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svpChange  

Smallest Valid Partitioning for Change-Point Detection
View on CRAN: Click here


Download and install svpChange package within the R console
Install from CRAN:
install.packages("svpChange")

Install from Github:
library("remotes")
install_github("cran/svpChange")

Install by package version:
library("remotes")
install_version("svpChange", "0.2.0")



Attach the package and use:
library("svpChange")
Maintained by
Vincent Runge
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-30
Latest Update: 2026-09-30
Description:
Provides methods for detecting multiple change-points and segmenting univariate time series using Smallest Valid Partitioning (SVP). SVP searches for a partition with the smallest number of segments whose segments satisfy a user-defined or built-in validity test. Among partitions with the same number of segments, it minimizes a within-segment sum-of-squared-errors criterion.
How to cite:
Vincent Runge (2026). svpChange: Smallest Valid Partitioning for Change-Point Detection. R package version 0.2.0, https://cran.r-project.org/web/packages/svpChange. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for svpChange
Functions, R codes and Examples using the svpChange R package
Full svpChange package functions and examples
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