MCMCprecision/DESCRIPTION at master · danheck/MCMCprecision · GitHub

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Package: MCMCprecision
Type: Package
Title: Precision of Discrete Parameters in Transdimensional MCMC
Version: 0.4.2
Date: 2025-07-22
Authors@R: c(person("Daniel W.","Heck",
                    email = "daniel.heck@uni-marburg.de",
                    role = c("aut","cre"),
                    comment = c(ORCID = "0000-0002-6302-9252")))
Author: Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>)
Maintainer: Daniel W. Heck <daniel.heck@uni-marburg.de>
Description: 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.
License: GPL-3
Encoding: UTF-8
Depends:
    R (>= 4.0.0)
Imports:
    Rcpp,
    parallel,
    utils,
    stats,
    Matrix,
    combinat
Suggests:
	  testthat,
    R.rsp
LinkingTo:
    Rcpp,
    RcppArmadillo,
    RcppProgress,
    RcppEigen
RoxygenNote: 7.3.2
URL: https://github.com/danheck/MCMCprecision
VignetteBuilder: R.rsp