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tidychangepoint:A Tidy Framework for Changepoint Detection Analysis
Changepoint detection algorithms for R are widespread but have different interfaces and reporting conventions. This makes the comparative analysis of results difficult. We solve this problem by providing a tidy, unified interface for several different changepoint detection algorithms. We also provide consistent numerical and graphical reporting leveraging the 'broom' and 'ggplot2' packages.
Maintained by Benjamin S. Baumer. Last updated 2 months ago.
2 stars 5.30 score 8 scripts
cran
wbs:Wild Binary Segmentation for Multiple Change-Point Detection
Provides efficient implementation of the Wild Binary Segmentation and Binary Segmentation algorithms for estimation of the number and locations of multiple change-points in the piecewise constant function plus Gaussian noise model.
Maintained by Rafal Baranowski. Last updated 5 months ago.
3 stars 2.26 score 2 dependentscran
cpop:Detection of Multiple Changes in Slope in Univariate Time-Series
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>.
Maintained by Daniel Grose. Last updated 10 months ago.
1.00 score