R: MCMCprecision: Precision of discrete parameters in...

MCMCprecision-package {MCMCprecision} | R Documentation

## MCMCprecision: Precision of discrete parameters in transdimensional MCMC

### Description

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.

### Details

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")`

### Author(s)

Daniel W. Heck

### References

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

### See Also

Useful links:

- https://github.com/danheck/MCMCprecision

[Package MCMCprecision version 0.4.0 Index]