• wbs

• Referenced in 92 articles [sw11110]
• Wild binary segmentation for multiple change-point detection. We propose a new technique, called wild ... number and locations of multiple change-points in data. We assume that the number ... change-points can increase to infinity with the sample size. Due to a certain random ... very short spacings between the change-points and/or very small jump magnitudes, unlike standard binary...

• CaterpillarSSA

• Referenced in 60 articles [sw20106]
• program performs extended analysis, forecasting and change-point detection for one-dimensional time series...

• StFinMetrics

• Referenced in 38 articles [sw29976]
• asset returns; rolling analysis and change-point detection; modelling extreme values and risk measures...

• FDRSeg

• Referenced in 19 articles [sw16730]
• control in multiscale change-point segmentation. Fast multiple change-point segmentation methods, which additionally provide ... Moreover, we show that FDRSeg estimates change-point locations, as well as the signal ... bounded, or even increasing, number of change-points. FDRSeg can be efficiently computed ... observations when there are many change-points. The performance of the proposed method is examined...

• ecp

• Referenced in 19 articles [sw21075]
• package ecp: Non-Parametric Multiple Change-Point Analysis of Multivariate Data. Implements various procedures ... finding multiple change-points. Two methods make use of dynamic programming and probabilistic pruning, with...

• factorcpt

• Referenced in 10 articles [sw18260]
• Simultaneous multiple change-point and factor analysis for high-dimensional time series. We propose ... time series factor models with multiple change-points in their second-order structure. We operate ... estimate the number and locations of change-points consistently as well as identifying whether they ... wavelets, we transform the problem of change-point detection in the second-order structure...

• breakfast

• Referenced in 11 articles [sw22395]
• package breakfast: Multiple Change-Point Detection and Segmentation. The breakfast package performs multiple change-point ... Segmentation” and ”Adaptive Wild Binary Segmentation” change-point detection and segmentation methodologies. To start with...

• stepR

• Referenced in 10 articles [sw20772]
• package stepR: Multiscale Change-Point Inference. Allows fitting of step-functions to univariate serial data ... addition, confidence intervals for the change-point locations and bands for the unknown signal...

• NHPP

• Referenced in 6 articles [sw03163]
• testing strategy, or resource allocation. The change-point and other parameters are often unknown ... applied in the case that the change-point is not necessarily the observation time point ... nonparametric method for estimating the change-point...

• npcp

• Referenced in 9 articles [sw14395]
• package npcp: Some Nonparametric Tests for Change-Point Detection in Possibly Multivariate Observations. Provides nonparametric...

• seqCBS

• Referenced in 6 articles [sw12152]
• homogeneous Poisson Processes with change point models. It uses an adaptation of Circular Binary Segmentation ... model selection method for the change-point model. A case and a control sample reads...

• FreSpeD

• Referenced in 6 articles [sw21049]
• FreSpeD: Frequency-specific change-point detection in epileptic seizure multi-channel EEG data...

• wbsts

• Referenced in 3 articles [sw19367]
• Multiple change-point detection for non-stationary time series using wild binary segmentation. We propose ... number and locations of the change-points in the second-order structure of a time ... cases where the spacings between change-points are short. In addition, we do not restrict ... total number of change-points a time series can have. We also ameliorate the performance...

• AR1seg

• Referenced in 6 articles [sw20393]
• robust approach for estimating change-points in the mean of an AR(1) Gaussian process...

• not

• Referenced in 6 articles [sw16502]
• detecting an unknown number of change-points occurring at unknown locations in one-dimensional data...

• gfpop

• Referenced in 3 articles [sw32351]
• Package for Univariate Graph-Constrained Change-point Detection. In a world with data that change ... abruptly, it is important to detect those changes accurately. In this paper we describe ... maximum likelihood inference of constrained multiple change-point models. This algorithm can be used...

• eNchange

• Referenced in 2 articles [sw33923]
• package eNchange: Ensemble Methods for Multiple Change-Point Detection. Implements a segmentation algorithm for multiple ... change-point detection in univariate time series using the Ensemble Binary Segmentation of Korkas...

• IDetect

• Referenced in 2 articles [sw28005]
• IDetect: Isolate-Detect Methodology for Multiple Change-Point Detection. Provides efficient implementation of the Isolate ... number and location of multiple change-points in one-dimensional data sequences from the ”deterministic...

• SeqBBS

• Referenced in 2 articles [sw17972]
• SeqBBS: a change-point model based algorithm and R package for searching CNV regions ... regions. We illustrate that a change-point (or a breakpoint) detection method, along with...

• PeakSegDisk

• Referenced in 3 articles [sw41661]
• package PeakSegDisk: Disk-Based Constrained Change-Point Detection. Disk-based implementation of Functional Pruning Optimal...