Package: stepR
Title: Multiscale Change-Point Inference
Version: 2.1-11
Authors@R: c(person("Pein", "Florian", role = c("aut", "cre"), email = "f.pein@lancaster.ac.uk"),
    person("Thomas", "Hotz", role = "aut", email = "thomas.hotz@tu-ilmenau.de"),
    person("Hannes", "Sieling", role = "aut", email = "hsielin@uni-goettingen.de"),
    person("Timo", "Aspelmeier", role = "ctb", email = "timo.aspelmeier@mathematik.uni-goettingen.de"))
Depends: R (>= 3.3.0)
Imports: Rcpp (>= 0.12.3), lowpassFilter (>= 1.0.0), R.cache (>=
        0.10.0), digest (>= 0.6.10), stats, graphics, methods
LinkingTo: Rcpp
Suggests: testthat (>= 1.0.0), knitr
VignetteBuilder: knitr
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.
License: GPL-3
Classification/MSC: 62G08, 92C40, 92D20
LazyData: yes
NeedsCompilation: yes
Packaged: 2026-06-24 09:31:22 UTC; root
Author: Pein Florian [aut, cre], Thomas Hotz [aut], Hannes Sieling
        [aut], Timo Aspelmeier [ctb]
Maintainer: Pein Florian <f.pein@lancaster.ac.uk>
Repository: https://florianpein.r-universe.dev
Date/Publication: 2026-03-24 06:10:18 UTC
RemoteUrl: https://github.com/cran/stepR
RemoteRef: HEAD
RemoteSha: 8c27ef6dedbc9fe09e52ca1bb9fa690c9754061f