Packaged: 2022-11-21 18:52:52 UTC; sarahteichman

Title: Multiple Change-Point Detection and Segmentation
Authors@R: person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = c("aut", "cre"))
Description: Performs multiple change-point detection in data sequences, or data sequence
segmentation, using computationally efficient multiscale methods. This version only
implements the "Tail-Greedy Unbalanced Haar" change-point detection methodology; more
methods will be added in future versions. To start with, see the function

Description: The breakfast package performs multiple change-point detection in data
sequences, or sequence segmentation, using computationally efficient multiscale
methods. This version of the package implements the "Tail-Greedy Unbalanced Haar",
"Wild Binary Segmentation" and "Adaptive Wild Binary Segmentation" change-point
detection and segmentation methodologies. To start with, see the function

Title: breakfast: Computationally Efficient Multiple Change-Point
Detection and Estimation with a Broad Range of Methods
person("Andreas", "Anastasiou", email = "anastasiou.andreas@ucy.ac.cy", role = "aut"),
person("Haeran", "Cho", email = "haeran.cho@bristol.ac.uk", role = "aut"),
Description: The breakfast package contains a collection of change-point detection and estimation methods, together with model selection and ensemble devices and visualisation tools.

Title: Methods for Fast Multiple Change-Point Detection and Estimation
Description: A developing software suite for multiple change-point detection/estimation (data segmentation) in data sequences.

Title: An R Package for Multiple Break-Point Detection via the
Author: Priyadarshana W.J.R.M. and Georgy Sofronov
Description: Implements the cross-entropy (CE) method, which is a model based stochastic optimization technique to estimate both the number as well as the corresponding locations of break-points in biological sequences of continuous measurements (Priyadarshana and Sofronov (2014)).

Title: Multiple Break-Point Detection via the Cross-Entropy Method
Description: Implements the cross-entropy (CE) method, which is a model based stochastic optimization technique to estimate both the number and their corresponding locations of break-points in biological sequences of continuous and discrete measurements as described in Priyadarshana and Sofronov (2014, 2012a, 2012b).
Imports: ggplot2, MASS, msm, foreach, doParallel, parallel