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 07472633Anastasiou, Andreas; Fryzlewicz, Piotr 2022 Detecting multiple generalized change-points by isolating single ones Andreas Anastasiou, Piotr Fryzlewicz 2019 Cited by 2 Authors 2 Fryzlewicz, Piotr 1 Anastasiou, Andreas Cited in 2 Serials 1 Metrika 1 Journal of the Korean Statistical Society Cited in 1 Field 2 Statistics (62-XX) Citations by Year