Package: msmbayes 0.3

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_0.3.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
msmbayes/json (API)

# 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

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

bigdat - A simulated multistate dataset with lots of observations and covariates
illdeath_data - A simulated dataset from an illness-death model
infsim - 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
infsim2 - Simulated infection testing data

On CRAN:

cpp

5.17 score 7 stars 6 scripts 48 exports 64 dependencies

Last updated from:80e2bd7f52. Checks:3 WARNING, 9 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	482
linux-devel-x86_64	WARNING	489
source / vignettes	OK	675
linux-release-arm64	OK	469
linux-release-x86_64	OK	494
macos-release-arm64	OK	288
macos-release-x86_64	OK	1017
macos-oldrel-arm64	OK	373
macos-oldrel-x86_64	OK	1315
windows-devel	WARNING	424
windows-release	OK	556
windows-oldrel	OK	566
wasm-release	FAIL	164

Exports:canpars_to_rates dnphase edf ematrix gamma_shape_in_bounds hnphase hr loghr loglik logoddsnext logrrnext logtaf mean_nphase mean_sojourn msmbayes msmbayes_prior_sample msmbayes_priorpred_sample msmhist msmhist_bardata msmprior n3_moment_bounds ncmoment_nphase nphase_Q phaseapprox_pars pmatrix pmatrixdf pnext pnphase qdf qmatrix qnphase qphaseapprox rates_to_canpars rnphase rrnext shape_ubound shapescale_to_rates sim_2state_smm skewness_nphase soj_prob soj_quantile standardise_to standardize_to statetable taf totlos var_nphase weibull_shape_in_bounds

Dependencies:abind arrayhelpers backports BH callr checkmate cli coda cpp11 desc distributional dplyr expm farver generics ggdist ggplot2 glue gridExtra gtable hardhat inline isoband labeling lattice lifecycle loo magrittr Matrix matrixStats numDeriv pillar pkgbuild pkgconfig posterior processx ps purrr quadprog QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan rstantools S7 scales sparsevctrs StanHeaders stringi stringr svUnit tensorA tibble tidybayes tidyr tidyselect utf8 vctrs viridisLite withr

Semi-Markov models with msmbayes

Rendered fromsemimarkov.Rmdusingknitr::rmarkdown

Last update: 2025-07-22
Started: 2024-12-19

Advanced phase-type models in msmbayes

Phase-type semi-Markov models | Fitting phase-type models in msmbayes | Example: data simulated from a standard Markov model | Example: data simulated from a phase-type model

Rendered fromnphase.Rmdusingknitr::rmarkdown

Last update: 2025-07-09
Started: 2024-12-20

Misclassification multi-state models in msmbayes

Multi-state models with misclassification | Specifiying prior distributions for misclassification probabilities | Fixed misclassification probabilities

Rendered frommisclass.Rmdusingknitr::rmarkdown

Last update: 2024-12-20
Started: 2024-12-20

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The 'msmbayes' package for Bayesian multi-state modelling of intermittently-observed data	msmbayes-package
A simulated multistate dataset with lots of observations and covariates	bigdat
Convert between canonical parameters and rates for a phase-type distribution	canpars_to_rates rates_to_canpars
Misclassification error probabilities from an msmbayes model	edf
Matrix of misclassification error probabilities from an msmbayes model	ematrix
Example fitted model objects used for testing msmbayes	example_models infsim_model infsim_modelc infsim_modelp infsim_modelpc
A simulated dataset from an illness-death model	illdeath_data
Simulated infection testing data	infsim infsim2
(Log) hazard ratios for covariates on transition intensities	hr loghr
Log likelihood from an msmbayes model	loglik logLik.msmbayes
Summarise posteriors for log odds of transitions from phase-type states	logoddsnext
(Log) time acceleration factors in semi-Markov models	logtaf taf
Mean sojourn times from an msmbayes model	mean_sojourn
Bayesian multi-state models for intermittently-observed data	msmbayes
Generate a sample from the prior distribution in a msmbayes model	msmbayes_prior_sample
Generate a dataset from the prior predictive distribution in a msmbayes model	msmbayes_priorpred_sample
Illustrate the empirical distribution of states against time in intermittently-observed multistate data	msmhist
Estimate state occupation probabilities to be illustrated by a bar plot in 'msmhist'	msmhist_bardata
Constructor for a prior distribution in msmbayes	msmprior
Bounds on normalised moments for phase-type approximations	n3_moment_bounds
Density, probability distribution, quantile, moment, hazard and random number generation functions for the Coxian phase-type distribution with any number of phases.	dnphase hnphase mean_nphase ncmoment_nphase nphase pnphase qnphase rnphase skewness_nphase var_nphase
Given a phase-type sojourn distribution, return the corresponding Markov intensity matrix where the last state is the absorbing state, and the the time to absorption is the sojourn distribution.	nphase_Q
Summarise posteriors for shape and scale parameters for the sojourn distribution in a semi-Markov msmbayes model	phaseapprox_pars
Transition probability matrix from an msmbayes model	pmatrix
Transition probabilities from an msmbayes model, presented as a tidy data frame	pmatrixdf
Probabilities for the next state in a multi-state model	pnext
Transition intensities from an msmbayes model, presented as a tidy data frame	qdf
Transition intensity matrix from an msmbayes model	qmatrix
Phase-type expansion of a transition intensity matrix to create a non-Markov multi-state model	qphaseapprox
Effects of covariates on competing exit transitions in phase type models	logrrnext rrnext rrnextdoc
Test whether a shape parameter of is in the bounds required for a valid phase-type approximation	gamma_shape_in_bounds shape_in_bounds weibull_shape_in_bounds
Upper bound for shape parameter in moment-based phase-type approximations	shape_ubound
Determine parameters of a phase-type model that approximate a parametric shape-scale distribution	shapescale_to_rates
Simulate intermittently-observed data from a semi-Markov multi-state model with two states and reversible transitions.	sim_2state_smm
Sojourn probability in a state of a msmbayes model	soj_prob
Quantiles of the sojourn distribution in a state of a msmbayes model	soj_quantile
Constructor for a standardising population used for model outputs	standardise_to standardize_to
Summarise intermittenly-observed multi-state data	statetable
Summarise basic parameter estimates from an msmbayes model	summary.msmbayes
Total length of stay in each state over an interval	totlos