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IDetect

swMATH ID: 28005
Software Authors: Andreas Anastasiou, Piotr Fryzlewicz
Description: R package IDetect: Isolate-Detect Methodology for Multiple Change-Point Detection. Provides efficient implementation of the Isolate-Detect methodology for the consistent estimation of the number and location of multiple change-points in one-dimensional data sequences from the ”deterministic + noise” model. For details on the Isolate-Detect methodology, please see Anastasiou and Fryzlewicz (2018) <https://docs.wixstatic.com/ugd/24cdcc_6a0866c574654163b8255e272bc0001b.pdf>. Currently implemented scenarios are: piecewise-constant signal with Gaussian noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise.
Homepage: https://cran.r-project.org/web/packages/IDetect/index.html
Source Code: https://github.com/cran/IDetect
Dependencies: R
Keywords: arXiv_stat.ME; Segmentation; symmetric interval expansion; threshold criterion; Schwarz information criterion; R; R package
Related Software: breakfast; FDRSeg; wbs; cpm; not; cumSeg; Segmentor3IsBack; changepoint; R; freeknotsplines; earth; changepoint.np; CRAN; jointseg; fpop; mosum; basta; capushe; ecp; stepR
Cited in: 2 Publications

Standard Articles

2 Publications describing the Software, including 1 Publication in zbMATH Year
Detecting multiple generalized change-points by isolating single ones. Zbl 07472633
Anastasiou, Andreas; Fryzlewicz, Piotr
2022
Detecting multiple generalized change-points by isolating single ones
Andreas Anastasiou, Piotr Fryzlewicz
2019

Cited in 1 Field

2 Statistics (62-XX)

Citations by Year