Package: changepoint 2.2.5
changepoint: Methods for Changepoint Detection
Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() functions should be your first point of call.
Authors:
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changepoint.pdf |changepoint.html✨
changepoint/json (API)
NEWS
# Install 'changepoint' in R: |
install.packages('changepoint', repos = c('https://rkillick.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rkillick/changepoint/issues
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Last updated 2 years agofrom:5253a05c63. Checks:OK: 4 NOTE: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 01 2024 |
R-4.5-win-x86_64 | NOTE | Sep 01 2024 |
R-4.5-linux-x86_64 | NOTE | Sep 01 2024 |
R-4.4-win-x86_64 | NOTE | Sep 01 2024 |
R-4.4-mac-x86_64 | NOTE | Sep 01 2024 |
R-4.4-mac-aarch64 | NOTE | Sep 01 2024 |
R-4.3-win-x86_64 | OK | Sep 01 2024 |
R-4.3-mac-x86_64 | OK | Sep 01 2024 |
R-4.3-mac-aarch64 | OK | Sep 01 2024 |
Exports:BINSEGclass_inputcoefcpt.meancpt.meanvarcpt.varcptscpts.fullcpts.full<-cpts.tscpts<-cpttypecpttype<-data.setdata.set.tsdata.set<-decisiondistributiondistribution<-likelihoodlogLikmethodmethod<-minseglenminseglen<-ncptsncpts.maxncpts.max<-nsegparamparam.estparam.est<-PELTpen.typepen.type<-pen.valuepen.value.fullpen.value.full<-pen.value<-penalty_decisionplotseg.lenshowsummarytest.stattest.stat<-