Multiple Change-Point Detection and Segmentation
person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = c("aut", "cre"))
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
segment.mean.

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
segment.mean.

breakfast: Computationally Efficient Multiple Change-Point
Detection and Estimation with a Broad Range of Methods
c(
person("Andreas", "Anastasiou", email = "anastasiou.andreas@ucy.ac.cy", role = "aut"),
person("Yining", "Chen", email = "y.chen101@lse.ac.uk", role = c("aut", "cre")),
person("Haeran", "Cho", email = "haeran.cho@bristol.ac.uk", role = "aut"),
person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = "aut"))
The breakfast package contains a collection of change-point detection and estimation methods, together with model selection and ensemble devices and visualisation tools.
Andreas Anastasiou [aut],
Yining Chen [aut, cre],
Haeran Cho [aut],
Piotr Fryzlewicz [aut]

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

An R Package for Multiple Break-Point Detection via the
Cross-Entropy Method
Priyadarshana W.J.R.M. and Georgy Sofronov
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)).