Package: stepR 2.1-11

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.

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

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
stepR/json (API)

# Install 'stepR' in R:

install.packages('stepR', repos = c('https://florianpein.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

MRC.1000 - Values of the MRC statistic for 1,000 observations
MRC.asymptotic - "Asymptotic" values of the MRC statistic
MRC.asymptotic.dyadic - "Asymptotic" values of the MRC statistic

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp

4.12 score 1 stars 1 packages 74 scripts 664 downloads 3 mentions 45 exports 7 dependencies

Last updated from:8c27ef6ded. Checks:12 OK, 1 ERROR. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	271
linux-devel-x86_64	OK	270
source / vignettes	ERROR	3246
linux-release-arm64	OK	261
linux-release-x86_64	OK	287
macos-release-arm64	OK	262
macos-release-x86_64	OK	553
macos-oldrel-arm64	OK	273
macos-oldrel-x86_64	OK	365
windows-devel	OK	303
windows-release	OK	334
windows-oldrel	OK	299
wasm-release	OK	198

Exports:.testSmallScales BesselPolynomial bounds bounds.MRC chi chi.FFT compareBlocks computeBounds computeStat confband contMC critVal dfilter jsmurf jumpint kMRC.pvalue kMRC.quant kMRC.simul monteCarloSimulation MRC MRC.FFT MRC.pvalue MRC.quant MRC.simul MRCoeff MRCoeff.FFT neighbours sdrobnorm smuceR stepblock stepbound stepbound.default stepbound.stepcand stepcand stepfit stepFit steppath steppath.default steppath.stepcand stepsel stepsel.AIC stepsel.BIC stepsel.MRC thresh.smuceR transit

Dependencies:digest lowpassFilter R.cache R.methodsS3 R.oo R.utils Rcpp

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

R package stepR

Rendered fromStepR.Rnwusingknitr::knitr

Last update: 2026-03-24
Started: 2017-05-19

Help page	Topics
Multiscale Change-Point Inference	stepR-package stepR
Bessel Polynomials	BesselPolynomial
Bounds based on MRC	bounds bounds.MRC [.bounds
Compare fit blockwise with ground truth	compareBlocks
Computation of the bounds	computeBounds
Computation of the multiscale statistic	computeStat
Continuous time Markov chain	contMC
Critical values	critVal
Digital filters	dfilter print.dfilter
Family of distributions	family
Interval systems	intervalSystem intervalsystem
Reconstruct filtered piecewise constant functions with noise	jsmurf
Confidence intervals for jumps and confidence bands for step functions	confband confband.stepfit jumpint jumpint.stepfit lines.confband points.jumpint
Monte Carlo simulation	monteCarloSimulation
Compute Multiresolution Criterion	chi chi.FFT kMRC.pvalue kMRC.quant kMRC.simul MRC MRC.FFT MRC.pvalue MRC.quant MRC.simul MRCoeff MRCoeff.FFT
Values of the MRC statistic for 1,000 observations (all intervals)	MRC.1000
"Asymptotic" values of the MRC statistic (all intervals)	MRC.asymptotic
"Asymptotic" values of the MRC statistic (dyadic intervals)	MRC.asymptotic.dyadic
Neighbouring integers	neighbors neighbours
Parametric families	parametricFamily parametricfamily
Penalties	penalties penalty
Robust standard deviation estimate	sdrobnorm
Piecewise constant regression with SMUCE	smuceR thresh.smuceR
Step function	lines.stepblock plot.stepblock print.stepblock stepblock [.stepblock
Jump estimation under restrictions	stepbound stepbound.default stepbound.stepcand
Forward selection of candidate jumps	stepcand
Fitted step function	fitted.stepfit lines.stepfit logLik.stepfit plot.stepfit print.stepfit residuals.stepfit stepfit [.stepfit
Piecewise constant multiscale inference	stepFit
Solution path of step-functions	length.steppath logLik.steppath print.steppath steppath steppath.default steppath.stepcand [[.steppath
Automatic selection of number of jumps	stepsel stepsel.AIC stepsel.BIC stepsel.MRC
Test Small Scales	.testSmallScales testSmallScales
TRANSIT algorithm for detecting jumps	transit

Package: stepR 2.1-11

stepR: Multiscale Change-Point Inference

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