Package: msmbayes 0.2

msmbayes: Bayesian Multi-State Models for Intermittently-Observed Data

Bayesian multi-state models for intermittently-observed data. Markov and phase-type semi-Markov models, and misclassification hidden Markov models.

Authors:Christopher Jackson [aut, cre]

msmbayes_0.2.tar.gz
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msmbayes.pdf |msmbayes.html✨
msmbayes/json (API)
NEWS

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

Bug tracker:https://github.com/chjackson/msmbayes/issues

Datasets:
  • bigdat - A simulated multistate dataset with lots of observations and covariates
  • cav_misc - Example fitted model objects used for testing msmbayes
  • infsim - Simulated infection testing data
  • infsim2 - Simulated infection testing data
  • infsim_model - Example fitted model objects used for testing msmbayes
  • infsim_modelc - Example fitted model objects used for testing msmbayes
  • infsim_modelp - Example fitted model objects used for testing msmbayes
  • infsim_modelpc - Example fitted model objects used for testing msmbayes

On CRAN:

4.26 score 4 stars 3 scripts 20 exports 62 dependencies

Last updated 3 months agofrom:0537c44f28. Checks:1 OK, 10 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 16 2025
R-4.5-win-x86_64ERRORFeb 16 2025
R-4.5-mac-x86_64ERRORFeb 16 2025
R-4.5-mac-aarch64ERRORFeb 16 2025
R-4.5-linux-x86_64ERRORFeb 16 2025
R-4.4-win-x86_64ERRORFeb 16 2025
R-4.4-mac-x86_64ERRORFeb 16 2025
R-4.4-mac-aarch64ERRORFeb 16 2025
R-4.3-win-x86_64ERRORFeb 16 2025
R-4.3-mac-x86_64ERRORFeb 16 2025
R-4.3-mac-aarch64ERRORFeb 16 2025

Exports:dnphaseedfhnphasehrloghrmean_sojournmsmbayesmsmhistmsmhist_bardatamsmpriorpmatrixpmatrixdfpnphaseqdfqmatrixrnphasesoj_probstandardise_tostandardize_tototlos

Dependencies:abindarrayhelpersbackportscallrcheckmateclicmdstanrcodacolorspacecpp11data.tabledistributionaldplyrexpmfansifarverfsgenericsggdistggplot2gluegtablehardhatinstantiateisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgconfigposteriorprocessxpspurrrquadprogR6RColorBrewerRcpprlangscalessparsevctrsstringistringrsvUnittensorAtibbletidybayestidyrtidyselectutf8vctrsviridisLitewithr

Advanced multi-state models in msmbayes

Christopher Jackson [email protected]

Rendered fromadvanced.Rmdusingknitr::rmarkdownon Feb 16 2025.

Last update: 2024-04-09
Started: 2024-03-28

Readme and manuals

Help Manual

Help pageTopics
The 'msmbayes' package for Bayesian multi-state modelling of intermittently-observed datamsmbayes-package
A simulated multistate dataset with lots of observations and covariatesbigdat
Misclassification probabilities from an msmbayes modeledf
Example fitted model objects used for testing msmbayescav_misc example_models infsim_model infsim_modelc infsim_modelp infsim_modelpc
Hazard ratios for covariates on transition intensitieshr
Simulated infection testing data"test (i.e. -1 0). 1 1-2 10 180 2 2-1 50 a age and are Baseline covariates, data, days defined female, For for hazard In in infsim infsim2 intensities is log male mean model negative negative" of on positive" positive. ratios simulation sojourn state state. The the time transition transition, transition. used using with `age10=` `age10`
Log hazard ratios for covariates on transition intensitiesloghr
Mean sojourn times from an msmbayes modelmean_sojourn
Bayesian multi-state models for intermittently-observed datamsmbayes
Illustrate the empirical distribution of states against time in intermittently-observed multistate datamsmhist
Estimate state occupation probabilities to be illustrated by a bar plot in 'msmhist'msmhist_bardata
Constructor for a prior distribution in msmbayesmsmprior
Density, probability distribution, hazard and random number generation functions for the Coxian phase-type distribution with any number of phases.dnphase hnphase nphase pnphase rnphase
Transition probability matrix from an msmbayes modelpmatrix
Transition probabilities from an msmbayes model, presented as a tidy data framepmatrixdf
Transition intensities from an msmbayes model, presented as a tidy data frameqdf
Transition intensity matrix from an msmbayes modelqmatrix
Sojourn probability in a state of a msmbayes modelsoj_prob
Constructor for a standardising population used for model outputsstandardise_to standardize_to
Summarise basic parameter estimates from an msmbayes modelsummary.msmbayes
Total length of stay in each state over an intervaltotlos