• 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...

• ecp

• Referenced in 22 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...

• FDRSeg

• Referenced in 19 articles [sw16730]
• multiscale change-point segmentation. Fast multiple change-point segmentation methods, which additionally provide faithful statistical...

• breakfast

• Referenced in 11 articles [sw22395]
• package breakfast: Multiple Change-Point Detection and Segmentation. The breakfast package performs multiple change-point...

• factorcpt

• Referenced in 10 articles [sw18260]
• Simultaneous multiple change-point and factor analysis for high-dimensional time series. We propose ... dimensional time series factor models with multiple change-points in their second-order structure...

• wbsts

• Referenced in 7 articles [sw19367]
• Multiple change-point detection for non-stationary time series using wild binary segmentation. We propose...

• eNchange

• Referenced in 2 articles [sw33923]
• package eNchange: Ensemble Methods for Multiple Change-Point Detection. Implements a segmentation algorithm for multiple...

• IDetect

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

• gfpop

• Referenced in 3 articles [sw32351]
• Graph-Constrained Change-point Detection. In a world with data that change rapidly and abruptly ... important to detect those changes accurately. In this paper we describe an R package implementing ... penalised maximum likelihood inference of constrained multiple change-point models. This algorithm can be used...

• cBrother

• Referenced in 2 articles [sw35382]
• assumptions for Bayesian recombination detection. Bayesian multiple change-point models accurately detect recombination in molecular...

• VIFCP

• Referenced in 1 article [sw16253]
• support the paper ’A sequential multiple change-point detection procedure via VIF regression’ (Accepted...

• nmcdr

• Referenced in 1 article [sw20745]
• package nmcdr: Non-parametric Multiple Change-Points Detection...

• changepointsHD

• Referenced in 1 article [sw26719]
• methods include binary segmentation for multiple change-point estimation. For estimating each individual change-point...

• rbrothers

• Referenced in 1 article [sw30325]
• rbrothers: R package for Bayesian multiple change-point recombination detection. R package rbrothers provides easy...

• StepBrothers

• Referenced in 1 article [sw34333]
• evolutionarily related. Of these methods, Markov change-point models currently provide the most coherent framework ... recombination events and generalizes to incorporate multiple recombinant sequences. This generalization answers important questions with...

• Matlab

• Referenced in 13488 articles [sw00558]
• MATLAB® is a high-level language and interactive...

• R

• Referenced in 9832 articles [sw00771]
• R is a language and environment for statistical...

• S-PLUS

• Referenced in 615 articles [sw02892]
• S-PLUS is a powerful environment for statistical...

• UCI-ml

• Referenced in 3397 articles [sw04074]
• UC Irvine Machine Learning Repository. We currently maintain...

• Bioconductor

• Referenced in 320 articles [sw04205]
• Bioconductor provides tools for the analysis and comprehension...