doi:10.1080/10618600.2018.1512868>. This method finds the best continuous piecewise linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalizes complexity based on an L0 penalty on changes in slope. Further information regarding the use of this package with detailed examples can be found in Fearnhead and Grose (2024) <doi:10.18637/jss.v109.i07>.">

cpop: Detection of Multiple Changes in Slope in Univariate Time-Series (original) (raw)

Detects multiple changes in slope using the CPOP dynamic programming approach of Fearnhead, Maidstone, and Letchford (2019) <doi:10.1080/10618600.2018.1512868>. This method finds the best continuous piecewise linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalizes complexity based on an L0 penalty on changes in slope. Further information regarding the use of this package with detailed examples can be found in Fearnhead and Grose (2024) <doi:10.18637/jss.v109.i07>.

Version: 1.0.8
Depends: R (≥ 4.1.0), crops, pacman
Imports: Rdpack, Rcpp (≥ 0.12.13), ggplot2, mathjaxr, pracma, methods
LinkingTo: Rcpp
Suggests: testthat
Published: 2025-06-11
DOI: 10.32614/CRAN.package.cpop
Author: Daniel Grose [aut, cre], Paul Fearnhead [aut]
Maintainer: Daniel Grose <dan.grose at lancaster.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: cpop citation info
Materials: NEWS
CRAN checks: cpop results

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