MCMCprecision-package | R Documentation |
MCMCprecision estimates the precision of the posterior model probabilities in transdimensional Markov chain Monte Carlo methods (e.g., reversible jump MCMC or product-space MCMC). This is useful for applications of transdimensional MCMC such as model selection, mixtures with varying numbers of components, change-point detection, capture-recapture models, phylogenetic trees, variable selection, and for discrete parameters in MCMC output in general.
The main function to assess the estimation uncertainty of discrete MCMC output is
is stationary
.
The method is explained in detail in Heck et al. (2019, Statistics & Computing),
available in the package by calling: vignette("MCMCprecision")
Daniel W. Heck
Heck, D. W., Overstall, A. M., Gronau, Q. F., & Wagenmakers, E.-J. (2019). Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. Statistics & Computing, 29, 631–643. https://dx.doi.org/10.1007/s11222-018-9828-0
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