| mcmcse-package | Monte Carlo Standard Errors for MCMC |
| batchSize | Batch size (truncation point) selection |
| BVN_Gibbs | MCMC samples from a bivariate normal distribution |
| confRegion | Confidence regions (ellipses) for Monte Carlo estimates |
| ess | Univariate effective sample size (ESS) as described in Gong and Flgal (2015). |
| estvssamp | Create a plot that shows how Monte Carlo estimates change with increasing sample size. |
| is.mcmcse | Check if the class of the object is mcmcse |
| mcmcse | Monte Carlo Standard Errors for MCMC |
| mcse | Compute Monte Carlo standard errors for expectations. |
| mcse.initseq | Multivariate Monte Carlo standard errors for expectations with the initial sequence method of Dai and Jones (2017) |
| mcse.mat | Apply 'mcse' to each column of the MCMC samples. |
| mcse.multi | Multivariate Monte Carlo standard errors for expectations. |
| mcse.q | Compute Monte Carlo standard errors for quantiles. |
| mcse.q.mat | Apply 'mcse.q' to each column of a matrix or data frame of MCMC samples. |
| minESS | Minimum effective sample size required for stable estimation as described in Vats et al. (2015) |
| multiESS | Effective Sample Size of a multivariate Markov chain as described in Vats et al. (2015). |