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 (K. Frick, A. Munk and H. Sieling, 2014) and HSMUCE (F. Pein, H. Sieling and A. Munk, 2017) . In addition, confidence intervals for the change-point locations and bands for the unknown signal can be obtained.


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install.packages("stepR")

2.0-2 by Pein Florian, 18 days ago


Browse source code at https://github.com/cran/stepR


Authors: Pein Florian [aut, cre], Thomas Hotz [aut], Hannes Sieling [aut], Timo Aspelmeier [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, R.cache, digest, stats, graphics, methods

Suggests testthat, knitr

Linking to Rcpp


Imported by FDRSeg, clampSeg, linearQ.


See at CRAN