2.1-9 |
| Package repository | View on CRAN |
| Installation |
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