• wbs

  • Referenced in 63 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 57 articles [sw20106]
  • program performs extended analysis, forecasting and change-point detection for one-dimensional time series...
  • StFinMetrics

  • Referenced in 34 articles [sw29976]
  • asset returns; rolling analysis and change-point detection; modelling extreme values and risk measures...
  • FDRSeg

  • Referenced in 14 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 16 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 8 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 6 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 7 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...
  • 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...
  • npcp

  • Referenced in 6 articles [sw14395]
  • package npcp: Some Nonparametric Tests for Change-Point Detection in Possibly Multivariate Observations. Provides nonparametric...
  • AR1seg

  • Referenced in 5 articles [sw20393]
  • robust approach for estimating change-points in the mean of an AR(1) Gaussian process...
  • not

  • Referenced in 5 articles [sw16502]
  • detecting an unknown number of change-points occurring at unknown locations in one-dimensional data...
  • 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...
  • gfpop

  • Referenced in 2 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...
  • changepointsHD

  • Referenced in 1 article [sw26719]
  • package changepointsHD: Change-Point Estimation for Expensive and High-Dimensional Models. This implements the methods ... series of methods for estimating change-points given user specified black-box models. The methods ... include binary segmentation for multiple change-point estimation. For estimating each individual change-point ... allow for the efficient estimation of change-points in complicated models with high dimensional data...
  • ShapeChange

  • Referenced in 1 article [sw18167]
  • package ShapeChange. Change-Point Estimation using Shape-Restricted Splines. In a scatterplot where the response ... change-point, which is a mode, an inflection point or a jump point. The main ... estimates the mean curve and the change-point as well using shape-restricted B-splines ... bootstrap confidence interval for the change-point is incorporated in the main routine...
  • trend

  • Referenced in 1 article [sw31461]
  • trend: Non-Parametric Trend Tests and Change-Point Detection. The analysis of environmental data often ... requires the detection of trends and change-points. This package includes tests for trend detection ... Pearson and Spearman correlation trend test), change-point detection (Lanzante’s test procedures, Pettitt...