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:Jonas Kristoffer Lindeløv [aut, cre]

mcp_0.3.4.tar.gz
mcp_0.3.4.zip(r-4.7-any)mcp_0.3.4.zip(r-4.6-any)mcp_0.3.4.zip(r-4.5-any)
mcp_0.3.4.tgz(r-4.6-any)mcp_0.3.4.tgz(r-4.5-any)
mcp_0.3.4.tar.gz(r-4.7-any)mcp_0.3.4.tar.gz(r-4.6-any)
mcp_0.3.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mcp/json (API)

# Install 'mcp' in R:
install.packages('mcp', repos = c('https://lindeloev.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lindeloev/mcp/issues

Pkgdown/docs site:https://lindeloev.github.io

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • demo_fit - Example 'mcpfit' for examples

On CRAN:

Conda:

jagscpp

6.93 score 119 stars 1 packages 120 scripts 743 downloads 4 mentions 20 exports 59 dependencies

Last updated from:e5b1370879. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK259
source / vignettesOK255
linux-releaseOK186
macos-releaseOK183
macos-oldrelOK277
windows-develOK156
windows-releaseOK134
windows-oldrelOK166
wasm-releaseOK147

Exports:bernoullicriterionexponentialfixefget_segment_tablehypothesisilogitis.mcpfitlogitloomcpmcp_examplenegbinomialphiplot_parspp_checkprobitranefsd_to_precwaic

Dependencies:abindarrayhelpersbackportsbayesplotcheckmateclicodacodetoolscpp11digestdistributionaldplyrfarverfuturefuture.applygenericsggdistggplot2ggridgesglobalsgluegtableisobandlabelinglatticelifecyclelistenvloomagrittrmatrixStatsnumDerivparallellypatchworkpillarpkgconfigplyrposteriorpurrrquadprogR6RColorBrewerRcppreshape2rjagsrlangS7scalesstringistringrsvUnittensorAtibbletidybayestidyrtidyselectutf8vctrsviridisLitewithr