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:Daniel W. Heck [aut, cre]

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'))

Peer review:

Bug tracker:https://github.com/danheck/mcmcprecision/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

3.70 score 4 packages 42 scripts 756 downloads 7 exports 7 dependencies

Last updated 5 years agofrom:f1248b7454. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-linux-x86_64NOTENov 19 2024

Exports:best_modelsfit_dirichletrdirichletrmarkovstationarystationary_mletransitions

Dependencies:combinatlatticeMatrixRcppRcppArmadilloRcppEigenRcppProgress

Heck, Overstall, Gronau, & Wagenmakers (2018, Statistics & Computing): Methods implemented in MCMCprecision

Rendered fromHeck_2018_Statistics_and_Computing.pdf.asisusingR.rsp::asison Nov 19 2024.

Last update: 2018-08-10
Started: 2018-08-10