Package: mcp 0.3.4
mcp: Regression with Multiple Change Points
Flexible and informed regression with Multiple Change Points. 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' is described in Lindeløv (submitted) <doi:10.31219/osf.io/fzqxv> and generalizes the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.
Authors:
mcp_0.3.4.tar.gz
mcp_0.3.4.tar.gz(r-4.5-noble)mcp_0.3.4.tar.gz(r-4.4-noble)
mcp_0.3.4.tgz(r-4.4-emscripten)mcp_0.3.4.tgz(r-4.3-emscripten)
mcp.pdf |mcp.html✨
mcp/json (API)
NEWS
# Install 'mcp' in R: |
install.packages('mcp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lindeloev/mcp/issues
Pkgdown:https://lindeloev.github.io
- demo_fit - Example 'mcpfit' for examples
Last updated 9 months agofrom:ee4040b642. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 13 2024 |
R-4.5-linux | OK | Nov 13 2024 |
Exports:bernoullicriterionexponentialfixefget_segment_tablehypothesisilogitis.mcpfitlogitloomcpmcp_examplenegbinomialphiplot_parspp_checkprobitranefsd_to_precwaic
Dependencies:abindarrayhelpersbackportsbayesplotcheckmateclicodacodetoolscolorspacecpp11digestdistributionaldplyrfansifarverfuturefuture.applygenericsggdistggplot2ggridgesglobalsgluegtableisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivparallellypatchworkpillarpkgconfigplyrposteriorpurrrquadprogR6RColorBrewerRcppreshape2rjagsrlangscalesstringistringrsvUnittensorAtibbletidybayestidyrtidyselectutf8vctrsviridisLitewithr