Package: MCMCprecision 0.4.0
Daniel W. Heck
MCMCprecision: Precision of Discrete Parameters in Transdimensional MCMC
Estimates the precision of transdimensional Markov chain Monte Carlo (MCMC) output, which is often used for Bayesian analysis of models with different dimensionality (e.g., model selection). Transdimensional MCMC (e.g., reversible jump MCMC) relies on sampling a discrete model-indicator variable to estimate the posterior model probabilities. If only few switches occur between the models, precision may be low and assessment based on the assumption of independent samples misleading. Based on the observed transition matrix of the indicator variable, the method of Heck, Overstall, Gronau, & Wagenmakers (2019, Statistics & Computing, 29, 631-643) <doi:10.1007/s11222-018-9828-0> draws posterior samples of the stationary distribution to (a) assess the uncertainty in the estimated posterior model probabilities and (b) estimate the effective sample size of the MCMC output.
Authors:
MCMCprecision_0.4.0.tar.gz
MCMCprecision_0.4.0.tar.gz(r-4.5-noble)MCMCprecision_0.4.0.tar.gz(r-4.4-noble)
MCMCprecision_0.4.0.tgz(r-4.4-emscripten)MCMCprecision_0.4.0.tgz(r-4.3-emscripten)
MCMCprecision.pdf |MCMCprecision.html✨
MCMCprecision/json (API)
NEWS
| # Install 'MCMCprecision' in R: |
| install.packages('MCMCprecision', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/danheck/mcmcprecision/issues
Last updated 5 years agofrom:f1248b7454. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 19 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 19 2024 |
Exports:best_modelsfit_dirichletrdirichletrmarkovstationarystationary_mletransitions
Dependencies:combinatlatticeMatrixRcppRcppArmadilloRcppEigenRcppProgress
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| MCMCprecision: Precision of discrete parameters in transdimensional MCMC | MCMCprecision-package MCMCprecision |
| Precision for the k Best-Performing Models | best_models |
| Estimate Parameters of Dirichlet Distribution | fit_dirichlet |
| Random Sample from Dirichlet Distribution | rdirichlet |
| Generate a sample of a discrete-state Markov chain | rmarkov |
| Precision of stationary distribution for discrete MCMC variables | stationary |
| MLE for stationary distribution of discrete MCMC variables | stationary_mle |
| Summary for Posterior Model Probabilities | summary.stationary |
| Get matrix of observed transition frequencies | transitions |